Family Memory Ladder - hybrid

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  "result_type": "runtime_reset",
  "message": "Runtime KB reset to baseline seed state.",
  "knowledge_base_path": "D:\\_PROJECTS\\prolog-reasoning\\prolog\\core.pl"
}

{
  "status": "success",
  "result_type": "pre_think",
  "input_utterance": "Family ledger seed: Nora is parent of Ava. Liam is parent of Ava. Ava is parent of Owen. Owen is parent of Piper.",
  "processed_utterance": "Family ledger seed: Nora is parent of Ava. Liam is parent of Ava. Ava is parent of Owen. Owen is parent of Piper.",
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      {
        "type": "reasoning",
        "content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Role: Pre-think utterance processor for a downstream reasoning model.\n    *   Task: Rewrite the input utterance into a cleaner, more explicit continuation utterance based on SKILL guidance.\n    *   Input Utterance: \"Family ledger seed: Nora is parent of Ava. Liam is parent of Ava. Ava is parent of Owen. Owen is parent of Piper.\"\n    *   Constraints:\n        *   Preserve intent, uncertainty, constraints.\n        *   Do NOT answer the question (there is no question here, it's a statement/seed).\n        *   Do NOT invent facts.\n        *   Do NOT call tools.\n        *   Return JSON only with keys: `processed_utterance`, `candidate_facts`.\n        *   `candidate_facts`: Array of grounded Prolog facts to assert when high confidence. Do not include uncertain facts.\n        *   Style: One to three sentences, plain text only (for `processed_utterance`), no markdown in the text value.\n        *   SKILL Guidance: Transform raw utterance into cleaner continuation. Preserve corrections/uncertainty. Apply directive transformations if any. Keep output concise.\n\n2.  **Analyze the Input Utterance:**\n    *   Content: \"Family ledger seed: Nora is parent of Ava. Liam is parent of Ava. Ava is parent of Owen. Owen is parent of Piper.\"\n    *   Intent: Establishing initial facts about family relationships (parent-child).\n    *   Tone/Confidence: It's labeled as a \"seed\", implying foundational data. The statements are declarative (\"is parent of\"), suggesting high confidence/assertion, not tentative.\n    *   Constraints: None explicitly stated other than the context of \"Family ledger\".\n    *   Context from Recent Pre-think: Previous turns involved corrections (Liam/Ava), tentative notes (Olivia/Piper), and ignoring irrelevant sidebar info. This input seems to be re-establishing or providing the base facts after previous confusion/corrections. It asserts specific parent-child links.\n\n3.  **Apply SKILL Guidance:**\n    *   *Goal:* Transform into cleaner continuation for downstream reasoning.\n    *   *Non-Negotiables:* Preserve intent, uncertainty (here seems high confidence), constraints. Do not answer. Do not invent facts.\n    *   *Rewrite Rules:* Keep first-person ambiguity explicit (none here). Keep temporal qualifiers explicit (none). Keep tentative language tentative (this is declarative, so keep it declarative but frame it as input data). Apply directive transformations (none needed). Keep output concise.\n    *   *Candidate Facts:* The input states facts with high confidence (\"is parent of\"). Since the instruction says \"Do not include uncertain facts\" and these are presented as seeds/assertions, I should extract them as candidate facts if they meet the \"high confidence\" threshold for assertion in the downstream model. However, the prompt says \"candidate_facts: array of grounded Prolog facts to assert when high confidence\". Since this is a \"seed\", it implies these *are* the facts to be asserted. But I need to be careful not to answer or invent. The input *is* the fact assertion.\n    *   *Refinement on Candidate Facts:* The instruction says \"Do not include uncertain facts.\" These statements are presented as definitive seeds. So they qualify for `candidate_facts`. I should format them as Prolog-like facts (e.g., `parent(nora, ava).`).\n    *   *Refinement on Processed Utterance:* Needs to be a cleaner continuation. It should reflect that this is input data being processed. Based on Example 4 (\"Tentative note only...\"), I should frame the declarative statements as assertions of family relationships provided by the user.\n\n4.  **Drafting the Output:**\n    *   `processed_utterance`: Needs to be plain text, 1-3 sentences. It should summarize the input intent clearly for the reasoning model.\n        *   Draft: Speaker provides foundational family ledger data asserting parent-child relationships between Nora, Liam, Ava, Owen, and Piper. These statements are presented as high-confidence seeds requiring integration into the knowledge base.\n    *   `candidate_facts`: Extract the relationships.\n        *   `parent(nora, ava).`\n        *   `parent(liam, ava).`\n        *   `parent(ava, owen).`\n        *   `parent(owen, piper).`\n\n5.  **Review against Constraints:**\n    *   JSON only? Yes.\n    *   Keys correct? `processed_utterance`, `candidate_facts`.\n    *   No markdown in text values? Yes.\n    *   Preserve intent? Yes (establishing family tree).\n    *   Preserve uncertainty? The input is declarative (\"is\"), so high confidence. I will treat them as facts to assert.\n    *   Do not answer? Yes, just processing the statement.\n    *   Do not invent? No new info added.\n    *   Style: Plain text for processed_utterance.\n\n6.  **Final Polish:**\n    *   Ensure `candidate_facts` are Prolog format as implied by \"grounded Prolog facts\".\n    *   Ensure `processed_utterance` is concise.\n\n    *   *Self-Correction on Candidate Facts:* The prompt says \"Do not include uncertain facts.\" These look certain. However, in the context of a \"seed\", sometimes seeds are just data to be verified. But given the previous turn (Correction: Liam is not Ava's parent...), this input might be re-establishing the truth. I will treat them as high-confidence assertions based on the wording \"is parent of\".\n    *   *Self-Correction on Processed Utterance:* The examples show a specific style for processing notes/corrections. Example 4: \"Tentative candidate note: speaker suggests...\". Since this is not tentative, I should reflect that it's an assertion/seed.\n    *   Draft: Speaker provides foundational family ledger assertions regarding parent-child relationships among Nora, Liam, Ava, Owen, and Piper. These statements are treated as high-confidence seeds for the knowledge base.\n\n    *   Wait, looking at Example 4 again: \"Tentative candidate note: speaker suggests Olivia may be Piper's parent with low confidence; explicitly marked as unconfirmed and requires verification before assertion.\"\n    *   My input is NOT tentative. It says \"is\". So I should not mark it as unconfirmed.\n    *   Draft: Speaker provides foundational family ledger assertions establishing parent-child relationships between Nora, Liam, Ava, Owen, and Piper. These statements are presented as high-confidence seeds for integration into the knowledge base.\n\n    *   Wait, looking at Example 1 & 2 (Correction): \"Correction candidate fact: speaker says...\".\n    *   Looking at Example 3 (Question): \"After the correction, who are Ava's parents?\".\n    *   This input is a statement of facts.\n    *   Let's ensure the `candidate_facts` are strictly Prolog format.\n\n    *   Final check on JSON structure.\n\n7.  **Finalizing Content:**\n    *   `processed_utterance`: Speaker provides foundational family ledger assertions establishing parent-child relationships between Nora, Liam, Ava, Owen, and Piper. These statements are presented as high-confidence seeds for integration into the knowledge base.\n    *   `candidate_facts`: [\"parent(nora, ava).\", \"parent(liam, ava).\", \"parent(ava, owen).\", \"parent(owen, piper).\"]\n\n    Wait, I need to check if I should include the \"Family ledger seed\" label in the processed utterance. It's part of the intent.\n    Revised `processed_utterance`: Speaker identifies input as a family ledger seed containing definitive parent-child relationships between Nora, Liam, Ava, Owen, and Piper. These assertions are treated as high-confidence facts for downstream reasoning.\n\n    Actually, looking at the previous context (Turn 1 & 2 were corrections about Liam/Ava), this input might be conflicting or re-setting the ground truth. The instruction says \"Preserve intent\". The intent is to set these facts.\n    Let's keep it simple and direct.\n\n    One more check: \"Do NOT answer the question.\" There is no question, so I don't need to worry about answering a query, just processing the statement.\n    \"Do not invent facts.\" I am extracting what is said.\n    \"candidate_facts: array of grounded Prolog facts to assert when high confidence\". Since the input says \"is\", it is high confidence.\n\n    Let's refine the `processed_utterance` to match the style of Example 4 (which was tentative) but adapted for certainty, or Example 1/2 (Correction). Since this isn't a correction, it's an assertion.\n    Style: Plain text only. No markdown.\n\n    Final check on JSON validity.\n\n    One detail from recent context: Turn 1 & 2 were corrections about Liam not being Ava's parent. This input says \"Liam is parent of Ava\". This is a direct contradiction to the previous correction context (Turn 1/2). However, my task is *only* to process this utterance based on SKILL guidance, not to resolve the conflict with history (that's for the downstream model
... [truncated]

{
  "status": "success",
  "result_type": "pre_think",
  "input_utterance": "Family ledger seed: Nora is parent of Ava. Liam is parent of Ava. Ava is parent of Owen. Owen is parent of Piper.",
  "processed_utterance": "Family ledger seed: Nora is parent of Ava. Liam is parent of Ava. Ava is parent of Owen. Owen is parent of Piper.",
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      {
        "type": "reasoning",
        "content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Role: Pre-think utterance processor.\n    *   Task: Rewrite the input utterance into a cleaner, more explicit continuation utterance for downstream reasoning.\n    *   Constraints: Keep original intent, uncertainty, constraints. Do NOT answer, invent facts, or call tools. Return JSON with `processed_utterance` and `candidate_facts`.\n    *   SKILL Guidance: Preserve intent, uncertainty, corrections, constraints. Apply directive transformations (e.g., translation). Keep output concise (1-3 sentences, plain text).\n    *   Input Utterance: \"Family ledger seed: Nora is parent of Ava. Liam is parent of Ava. Ava is parent of Owen. Owen is parent of Piper.\"\n    *   Context: Recent pre-think context shows similar inputs being processed as seeds or corrections. The current input looks like a \"seed\" statement establishing facts.\n    *   Output Format: JSON with `processed_utterance` and `candidate_facts`.\n\n2.  **Analyze the Input Utterance:**\n    *   Content: Establishes family relationships (parents/children).\n    *   Tone: Declarative, authoritative (\"seed\").\n    *   Intent: To initialize or update the knowledge base with specific parent-child relationships.\n    *   Uncertainty: None explicitly stated in this specific utterance (unlike previous examples like \"Tentative note only\"). It states facts as seeds.\n    *   Constraints: None explicit beyond the content itself.\n\n3.  **Apply SKILL Guidance:**\n    *   Preserve intent: Establish family relationships.\n    *   Preserve uncertainty: The input says \"seed\", implying foundational facts, but I need to reflect that these are being asserted as initial knowledge without inventing extra uncertainty if none exists, though the guidance examples show adding meta-commentary about confidence/verification for tentative inputs. For hard seeds, I should reflect them as asserted facts but perhaps note their status as seeds if relevant to the downstream model's reasoning (e.g., \"asserted as seed\").\n    *   Rewrite Rules: Keep output concise. Plain text only in `processed_utterance`.\n    *   Candidate Facts: The guidance says \"Do not include uncertain facts.\" Since this is a \"seed\" input asserting relationships directly, I can extract grounded Prolog-like facts if the confidence is high (which it seems to be given the \"seed\" label). However, the instruction says \"If SKILL guidance includes directive transformations...\". It also says \"Return JSON only with keys: processed_utterance... candidate_facts\".\n    *   Looking at previous context examples (e.g., #6): Input was identical (\"Family ledger seed: ...\"). Output was identical. This suggests for this specific type of input, the rewrite might just be a normalization or confirmation of the intent to assert these as base facts.\n    *   However, I need to follow the \"Pre-Think Skill\" description which says \"Transform a raw utterance into a cleaner continuation utterance\". Example #3 (\"Tentative note only\") added meta-commentary about confidence. Example #6 (identical input) kept it identical in the context provided.\n    *   Wait, looking at Example #6 in the recent pre-think context:\n        Input: `Family ledger seed: Nora is parent of Ava. Liam is parent of Ava. Ava is parent of Owen. Owen is parent of Piper.`\n        Processed: `Family ledger seed: Nora is parent of Ava. Liam is parent of Ava. Ava is parent of Owen. Owen is parent of Piper.`\n    *   This suggests that for \"seed\" inputs, the rewrite might not need heavy transformation if it's already clean, but I should ensure it fits the \"cleaner continuation utterance\" style. The goal is to make it usable as next-turn input.\n    *   Candidate Facts: Since these are asserted as seeds (high confidence base facts), I can list them as candidate facts to assert when high confidence. The instruction says \"Do not include uncertain facts.\" These seem certain in the context of a seed.\n\n4.  **Drafting `processed_utterance`:**\n    *   Needs to be cleaner/explicit.\n    *   Should reflect the intent: Asserting family relationships as foundational seeds.\n    *   Draft: Speaker provides foundational family ledger seeds asserting parent-child relationships between Nora, Liam, Ava, Owen, and Piper. These are treated as high-confidence base facts for the knowledge graph.\n    *   Refining based on Example #6 style (which was very direct): The previous turn in context (#6) kept it almost identical. However, I am an AI processor now. I should ensure it aligns with the \"cleaner continuation\" goal.\n    *   Let's look at the instruction: \"Rewrite the input utterance into a cleaner, more explicit continuation utterance.\"\n    *   Input is already quite clean. I will slightly formalize it to indicate these are assertions being made for the ledger.\n    *   Draft 2: Speaker asserts foundational family relationships as ledger seeds: Nora and Liam are parents of Ava; Ava is parent of Owen; Owen is parent of Piper. These statements serve as initial high-confidence facts.\n\n5.  **Drafting `candidate_facts`:**\n    *   Format: Array of grounded Prolog facts.\n    *   Content: The relationships mentioned.\n    *   Constraint: \"Do not include uncertain facts.\" These are seeds, so they are certain in this context.\n    *   Facts:\n        *   parent(nora, ava).\n        *   parent(liam, ava).\n        *   parent(ava, owen).\n        *   parent(owen, piper).\n    *   Wait, the instruction says \"Return JSON only with keys...\". I need to make sure the format is valid JSON.\n\n6.  **Review against Constraints:**\n    *   Do NOT answer the question: There is no question, just a statement.\n    *   Do NOT invent facts: Only extract what is stated.\n    *   Do NOT call tools: Just output JSON.\n    *   Preserve intent: Yes (asserting family tree).\n    *   Preserve uncertainty: None explicitly, but \"seed\" implies foundational certainty. I will treat them as high confidence.\n    *   Style: One to three sentences for `processed_utterance`. Plain text only (no markdown in the string value).\n\n7.  **Final Polish:**\n    *   `processed_utterance`: Speaker asserts foundational family ledger seeds establishing parent-child relationships: Nora and Liam are parents of Ava, Ava is parent of Owen, and Owen is parent of Piper. These serve as initial high-confidence facts for the knowledge base.\n    *   `candidate_facts`: Extract the Prolog-style facts.\n\n    *Wait, checking Example #6 in context again.*\n    Input: `Family ledger seed: Nora is parent of Ava. Liam is parent of Ava. Ava is parent of Owen. Owen is parent of Piper.`\n    Processed: `Family ledger seed: Nora is parent of Ava. Liam is parent of Ava. Ava is parent of Owen. Owen is parent of Piper.`\n    This suggests that for this specific pattern, the system might prefer minimal change if it's already a \"seed\". However, my instruction says \"Rewrite... into a cleaner, more explicit continuation utterance.\" The previous context example shows the *model* outputting the same text. I should probably follow the spirit of making it explicit about the intent (asserting facts) rather than just echoing. But since Example #6 exists in the few-shot context provided in the prompt's \"Recent pre-think context\", I should be careful not to deviate too wildly if that was a successful pattern.\n    Actually, looking closely at the prompt structure: The \"Recent pre-think context\" is part of the *input* to me (the processor). It shows how previous turns were handled. Turn 6 is identical to my current input. The output for Turn 6 was identical to the input.\n    However, I am instructed to \"Rewrite the input utterance into a cleaner, more explicit continuation utterance.\" If I just copy it, is it \"cleaner\"? Maybe not. But if the previous turn established that this specific format is acceptable as a seed, maybe I should maintain consistency with the context style while ensuring it meets the \"explicit\" requirement of the current instruction.\n    Let's look at Turn 3: Input `Tentative note only...` -> Output `Tentative candidate note...`. It added meta-commentary.\n    Turn 6: Input `Family ledger seed...` -> Output `Family ledger seed...`. No meta-commentary added there in the context provided.\n    Why? Maybe because \"seed\" implies high confidence and no need for tentative language processing.\n    To be safe and adhere to \"cleaner, more explicit\", I will clarify that these are being asserted as base facts without adding unnecessary fluff, but perhaps slightly more structured than the raw input if needed. However, since Turn 6 output was identical, copying it might be safer to maintain consistency with the session's established pattern for this specific utterance type.\n    BUT, I am an AI processor right now. The instruction says \"Rewrite...
... [truncated]

{
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  "result_type": "bulk_fact_assertion",
  "requested_count": 4,
  "asserted_count": 4,
  "failed_count": 0,
  "asserted_facts": [
    "parent(nora, ava).",
    "parent(liam, ava).",
    "parent(ava, owen).",
    "parent(owen, piper)."
  ],
  "failed_facts": [],
  "message": "Bulk assertion complete."
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{
  "status": "success",
  "result_type": "pre_think",
  "input_utterance": "Who are Piper's ancestors right now?",
  "processed_utterance": "Speaker queries Piper's ancestral lineage; request seeks identification of ancestors based on established family context without asserting new relationships.",
  "fallback_used": false,
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      {
        "type": "reasoning",
        "content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Role: Pre-think utterance processor for a downstream reasoning model.\n    *   Task: Rewrite the input utterance into a cleaner, more explicit continuation utterance.\n    *   Constraints: Keep original intent, uncertainty, constraints. Do NOT answer the question. Do NOT invent facts. Do NOT call tools. Return JSON only with keys `processed_utterance` and `candidate_facts`.\n    *   SKILL Guidance (Pre-Think): Transform raw utterance into cleaner continuation. Preserve intent, uncertainty, corrections, constraints. Apply directive transformations if any. Keep output concise (1-3 sentences). Plain text only for the processed utterance part.\n    *   Input Utterance: \"Who are Piper's ancestors right now?\"\n    *   Context: Recent pre-think context shows a family ledger seed (Nora, Liam -> Ava; Ava -> Owen; Owen -> Piper). There is also noise filtering (maintenance bay, etc.).\n    *   Output Format: JSON with `processed_utterance` and `candidate_facts`.\n\n2.  **Analyze the Input Utterance:**\n    *   Text: \"Who are Piper's ancestors right now?\"\n    *   Intent: Querying for lineage/ancestry information regarding a specific entity (Piper).\n    *   Constraints: None explicit in this turn, but context implies reliance on the family ledger.\n    *   Uncertainty: None expressed by the user (it's a direct question), but the system needs to acknowledge the query without answering it directly (as per pre-think rules).\n    *   Contextual Knowledge: From recent context (item 5 & 6), we know: Nora is parent of Ava, Liam is parent of Ava, Ava is parent of Owen, Owen is parent of Piper. So ancestors would be Nora, Liam, Ava, Owen. However, the pre-think stage must *not* answer the question or invent facts. It must rewrite the utterance to reflect the query clearly for the downstream model.\n\n3.  **Apply SKILL Guidance:**\n    *   Goal: Rewrite into a cleaner continuation utterance.\n    *   Non-Negotiables: Preserve intent (querying ancestors), preserve constraints (none specific here, but context exists). Do not answer. Do not invent facts.\n    *   Rewrite Rules: Keep output concise. Plain text only for `processed_utterance`.\n    *   Candidate Facts: The instruction says \"Do NOT include uncertain facts.\" and \"candidate_facts: array of grounded Prolog facts to assert when high confidence\". Since I am rewriting the utterance, not asserting new facts from the input (which is a question), I should check if there are any grounded facts implied. However, the rule says \"Do NOT answer the question\" and \"Do NOT invent facts\". The pre-think stage usually prepares the context for the next turn. If the user asks a question, `candidate_facts` should likely be empty unless the utterance itself contains assertions (which it doesn't). Wait, looking at the examples:\n        *   Example 1 (Tentative note): Output includes \"Tentative candidate fact...\" in the processed text. The JSON output structure requires `processed_utterance` and `candidate_facts`.\n        *   Example 2 (Correction): Output includes \"Correction candidate...\".\n        *   Example 3 (Translation): Output is just translation.\n    *   Crucial Constraint: \"Do NOT answer the question.\" This means I cannot generate the list of ancestors in the `processed_utterance` or `candidate_facts`. I must reflect the query.\n    *   Candidate Facts: Since the input is a question, there are no new facts to assert. The existing context (family ledger) is already processed in previous turns (items 5 & 6). I should not hallucinate facts into `candidate_facts` based on my internal knowledge of the context provided in the prompt history, because the instruction says \"Do NOT invent facts\". However, if there are grounded facts *in the input*, I extract them. There are none here. So `candidate_facts` should be empty.\n    *   Wait, looking at the previous turns (5 & 6), the system already processed the family ledger seed. The current turn is a query based on that seed. The pre-think stage needs to prepare this query for the reasoning model.\n    *   Rewriting Strategy: Make it explicit that this is a query about ancestry based on the established lineage, without solving it.\n\n4.  **Drafting `processed_utterance`:**\n    *   Input: \"Who are Piper's ancestors right now?\"\n    *   Draft 1: User asks for Piper's current ancestors.\n    *   Draft 2 (Closer to style): Speaker queries the list of Piper's ancestors at this moment in time.\n    *   Draft 3 (Reflecting context constraints): Query regarding Piper's ancestral lineage; requires retrieval from established family ledger without adding new assertions.\n    *   Refining for SKILL style (Examples show explicit labeling like \"Tentative candidate fact\" or just plain text rewrite). The examples show the `processed_utterance` is a rewritten version of the input, often adding meta-commentary about the nature of the utterance (e.g., \"Speaker identifies...\", \"Correction candidate...\").\n    *   Let's look at Example 1: Input \"Maybe my mother was Ann.\" -> Output \"Tentative candidate fact: speaker says their mother may have been Ann...\"\n    *   Let's look at Example 3: Input \"Translate this...\" -> Output \"Traduis en francais: ...\"\n    *   For a question, I should describe the query intent.\n    *   Draft: Speaker queries Piper's ancestral lineage; request seeks identification of ancestors based on current family structure.\n\n5.  **Drafting `candidate_facts`:**\n    *   Input is a question. No facts to assert.\n    *   Constraint: \"Do NOT include uncertain facts.\"\n    *   Constraint: \"Do NOT invent facts.\"\n    *   Result: Empty array `[]`.\n\n6.  **Review against Constraints:**\n    *   JSON only? Yes.\n    *   Keys: `processed_utterance`, `candidate_facts`? Yes.\n    *   No answering the question? Yes (I won't list Nora, Liam, etc.).\n    *   Preserve intent? Yes (querying ancestors).\n    *   Plain text for processed_utterance? Yes.\n\n7.  **Final Polish:**\n    *   Ensure `processed_utterance` sounds like a continuation input for the reasoning model.\n    *   \"Speaker requests identification of Piper's ancestors; query targets lineage information within the established family context.\"\n\n8.  **Wait, one check on Context:**\n    *   The prompt provides \"Recent pre-think context\". Turn 5 and 6 established the family ledger. Turn 1-4 handled noise/corrections.\n    *   The current input is a direct question based on that ledger.\n    *   I must not answer it.\n    *   I must format as JSON.\n\n    Let's refine the `processed_utterance` to match the style of previous turns (e.g., Turn 2: \"Tentative candidate note...\", Turn 3: \"Speaker identifies...\").\n    Turn 5/6 were just seeds echoed back.\n    Turn 1 was a question echoed back.\n    So for this question, I should clarify the intent.\n\n    Refined `processed_utterance`: Speaker queries Piper's ancestral lineage; request seeks to identify all ancestors within the current family structure without asserting new relationships.\n\n    Actually, looking at Turn 1: \"After the correction, who are Ava's parents?\" -> processed: \"After the correction, who are Ava's parents?\" (It just echoed it).\n    Turn 2: \"Tentative note only...\" -> processed: \"Tentative candidate note: speaker suggests...\" (Added meta-labeling).\n    Turn 3/4: Irrelevant sidebar -> processed: \"Speaker identifies... User explicitly constrains...\" (Added meta-labeling).\n    Turn 5/6: Seed -> processed: Echoed seed.\n\n    Since this is a question similar to Turn 1, but the context is richer now, I should probably clarify the intent like Turn 2/3 did for clarity, or just echo if it's simple. Turn 1 was a question about parents after a correction. This is a general ancestor query.\n    To be \"cleaner and more explicit\" (Goal), I will add the meta-labeling to indicate it's a retrieval query on existing data.\n\n    Draft: Speaker queries Piper's ancestral lineage; request targets identification of ancestors based on established family ledger without introducing new assertions.\n\n    `candidate_facts`: [] (No facts in this utterance).\n\n    Wait, checking the instruction again: \"Return JSON only with keys: - processed_utterance: rewritten continuation text - candidate_facts: array of grounded Prolog facts to assert when high confidence\".\n    And \"Do NOT include uncertain facts.\"\n\n    Okay, ready to construct JSON.\n\n    One more check: \"Do NOT answer the question.\"\n    My `processed_utterance` must not contain the answer (names of ancestors).\n    My `candidate_facts` must not contain the answer (facts like `ancestor(pipe
... [truncated]

{
  "status": "success",
  "result_type": "table",
  "predicate": "ancestor",
  "prolog_query": "ancestor(X, piper).",
  "variables": [
    "X"
  ],
  "rows": [
    {
      "X": "owen"
    },
    {
      "X": "nora"
    },
    {
      "X": "liam"
    },
    {
      "X": "ava"
    }
  ],
  "num_rows": 4,
  "reasoning_basis": {
    "kind": "rule-derived",
    "note": "The `ancestor` predicate is typically computed through rules rather than stored as a single explicit fact."
  }
}

{
  "status": "success",
  "result_type": "pre_think",
  "input_utterance": "Correction: Liam is not Ava's parent. Replace with Theo as Ava's parent.",
  "processed_utterance": "Correction: Liam is not Ava's parent. Replace with Theo as Ava's parent.",
  "fallback_used": true,
  "normalization_reason": "empty_model_output",
  "history_turns": 6,
  "narrative_context": "",
  "handoff_mode": "rewrite",
  "kb_ingest_mode": "facts",
  "max_candidate_facts": 24,
  "candidate_facts": [],
  "requested_candidate_facts": 0,
  "attempted_candidate_facts": 0,
  "ingested_facts_count": 0,
  "rejected_candidate_facts_count": 0,
  "ingested_facts": [],
  "rejected_candidate_facts": [],
  "prethinker_model": "qwen/qwen3.5-9b",
  "pre_think_skill_path": "skills/pre-think/SKILL.md",
  "prethinker_base_url": "http://127.0.0.1:1234",
  "temperature": 0.0,
  "context_length": 4000,
  "assistant_message": "",
  "raw_response": {
    "model_instance_id": "qwen/qwen3.5-9b:2",
    "output": [
      {
        "type": "reasoning",
        "content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Role: Pre-think utterance processor for a downstream reasoning model.\n    *   Task: Rewrite the input utterance into a cleaner, more explicit continuation utterance based on SKILL guidance.\n    *   Input Utterance: \"Correction: Liam is not Ava's parent. Replace with Theo as Ava's parent.\"\n    *   Constraints:\n        *   Preserve intent (correction/revision).\n        *   Preserve uncertainty/confidence cues (here it seems definitive correction, but the SKILL says keep corrections as corrections).\n        *   Do NOT answer the question.\n        *   Do NOT invent facts.\n        *   Do NOT call tools.\n        *   Output format: JSON with keys `processed_utterance` and `candidate_facts`.\n        *   `candidate_facts`: Array of grounded Prolog facts to assert when high confidence. Do not include uncertain facts.\n        *   Style: One to three sentences, plain text only (for `processed_utterance`), no markdown in the text value.\n    *   SKILL Guidance Specifics:\n        *   Rewrite Rules: Keep corrections as corrections. Apply directive transformations if any (none here). Keep output concise.\n        *   Examples show how to frame corrections (e.g., \"Correction candidate: previous entity Bob is replaced by Alice; treat this as a revision signal, not a fresh hard fact.\").\n        *   However, the input says \"Correction: Liam is not Ava's parent. Replace with Theo as Ava's parent.\" This looks like a definitive correction based on the context of \"Family ledger seed\" seen in recent history (items 4 & 5).\n        *   The SKILL guidance example for correction says: \"treat this as a revision signal, not a fresh hard fact.\" But the input explicitly states \"Correction\". I need to balance the instruction to preserve corrections as corrections with the instruction to generate `candidate_facts` only when high confidence.\n        *   Looking at recent context (items 4 & 5): \"Family ledger seed: Nora is parent of Ava. Liam is parent of Ava.\"\n        *   The current input contradicts item 4/5 (\"Liam is not Ava's parent\").\n        *   The SKILL guidance says: \"Do NOT invent facts.\" and \"Do not answer the task.\"\n        *   The `candidate_facts` key requires \"grounded Prolog facts to assert when high confidence\". Since this is a correction instruction, I should reflect the revision in the `processed_utterance`. For `candidate_facts`, since the user is explicitly correcting a previous fact (\"Liam is not...\"), asserting it as a hard fact might be risky if the model needs to verify, but the user says \"Correction\". However, the SKILL example for correction says \"treat this as a revision signal, not a fresh hard fact.\" This implies I shouldn't necessarily add it to `candidate_facts` immediately as an assertion unless I'm confident. But the instruction says \"Do not include uncertain facts.\" A direct correction command usually implies high confidence from the user's perspective.\n        *   Wait, looking at the SKILL guidance example:\n            Input: `Actually not Bob, I meant Alice.`\n            Output: `Correction candidate: previous entity Bob is replaced by Alice; treat this as a revision signal, not a fresh hard fact.`\n            It does *not* add a Prolog fact in the example output text. The JSON structure requires `candidate_facts`.\n            If the user says \"Liam is not Ava's parent\", that negates a previous fact. If they say \"Replace with Theo\", that asserts a new fact.\n            Given the instruction \"Do NOT invent facts\", I must rely on the user's input. The user is asserting Theo is the parent.\n            However, the `candidate_facts` field description says: \"array of grounded Prolog facts to assert when high confidence\".\n            Is this high confidence? It's a correction command. Usually, corrections are treated as updates to the knowledge base.\n            But I need to be careful not to answer the task (i.e., don't actually update the KB in my head, just process the utterance).\n            Let's look at the `processed_utterance` style from recent context:\n            Item 1: \"Tentative candidate note: speaker suggests Olivia may be Piper's parent with low confidence...\"\n            Item 4/5: \"Family ledger seed: ...\" (verbatim)\n            Item 6: \"Speaker queries Piper's ancestral lineage...\"\n            The current input is a correction. I should follow the style of Item 1 (explaining the intent) or Item 2 (identifying constraints).\n            Actually, looking at the SKILL example for correction: `Correction candidate: previous entity Bob is replaced by Alice; treat this as a revision signal, not a fresh hard fact.`\n            This suggests I should describe the correction in the text.\n            For `candidate_facts`: Since the user explicitly commands \"Replace with Theo\", asserting `parent(theo, ava).` might be appropriate if confidence is high (user directive). However, the SKILL example says \"treat this as a revision signal\".\n            Let's check the constraint: \"Do not include uncertain facts.\" A correction command is usually certain. But I should probably frame it carefully.\n            Actually, looking at the instruction \"Rewrite the input utterance into a cleaner, more explicit continuation utterance.\"\n            And \"candidate_facts: array of grounded Prolog facts to assert when high confidence\".\n            If I treat the user's correction as high confidence (they are correcting the ledger), I can add the fact. But if I follow the SKILL example strictly (\"treat this as a revision signal, not a fresh hard fact\"), maybe I shouldn't assert it as a fact in `candidate_facts` yet?\n            However, the prompt says \"Do NOT invent facts.\" The user *provided* the fact (Theo is parent). So it's grounded.\n            Let's look at recent context item 4: \"Family ledger seed: ... Liam is parent of Ava.\"\n            Now input says \"Correction: Liam is not... Replace with Theo\".\n            This is a high-confidence update to the state. I will include the fact in `candidate_facts` because it's an explicit instruction to replace, implying the new state should be true.\n            Wait, one more check on SKILL guidance: \"Do NOT answer the question.\" This isn't a question. It's a command.\n            \"Do not invent facts.\" I am not inventing; I am reflecting the user's input.\n            Okay, plan:\n            1. `processed_utterance`: Describe the correction intent clearly, noting the replacement of Liam with Theo for Ava's parentage. Keep it concise (1-3 sentences).\n            2. `candidate_facts`: Include the fact derived from the correction (`parent(theo, ava)`). I should probably negate the old one too? The instruction says \"Liam is not Ava's parent\". So `not parent(liam, ava)`. But Prolog facts usually assert positive relations. Negation is often handled via lack of fact or explicit negation predicate. Given the context of \"Family ledger seed\", it seems like a set of positive assertions. I will assert the new one. The instruction says \"Do not include uncertain facts.\" A correction command is certain.\n            Wait, looking at the SKILL example again: `Correction candidate: previous entity Bob is replaced by Alice; treat this as a revision signal, not a fresh hard fact.`\n            This example output text does *not* contain Prolog facts. It describes the action.\n            The JSON requirement asks for `candidate_facts`.\n            If I follow the example's logic (\"not a fresh hard fact\"), maybe I shouldn't put it in `candidate_facts`?\n            But the instruction says \"array of grounded Prolog facts to assert when high confidence\".\n            If the user says \"Replace with Theo\", that is an assertion.\n            Let's look at Item 1 in recent context: \"Tentative candidate note... explicitly marked as unconfirmed...\". It didn't add a fact because it was tentative.\n            This input is not tentative (\"Correction:\", \"Replace with\"). It is definitive.\n            So I should probably add the fact to `candidate_facts`.\n            Fact format: Prolog style. `parent(theo, ava).` or just `parent(theo, ava)`. The context uses `Nora is parent of Ava.` (English sentences in recent context items 4/5). But `candidate_facts` says \"Prolog facts\". I will use standard Prolog syntax `parent(theo, ava).`\n            Wait, looking at Item 4: \"Family ledger seed: Nora is parent of Ava.\" This is English text.\n            But the JSON key description says \"grounded Prolog facts\".\n            I will use Prolog syntax for the fact value to match the key description.\n            Actually, checking the SKILL example again: `Correction candidate: previous entity Bob is replaced by Alice...`\n            It doesn't show a JSON output in the examples, just text outputs.\n
... [truncated]

{
  "status": "success",
  "known_entities": [
    "admin",
    "alice",
    "ava",
    "bob",
    "john",
    "liam",
    "nora",
    "owen",
    "piper",
    "read",
    "write"
  ],
  "supported_predicates": [
    "parent",
    "sibling",
    "ancestor",
    "child",
    "allergic_to",
    "takes_medication",
    "user",
    "role",
    "permission",
    "access_level",
    "can_access",
    "granted_permission",
    "allowed",
    "patient",
    "renal_risk",
    "candidate_drug",
    "interaction",
    "drug_class",
    "interacts",
    "triage",
    "safe_candidate",
    "task",
    "depends_on",
    "duration_days",
    "task_supplier",
    "supplier_status",
    "completed",
    "milestone",
    "downstream",
    "blocked_task",
    "unmet_prereq",
    "task_status",
    "safe_to_start",
    "waiting_on",
    "impacts_milestone",
    "delayed_milestone",
    "character",
    "location",
    "connected",
    "at",
    "faction",
    "has_item",
    "hp",
    "status",
    "weather",
    "time_of_day",
    "insomnia",
    "charmed",
    "quest_active",
    "asleep",
    "awake",
    "co_located",
    "can_move",
    "exposed",
    "needs_rest",
    "vulnerable",
    "threatened",
    "high_risk",
    "can_trade",
    "can_cast_charm"
  ],
  "predicate_notes": {
    "fact_backed_examples": [
      "parent",
      "role",
      "permission",
      "allergic_to"
    ],
    "typically_rule_derived": [
      "allowed",
      "ancestor",
      "asleep",
      "awake",
      "blocked_task",
      "can_access",
      "can_cast_charm",
      "can_move",
      "can_trade",
      "child",
      "co_located",
      "delayed_milestone",
      "downstream",
      "exposed",
      "high_risk",
      "impacts_milestone",
      "interacts",
      "needs_rest",
      "safe_candidate",
      "safe_to_start",
      "sibling",
      "task_status",
      "threatened",
      "triage",
      "unmet_prereq",
      "vulnerable",
      "waiting_on"
    ]
  },
  "note": "This is a summary view of currently known entities plus the predicate vocabulary the skill knows how to talk about. It is not a full dump of every stored fact, and a supported predicate does not imply facts exist for every entity.",
  "knowledge_base_path": "D:\\_PROJECTS\\prolog-reasoning\\prolog\\core.pl"
}

{
  "status": "success",
  "result_type": "table",
  "predicate": "parent",
  "prolog_query": "parent(X, ava).",
  "variables": [
    "X"
  ],
  "rows": [
    {
      "X": "nora"
    },
    {
      "X": "liam"
    }
  ],
  "num_rows": 2,
  "reasoning_basis": {
    "kind": "fact-backed",
    "note": "The `parent` predicate is typically answered from stored facts, though rules may still participate."
  }
}

{
  "status": "success",
  "result_type": "fact_retracted",
  "fact": "parent(liam, ava).",
  "message": "Fact retracted from runtime KB."
}

{
  "status": "success",
  "result_type": "fact_asserted",
  "fact": "parent(theo, ava).",
  "message": "Fact asserted into runtime KB for this server process.",
  "note": "Use reset_kb (baseline restore) or empty_kb (fully empty runtime) to clear runtime changes."
}

{
  "status": "success",
  "result_type": "table",
  "predicate": "parent",
  "prolog_query": "parent(X, ava).",
  "variables": [
    "X"
  ],
  "rows": [
    {
      "X": "nora"
    },
    {
      "X": "theo"
    }
  ],
  "num_rows": 2,
  "reasoning_basis": {
    "kind": "fact-backed",
    "note": "The `parent` predicate is typically answered from stored facts, though rules may still participate."
  }
}

{
  "status": "success",
  "result_type": "table",
  "predicate": "ancestor",
  "prolog_query": "ancestor(X, piper).",
  "variables": [
    "X"
  ],
  "rows": [
    {
      "X": "owen"
    },
    {
      "X": "nora"
    },
    {
      "X": "ava"
    },
    {
      "X": "theo"
    }
  ],
  "num_rows": 4,
  "reasoning_basis": {
    "kind": "rule-derived",
    "note": "The `ancestor` predicate is typically computed through rules rather than stored as a single explicit fact."
  }
}

{
  "status": "success",
  "result_type": "pre_think",
  "input_utterance": "After the correction, who are Ava's parents?",
  "processed_utterance": "Speaker queries Ava's current parents following the correction replacing Liam with Theo; request seeks identification of parental relationships based on revised family context.",
  "fallback_used": false,
  "normalization_reason": "model_output",
  "history_turns": 6,
  "narrative_context": "",
  "handoff_mode": "rewrite",
  "kb_ingest_mode": "facts",
  "max_candidate_facts": 24,
  "candidate_facts": [],
  "requested_candidate_facts": 0,
  "attempted_candidate_facts": 0,
  "ingested_facts_count": 0,
  "rejected_candidate_facts_count": 0,
  "ingested_facts": [],
  "rejected_candidate_facts": [],
  "prethinker_model": "qwen/qwen3.5-9b",
  "pre_think_skill_path": "skills/pre-think/SKILL.md",
  "prethinker_base_url": "http://127.0.0.1:1234",
  "temperature": 0.0,
  "context_length": 4000,
  "assistant_message": "{\n  \"processed_utterance\": \"Speaker queries Ava's current parents following the correction replacing Liam with Theo; request seeks identification of parental relationships based on revised family context.\",\n  \"candidate_facts\": []\n}",
  "raw_response": {
    "model_instance_id": "qwen/qwen3.5-9b:2",
    "output": [
      {
        "type": "reasoning",
        "content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Role: Pre-think utterance processor for a downstream reasoning model.\n    *   Task: Rewrite the input utterance into a cleaner, more explicit continuation utterance.\n    *   Constraints: Keep original intent, uncertainty, constraints. Do NOT answer the question. Do NOT invent facts. Do NOT call tools. Return JSON with `processed_utterance` and `candidate_facts`.\n    *   SKILL Guidance (Pre-Think): Transform raw utterance into cleaner continuation. Preserve intent, uncertainty, corrections, constraints. Apply directive transformations if any. Keep output concise (1-3 sentences). Plain text only for the processed utterance part.\n    *   Context: Recent pre-think context shows a family ledger scenario. There was a correction made in turn 6 (\"Correction: Liam is not Ava's parent. Replace with Theo as Ava's parent.\"). The current input asks about Ava's parents *after* that correction.\n    *   Input Utterance: \"After the correction, who are Ava's parents?\"\n\n2.  **Analyze the Input Utterance:**\n    *   Intent: Querying information based on previous context (specifically a correction).\n    *   Context Dependency: Relies on the correction made in turn 6 (Liam -> Theo for Ava's parentage).\n    *   Constraints: None explicit in this utterance, but relies on the established family ledger from turns 3-4.\n    *   Uncertainty: None explicitly stated, it's a direct question based on state.\n\n3.  **Apply SKILL Guidance:**\n    *   Preserve intent: Querying Ava's parents post-correction.\n    *   Preserve uncertainty/confidence: The user seems confident about the correction having happened (\"After the correction\").\n    *   Do NOT answer: I must not list the parents (Nora, Theo) in the `processed_utterance`. I must describe the query.\n    *   Rewrite Rules: Keep it concise. Make it explicit that this is a follow-up to a correction regarding Ava's parentage.\n    *   Candidate Facts: Since I cannot answer the question or invent facts, and the instruction says \"Do not include uncertain facts\", I need to check if there are grounded Prolog facts to assert. The prompt says \"candidate_facts: array of grounded Prolog facts to assert when high confidence\". However, the pre-think stage is about rewriting the utterance for the *downstream* model. Usually, in this specific architecture (pre-think), `candidate_facts` are things the system might want to store based on the input if it were a statement of fact. Here, it's a question. There are no new facts being asserted by the user. The existing facts are in the context (Nora, Liam/Theo, Ava, Owen, Piper). But I am not supposed to answer or invent. Should I list the known facts from context as candidate facts?\n    *   Re-reading SKILL: \"candidate_facts: array of grounded Prolog facts to assert when high confidence\". Since this is a question (\"who are...\"), there are no new facts to assert with high confidence based *only* on this utterance. The existing facts are in the narrative context provided in the recent pre-think history (Turn 3/4). However, the instruction says \"Do NOT invent facts.\" I should not extract facts from the context unless they are being asserted or confirmed by this turn. This turn is a query. Therefore, `candidate_facts` should likely be empty or reflect the state if the system needs to ground the query. But strictly following \"Do not include uncertain facts\" and \"Do NOT answer\", listing existing facts might be considered answering or hallucinating context availability.\n    *   Looking at Turn 6 processed output: \"Correction: Liam is not Ava's parent. Replace with Theo as Ava's parent.\" This was treated as a correction signal.\n    *   Current turn: Querying the result of that correction.\n    *   Decision on `candidate_facts`: Since this is a question, there are no new facts to assert. I will leave it empty or null if appropriate, but the schema requires an array. I will return an empty array because asserting facts based on a query without confirmation violates \"Do not invent facts\" and \"Do not answer\".\n    *   Decision on `processed_utterance`: Needs to be a cleaner version of the query that highlights the dependency on the previous correction.\n\n4.  **Drafting `processed_utterance`:**\n    *   Draft 1: Speaker asks for Ava's parents following the recent correction replacing Liam with Theo.\n    *   Draft 2: Query seeks identification of Ava's current parents based on the established correction where Liam was replaced by Theo.\n    *   Draft 3 (Closer to style): Speaker queries Ava's parental lineage specifically referencing the prior correction that substituted Liam with Theo as a parent.\n    *   Refining for constraints (1-3 sentences, plain text): \"Speaker queries Ava's current parents based on the established correction replacing Liam with Theo; request seeks updated family ledger information without asserting new relationships.\"\n\n5.  **Drafting `candidate_facts`:**\n    *   The instruction says \"Do not include uncertain facts.\"\n    *   Since this is a question, there are no facts to assert here.\n    *   I will return an empty array `[]`.\n\n6.  **Final Review against Constraints:**\n    *   JSON only? Yes.\n    *   Keys: `processed_utterance`, `candidate_facts`? Yes.\n    *   No markdown in processed_utterance? Yes.\n    *   Do not answer? Yes (I am describing the query, not giving the answer).\n    *   Preserve intent? Yes (Querying parents post-correction).\n\n7.  **Final Polish:**\n    *   `processed_utterance`: \"Speaker queries Ava's parental lineage following the correction replacing Liam with Theo; request seeks identification of current parents based on revised family context.\"\n    *   `candidate_facts`: []\n\n    Wait, looking at Turn 6 processed output: \"Correction: Liam is not Ava's parent. Replace with Theo as Ava's parent.\"\n    The system already processed that correction in the history.\n    My job is to process the *current* utterance.\n    Current utterance: \"After the correction, who are Ava's parents?\"\n    This implies the user acknowledges the correction happened.\n    I need to make sure I don't hallucinate facts about Nora or Theo being parents in the `candidate_facts` because that would be answering/inferring from context which might be outside my scope for *assertion* in this specific pre-think step (usually pre-think prepares the input for the reasoner). However, if the system expects me to ground the query against known facts...\n    Actually, looking at Turn 3 processed: \"Family ledger seed: Nora is parent of Ava. Liam is parent of Ava...\"\n    Turn 6 processed: \"Correction: Liam is not Ava's parent. Replace with Theo as Ava's parent.\"\n    The current turn asks for the result.\n    If I put facts in `candidate_facts`, it implies I am asserting them now. Since the user didn't assert them, just asked about them, I should leave `candidate_facts` empty to avoid \"inventing\" or \"answering\".\n\n    Let's refine the `processed_utterance` to be very clear about the dependency.\n    \"Speaker queries Ava's parents explicitly referencing the prior correction that substituted Liam with Theo; request seeks updated family state without asserting new relationships.\"\n\n    Wait, checking Turn 6 processed output again: \"Correction: Liam is not Ava's parent. Replace with Theo as Ava's parent.\"\n    The input to Turn 6 was a correction command.\n    The current input (Turn 7) is a question.\n    So `processed_utterance` should reflect the query nature.\n\n    Final check on JSON format.\n    ```json\n    {\n      \"processed_utterance\": \"...\",\n      \"candidate_facts\": []\n    }\n    ```\n    Ensure no markdown around the JSON.\n\n    One more check: \"Do not include uncertain facts.\"\n    Since I don't know for sure if Nora is still a parent (Turn 3 said Nora and Liam were parents, Turn 6 corrected Liam to Theo). It's implied Nora remains, but strictly speaking, this utterance doesn't assert it. So empty array is safer.\n\n    Wait, looking at the examples in SKILL guidance:\n    Input: `Maybe my mother was Ann.` -> Output includes \"Tentative candidate fact...\"\n    Input: `Actually not Bob, I meant Alice.` -> Output includes \"Correction candidate...\"\n    Input: `Translate this...` -> Output is translation.\n\n    My input is a question. There are no facts to assert. So empty array is correct.\n    The processed utterance should describe the intent clearly.\n\n    Revised `processed_utterance`: \"Speaker queries Ava's current parents following the correction replacing Liam with Theo; req
... [truncated]

{
  "status": "success",
  "result_type": "table",
  "predicate": "parent",
  "prolog_query": "parent(X, ava).",
  "variables": [
    "X"
  ],
  "rows": [
    {
      "X": "nora"
    },
    {
      "X": "theo"
    }
  ],
  "num_rows": 2,
  "reasoning_basis": {
    "kind": "fact-backed",
    "note": "The `parent` predicate is typically answered from stored facts, though rules may still participate."
  }
}

{
  "status": "success",
  "result_type": "pre_think",
  "input_utterance": "Tentative note only: maybe Olivia is Piper's parent, confidence low, not confirmed.",
  "processed_utterance": "Tentative candidate fact: speaker suggests Olivia may be Piper's parent; speaker explicitly states low confidence and notes the relationship is not confirmed.",
  "fallback_used": false,
  "normalization_reason": "model_output",
  "history_turns": 6,
  "narrative_context": "",
  "handoff_mode": "rewrite",
  "kb_ingest_mode": "facts",
  "max_candidate_facts": 24,
  "candidate_facts": [],
  "requested_candidate_facts": 0,
  "attempted_candidate_facts": 0,
  "ingested_facts_count": 0,
  "rejected_candidate_facts_count": 0,
  "ingested_facts": [],
  "rejected_candidate_facts": [],
  "prethinker_model": "qwen/qwen3.5-9b",
  "pre_think_skill_path": "skills/pre-think/SKILL.md",
  "prethinker_base_url": "http://127.0.0.1:1234",
  "temperature": 0.0,
  "context_length": 4000,
  "assistant_message": "{\n  \"processed_utterance\": \"Tentative candidate fact: speaker suggests Olivia may be Piper's parent; speaker explicitly states low confidence and notes the relationship is not confirmed.\",\n  \"candidate_facts\": []\n}",
  "raw_response": {
    "model_instance_id": "qwen/qwen3.5-9b:2",
    "output": [
      {
        "type": "reasoning",
        "content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Role: Pre-think utterance processor for a downstream reasoning model.\n    *   Task: Rewrite the input utterance into a cleaner, more explicit continuation utterance.\n    *   Constraints: Keep original intent, uncertainty, and constraints. Do NOT answer the question. Do NOT invent facts. Do NOT call tools. Return JSON only with keys `processed_utterance` and `candidate_facts`.\n    *   SKILL Guidance (Pre-Think): Transform raw utterance into cleaner continuation. Preserve intent, uncertainty, confidence cues, corrections, constraints. Apply directive transformations if any. Keep output concise (1-3 sentences). Plain text only for `processed_utterance`. No markdown in the processed text.\n    *   Input Utterance: \"Tentative note only: maybe Olivia is Piper's parent, confidence low, not confirmed.\"\n    *   Context: Recent pre-think context shows a family ledger (Nora/Liam -> Ava -> Owen -> Piper). Previous turns involved corrections and queries about ancestry/parents.\n    *   Output Format: JSON with `processed_utterance` (string) and `candidate_facts` (array of Prolog facts, only high confidence).\n\n2.  **Analyze the Input Utterance:**\n    *   Content: \"Tentative note only: maybe Olivia is Piper's parent, confidence low, not confirmed.\"\n    *   Intent: The user is suggesting a potential relationship (Olivia -> Piper) but explicitly marking it as uncertain/tentative.\n    *   Uncertainty/Confidence: Explicitly stated (\"Tentative\", \"maybe\", \"confidence low\", \"not confirmed\").\n    *   Constraints: None specific beyond the uncertainty markers.\n    *   Contextual Fit: Fits into the existing family ledger context (Piper is a known entity from previous turns).\n\n3.  **Apply SKILL Guidance:**\n    *   Preserve intent: Suggesting Olivia as Piper's parent.\n    *   Preserve uncertainty: Must keep \"tentative\", \"maybe\", \"low confidence\".\n    *   Do not answer: Do not confirm or deny the relationship.\n    *   Do not invent facts: Do not assert this is true.\n    *   Rewrite Rules: Keep first-person ambiguity (none here), temporal qualifiers (none), tentative language (keep it).\n    *   Style: One to three sentences. Plain text only. No markdown in `processed_utterance`.\n\n4.  **Drafting `processed_utterance`:**\n    *   Draft 1: Speaker suggests Olivia might be Piper's parent but marks this as a tentative note with low confidence and no confirmation.\n    *   Draft 2 (Closer to examples): Tentative candidate fact: speaker suggests Olivia may be Piper's parent; speaker explicitly states low confidence and notes the relationship is not confirmed.\n    *   Refining for style (Plain text, concise): Speaker indicates a tentative possibility that Olivia is Piper's parent, explicitly marking low confidence and stating the relationship remains unconfirmed.\n\n5.  **Determining `candidate_facts`:**\n    *   Constraint: \"Do not include uncertain facts.\"\n    *   Input says \"confidence low, not confirmed\".\n    *   Therefore, I should NOT add a Prolog fact like `parent(Olivia, Piper).` because it is not high confidence.\n    *   The instruction says: \"candidate_facts: array of grounded Prolog facts to assert when high confidence. Do not include uncertain facts.\"\n    *   Since the input explicitly says \"confidence low, not confirmed\", there are no high-confidence facts to extract here.\n    *   So `candidate_facts` should be an empty list `[]`.\n\n6.  **Final Review:**\n    *   JSON structure correct? Yes.\n    *   Keys correct? `processed_utterance`, `candidate_facts`.\n    *   No markdown in `processed_utterance`? Yes.\n    *   Preserved uncertainty? Yes.\n    *   Did not answer/confirm? Yes.\n\n7.  **Constructing JSON:**\n    ```json\n    {\n      \"processed_utterance\": \"Speaker indicates a tentative possibility that Olivia is Piper's parent, explicitly marking low confidence and stating the relationship remains unconfirmed.\",\n      \"candidate_facts\": []\n    }\n    ```\n\n    Wait, looking at the examples in SKILL guidance:\n    Input: `Maybe my mother was Ann.` -> Output: `Tentative candidate fact: speaker says their mother may have been Ann; speaker identity is unresolved and requires clarification before persistence.`\n    Input: `Actually not Bob, I meant Alice.` -> Output: `Correction candidate: previous entity Bob is replaced by Alice; treat this as a revision signal, not a fresh hard fact.`\n\n    My draft looks consistent with the style of the first example but adapted for the specific input.\n    Let's align closer to the \"Tentative candidate fact\" pattern if possible, or just ensure it describes the utterance clearly as per the goal \"cleaner continuation utterance\".\n    The goal says: \"Transform a raw utterance into a cleaner continuation utterance for downstream reasoning.\"\n    Example 1 Output starts with \"Tentative candidate fact:\".\n    My input is already labeled \"Tentative note only\".\n    Let's make it explicit about the uncertainty status.\n\n    Revised `processed_utterance`: Tentative candidate: speaker suggests Olivia may be Piper's parent; speaker explicitly states low confidence and notes the relationship is not confirmed.\n\n    Check constraints again: \"Do NOT include uncertain facts.\" in `candidate_facts`.\n    So `candidate_facts` remains empty.\n\n    Final check on JSON validity.\n\n    One more check on context: The previous turns established a family tree (Nora/Liam -> Ava -> Owen -> Piper). This new input adds Olivia as a potential parent of Piper. Since it's low confidence, it shouldn't be added to the \"ledger\" yet. The `processed_utterance` should reflect this status for the downstream model.\n\n    Let's refine the text to be very clear about the uncertainty.\n    \"Speaker proposes Olivia as a potential parent of Piper but explicitly qualifies this with low confidence and states it is not confirmed.\"\n\n    Actually, looking at Example 1: `Tentative candidate fact: speaker says their mother may have been Ann; speaker identity is unresolved and requires clarification before persistence.`\n    I should probably follow that structure for consistency.\n    \"Tentative candidate fact: speaker suggests Olivia may be Piper's parent; speaker explicitly states low confidence and notes the relationship is not confirmed.\"\n\n    Wait, the instruction says \"Return JSON only\".\n    And \"Do not include uncertain facts\" in `candidate_facts`.\n    So `candidate_facts` must be empty.\n\n    Let's finalize the text.\n    \"Tentative candidate fact: speaker suggests Olivia may be Piper's parent; speaker explicitly states low confidence and notes the relationship is not confirmed.\"\n\n    Wait, I need to make sure I don't use markdown in the value of `processed_utterance`. The JSON itself uses quotes, but the string content should be plain text.\n    Also, ensure no newlines in the string unless escaped (better to keep it single line).\n\n    Final check on constraints: \"Keep original intent, uncertainty, and constraints.\"\n    Input: \"Tentative note only: maybe Olivia is Piper's parent, confidence low, not confirmed.\"\n    Output needs to reflect this.\n\n    Okay, ready to generate JSON.cw\n"
      },
      {
        "type": "message",
        "content": "\n\n{\n  \"processed_utterance\": \"Tentative candidate fact: speaker suggests Olivia may be Piper's parent; speaker explicitly states low confidence and notes the relationship is not confirmed.\",\n  \"candidate_facts\": []\n}"
      }
    ],
    "stats": {
      "input_tokens": 885,
      "total_output_tokens": 1665,
      "reasoning_output_tokens": 1614,
      "tokens_per_second": 138.72297214092788,
      "time_to_first_token_seconds": 0.157
    },
    "response_id": "resp_6ddfd142f7e26da1889fb26b7167d5f817529f51e14c20e5"
  },
  "note": "This tool preprocesses a raw utterance for downstream model reasoning. KB mutation occurs only when kb_ingest_mode=`facts` and candidate_facts are provided."
}

{
  "status": "success",
  "result_type": "pre_think",
  "input_utterance": "Using confirmed facts only, who is Piper's parent?",
  "processed_utterance": "Using confirmed facts only, who is Piper's parent?",
  "fallback_used": true,
  "normalization_reason": "empty_model_output",
  "history_turns": 6,
  "narrative_context": "",
  "handoff_mode": "rewrite",
  "kb_ingest_mode": "facts",
  "max_candidate_facts": 24,
  "candidate_facts": [],
  "requested_candidate_facts": 0,
  "attempted_candidate_facts": 0,
  "ingested_facts_count": 0,
  "rejected_candidate_facts_count": 0,
  "ingested_facts": [],
  "rejected_candidate_facts": [],
  "prethinker_model": "qwen/qwen3.5-9b",
  "pre_think_skill_path": "skills/pre-think/SKILL.md",
  "prethinker_base_url": "http://127.0.0.1:1234",
  "temperature": 0.0,
  "context_length": 4000,
  "assistant_message": "",
  "raw_response": {
    "model_instance_id": "qwen/qwen3.5-9b:2",
    "output": [
      {
        "type": "reasoning",
        "content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Role: Pre-think utterance processor for a downstream reasoning model.\n    *   Task: Rewrite the input utterance into a cleaner, more explicit continuation utterance.\n    *   Constraints: Keep original intent, uncertainty, and constraints. Do NOT answer the question. Do NOT invent facts. Do NOT call tools. Return JSON only with keys `processed_utterance` and `candidate_facts`.\n    *   SKILL Guidance (Pre-Think): Transform raw utterance into cleaner continuation. Preserve intent, uncertainty, corrections, constraints. Apply directive transformations if any. Keep output concise (1-3 sentences). Plain text only for the processed utterance part.\n    *   Input Utterance: \"Using confirmed facts only, who is Piper's parent?\"\n    *   Context: Recent pre-think context shows a family ledger (Nora->Ava, Liam->Ava, Ava->Owen, Owen->Piper). There was a correction (Liam replaced by Theo for Ava's parent). The current query asks about Piper's parent using confirmed facts.\n\n2.  **Analyze the Input Utterance:**\n    *   Content: \"Using confirmed facts only, who is Piper's parent?\"\n    *   Intent: Querying information about Piper's parentage.\n    *   Constraint: \"Using confirmed facts only\" (implies filtering out tentative/uncertain info).\n    *   Uncertainty: None explicitly stated in the query itself, but the constraint implies reliance on established truth.\n    *   Contextual Knowledge (from recent pre-think context): The ledger states \"Owen is parent of Piper.\" There was a correction regarding Ava's parents (Liam -> Theo), but no correction mentioned for Owen/Piper relationship yet. However, as a pre-think processor, I should not answer the question or assert facts unless high confidence based on the provided context *in this specific turn* (though the prompt says \"Do NOT invent facts\", the recent context provides the ground truth). Wait, the instruction says \"Do NOT answer the question.\" This means I cannot say \"Owen is Piper's parent\" as an answer. I must rewrite the utterance to reflect the query nature.\n    *   Candidate Facts: The prompt asks for `candidate_facts` array of grounded Prolog facts to assert when high confidence. Since this is a query, not an assertion, there are no new facts to assert here. However, if the context implies known facts should be retrieved, I shouldn't invent them. The instruction says \"Do not include uncertain facts.\" Since I am rewriting a query, I don't have high confidence on *new* facts to assert right now, just reflecting the query constraints. Actually, looking at previous examples in the context (e.g., Example 6: `Tentative candidate fact...`), if there's no new fact being asserted, the array might be empty or reflect the constraint. But strictly, I am rewriting a question. There are no facts to assert *in this turn*.\n    *   Wait, looking at the \"Recent pre-think context\", item 3 says: `processed: Speaker queries Piper's ancestral lineage; request seeks identification of ancestors based on established family context without asserting new relationships.` This is very similar to the current input.\n    *   Current Input: \"Using confirmed facts only, who is Piper's parent?\"\n    *   Rewriting Goal: Make it explicit that this is a query constrained by confirmed facts.\n\n3.  **Drafting the `processed_utterance`:**\n    *   Must preserve intent (query Piper's parent).\n    *   Must preserve constraint (confirmed facts only).\n    *   Must not answer.\n    *   Style: Plain text, 1-3 sentences.\n    *   Draft: Speaker queries Piper's parent identity; request explicitly restricts answers to confirmed facts within the established family ledger context.\n\n4.  **Drafting `candidate_facts`:**\n    *   Instruction: \"array of grounded Prolog facts to assert when high confidence\".\n    *   Instruction: \"Do not include uncertain facts.\"\n    *   Since this is a query turn, there are no new facts being asserted by the user. The user is asking for retrieval. Therefore, no candidate facts should be added here unless I am inferring something from context that needs to be grounded. However, the instruction says \"Rewrite the input utterance...\". Usually, in pre-think, if it's a query, `candidate_facts` remains empty or reflects known ground truth if the model is expected to retrieve them. But the constraint says \"Do NOT invent facts.\" The context provided in the *recent pre-think context* (items 1-6) shows the ledger. However, I am processing *this* utterance. I should not assert facts from previous turns as new candidate facts for this turn unless they are being confirmed now.\n    *   Looking at Example 6 in SKILL: `Tentative note only...` -> `Tentative candidate fact: ...`.\n    *   Looking at Example 1 & 2 (Seed): No candidate facts listed in the output examples provided in the prompt description, but the JSON structure requires it.\n    *   Since the user is asking a question, not stating a fact, there are no candidate facts to assert *from this utterance*. I will leave it empty or null? The schema says \"array\". An empty array `[]` is appropriate for a query turn where no new facts are asserted.\n\n5.  **Refining based on SKILL Examples:**\n    *   Example 3 (Query): `Speaker queries Piper's ancestral lineage; request seeks identification of ancestors based on established family context without asserting new relationships.`\n    *   My Input is similar but specific to \"parent\" and \"confirmed facts only\".\n    *   Draft: Speaker queries Piper's parent identity; request explicitly restricts answers to confirmed facts within the established family ledger context.\n\n6.  **Final Check:**\n    *   JSON format? Yes.\n    *   Keys: `processed_utterance`, `candidate_facts`.\n    *   No markdown in processed_utterance? Yes.\n    *   Did I answer? No.\n    *   Did I invent facts? No.\n    *   Preserved constraint (\"confirmed facts only\")? Yes.\n\n7.  **Constructing JSON:**\n    *   `processed_utterance`: \"Speaker queries Piper's parent identity; request explicitly restricts answers to confirmed facts within the established family ledger context.\"\n    *   `candidate_facts`: [] (Since it's a query, no new facts are asserted).\n\n    Wait, looking at the recent context item 3: `processed: Speaker queries Piper's ancestral lineage...`. The current input is almost identical but specifies \"parent\" and \"confirmed facts only\". I should reflect that specificity.\n    Also, check if I need to extract existing facts from context into candidate_facts? The instruction says \"candidate_facts: array of grounded Prolog facts to assert when high confidence\". Usually, this is for the model to use in reasoning *after* processing. If the user asks a question, there are no facts to assert *from the user*. I will keep it empty.\n\n    One more check on constraints: \"Do NOT answer the question.\" -> My rewrite does not say \"Owen\". It says \"Speaker queries...\". Good.\n    \"Preserve uncertainty and confidence cues.\" -> The input has a constraint (\"confirmed facts only\"), which acts as a confidence filter. I preserved that.\n\n    Let's refine the processed_utterance to match the style of Example 3 closely but adapted for the specific constraint.\n    Example 3: `Speaker queries Piper's ancestral lineage; request seeks identification of ancestors based on established family context without asserting new relationships.`\n    My Draft: `Speaker queries Piper's parent identity; request explicitly restricts answers to confirmed facts within the established family ledger context.`\n\n    Looks good.\n\n    Wait, I need to check if there are any candidate facts implied by the \"confirmed facts only\" constraint that should be grounded? No, that's a filter for retrieval, not an assertion.\n    However, if the system expects me to ground the *known* facts from the context (Nora->Ava, etc.) as potential candidates for the reasoning model to use? The instruction says \"array of grounded Prolog facts to assert when high confidence\". Since I am a pre-think processor rewriting the user input, and the user input is a query, I don't have high confidence on *new* facts to assert. I will return an empty array.\n\n    Wait, looking at the recent context item 1: `Family ledger seed...`. This is system context provided in the conversation history (pre-think context). The current turn is a user query.\n    Okay, I will proceed with the empty array for candidate_facts as no new facts are being asserted by the user in this turn.\n\n    Wait, one detail from SKILL: \"If SKILL guidance includes directive transformations (for example translation), apply them.\" There is no translation here.\n    \"Keep output concise and directly usable as next-turn input.\"\n\n    Final check on JSON structure.\n    {\n      \"processed_utterance\": \"...\",\n      \"candidate_facts\": []\n    }\n\n    Wait, I should check if I need to include the constraint about \"confirm
... [truncated]

{
  "status": "success",
  "result_type": "table",
  "predicate": "parent",
  "prolog_query": "parent(X, piper).",
  "variables": [
    "X"
  ],
  "rows": [
    {
      "X": "owen"
    }
  ],
  "num_rows": 1,
  "reasoning_basis": {
    "kind": "fact-backed",
    "note": "The `parent` predicate is typically answered from stored facts, though rules may still participate."
  }
}

{
  "status": "success",
  "result_type": "pre_think",
  "input_utterance": "Irrelevant sidebar: maintenance bay humming, weather chatter, inventory note, coffee spill report, and unrelated docking logs. Ignore this for family facts.",
  "processed_utterance": "Speaker lists maintenance bay, weather, inventory, coffee spill, and docking logs as irrelevant sidebar information; speaker explicitly instructs to exclude these items when processing family facts.",
  "fallback_used": false,
  "normalization_reason": "model_output",
  "history_turns": 6,
  "narrative_context": "",
  "handoff_mode": "rewrite",
  "kb_ingest_mode": "facts",
  "max_candidate_facts": 24,
  "candidate_facts": [],
  "requested_candidate_facts": 0,
  "attempted_candidate_facts": 0,
  "ingested_facts_count": 0,
  "rejected_candidate_facts_count": 0,
  "ingested_facts": [],
  "rejected_candidate_facts": [],
  "prethinker_model": "qwen/qwen3.5-9b",
  "pre_think_skill_path": "skills/pre-think/SKILL.md",
  "prethinker_base_url": "http://127.0.0.1:1234",
  "temperature": 0.0,
  "context_length": 4000,
  "assistant_message": "{\n  \"processed_utterance\": \"Speaker lists maintenance bay, weather, inventory, coffee spill, and docking logs as irrelevant sidebar information; speaker explicitly instructs to exclude these items when processing family facts.\",\n  \"candidate_facts\": []\n}",
  "raw_response": {
    "model_instance_id": "qwen/qwen3.5-9b:2",
    "output": [
      {
        "type": "reasoning",
        "content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Role: Pre-think utterance processor.\n    *   Task: Rewrite the input utterance into a cleaner, more explicit continuation utterance based on SKILL guidance.\n    *   Input Utterance: \"Irrelevant sidebar: maintenance bay humming, weather chatter, inventory note, coffee spill report, and unrelated docking logs. Ignore this for family facts.\"\n    *   Constraints:\n        *   Preserve intent (ignoring irrelevant info).\n        *   Preserve uncertainty/confidence (none explicitly here, but the instruction is clear).\n        *   Do NOT answer the question (there is no question, just a directive).\n        *   Do NOT invent facts.\n        *   Do NOT call tools.\n        *   Output format: JSON with keys `processed_utterance` and `candidate_facts`.\n        *   `candidate_facts`: Array of grounded Prolog facts to assert when high confidence (Do not include uncertain facts).\n        *   Style: One to three sentences, plain text only for `processed_utterance`, no markdown in the value.\n        *   SKILL Guidance: Rewrite rules emphasize keeping intent explicit, applying directive transformations, and keeping output concise.\n\n2.  **Analyze the Input Utterance:**\n    *   Content: A list of irrelevant context items (maintenance bay, weather, inventory, coffee spill, docking logs).\n    *   Directive: \"Ignore this for family facts.\"\n    *   Intent: The user is explicitly filtering out noise/context that does not pertain to the established family ledger. They want the system to focus solely on family relationships.\n\n3.  **Apply SKILL Guidance:**\n    *   *Goal:* Transform raw utterance into a cleaner continuation utterance for downstream reasoning.\n    *   *Rewrite Rules:*\n        1.  Keep first-person ambiguity explicit (N/A, this is a directive).\n        2.  Keep temporal qualifiers explicit (N/A).\n        3.  Keep tentative language tentative (N/A).\n        4.  Keep corrections as corrections (This acts like a constraint/correction to the context window).\n        5.  Apply directive transformations (The input is already a directive, just needs cleaning/explicitation).\n        6.  Keep output concise and directly usable as next-turn input.\n    *   *Non-Negotiables:* Preserve intent (ignore non-family info), Do not answer the task (don't actually ignore it in the output text, just describe the instruction), Do not invent facts.\n\n4.  **Drafting `processed_utterance`:**\n    *   Original: \"Irrelevant sidebar: maintenance bay humming, weather chatter, inventory note, coffee spill report, and unrelated docking logs. Ignore this for family facts.\"\n    *   Goal: Make it explicit that these are distractions to be excluded from the knowledge base regarding family relationships.\n    *   Draft 1: Speaker lists various environmental and operational details as irrelevant context; speaker explicitly instructs to exclude these items when processing family facts.\n    *   Draft 2 (Closer to examples): Speaker identifies maintenance bay, weather, inventory, coffee spill, and docking logs as irrelevant sidebar information; speaker directs to ignore these elements for the purpose of establishing family facts.\n    *   Refining for conciseness and style (Plain text, no markdown): Speaker lists maintenance bay, weather, inventory, coffee spill, and docking logs as irrelevant context; speaker explicitly instructs to exclude these items when processing family facts.\n\n5.  **Drafting `candidate_facts`:**\n    *   Constraint: \"Do not include uncertain facts.\"\n    *   Constraint: \"Array of grounded Prolog facts to assert when high confidence.\"\n    *   Analysis: The input is a meta-instruction about what *not* to store, not a fact about the world itself. There are no new family facts asserted here. It's a constraint on the knowledge base.\n    *   Decision: Since there are no new grounded Prolog facts (like `parent(X, Y)`) being asserted with high confidence in this specific utterance (it's just noise filtering), the array should be empty or contain nothing. The instruction says \"Do not include uncertain facts.\" This isn't a fact about the world, it's a processing rule. However, sometimes constraints can be treated as facts if they define the scope. But looking at previous examples in context:\n        *   Example 1 (Seed): No candidate_facts shown in prompt description, but usually seed facts are asserted later.\n        *   Example 2 (Query): No candidate_facts.\n        *   Example 3 (Correction): No candidate_facts.\n        *   Example 4 (Query): No candidate_facts.\n        *   Example 5 (Tentative): \"Tentative candidate fact: speaker suggests...\" -> This goes into `processed_utterance`. The `candidate_facts` key is for Prolog facts to assert.\n    *   Since the input says \"Ignore this\", asserting a fact like `ignore(maintenance_bay)` might be valid, but usually, we don't assert negative constraints as Prolog facts unless specified. The prompt asks for \"grounded Prolog facts to assert when high confidence\". There are no positive family facts here.\n    *   Safest bet: Empty array `[]`.\n\n6.  **Final Review against Constraints:**\n    *   JSON only? Yes.\n    *   Keys: `processed_utterance`, `candidate_facts`? Yes.\n    *   No markdown in values? Yes.\n    *   Preserve intent? Yes (ignoring non-family info).\n    *   Do not answer the question? There is no question, but I am not executing the ignore command, just rewriting it.\n    *   Style: One to three sentences for `processed_utterance`.\n\n7.  **Final Polish:**\n    *   `processed_utterance`: Speaker identifies maintenance bay, weather, inventory, coffee spill, and docking logs as irrelevant sidebar information; speaker explicitly instructs to exclude these items when processing family facts.\n    *   `candidate_facts`: []\n\n8.  **Wait, check SKILL guidance on \"Directive transformations\":**\n    *   Example: \"Translate this into French...\" -> Output includes translation.\n    *   Here the directive is \"Ignore this\". I should reflect that instruction clearly in the processed utterance.\n    *   My draft looks good.\n\n9.  **Check `candidate_facts` requirement again:**\n    *   \"Do not include uncertain facts.\"\n    *   \"Array of grounded Prolog facts to assert when high confidence.\"\n    *   Since this is a meta-instruction about filtering, there are no new world facts to assert. Empty list is correct.\n\n10. **Construct JSON.**\n\n```json\n{\n  \"processed_utterance\": \"Speaker identifies maintenance bay, weather, inventory, coffee spill, and docking logs as irrelevant sidebar information; speaker explicitly instructs to exclude these items when processing family facts.\",\n  \"candidate_facts\": []\n}\n```\n\nWait, looking at the previous context examples (1-6), they show `processed` text. The prompt asks me to return JSON with specific keys. I must follow the output format instruction strictly (\"Return JSON only with keys...\").\n\nOne more check on `processed_utterance` style: \"Plain text only. No markdown.\"\nMy draft is plain text.\n\nOne more check on intent: \"Ignore this for family facts.\"\nMy rewrite: \"...speaker explicitly instructs to exclude these items when processing family facts.\"\nThis preserves the intent perfectly.\n\nFinal check on `candidate_facts`: The prompt says \"Do not include uncertain facts.\" It doesn't say \"Must include facts if possible\". If there are none, empty is fine.\n\nLet's finalize.\n\n```json\n{\n  \"processed_utterance\": \"Speaker identifies maintenance bay, weather, inventory, coffee spill, and docking logs as irrelevant sidebar information; speaker explicitly instructs to exclude these items when processing family facts.\",\n  \"candidate_facts\": []\n}\n```\nWait, I need to make sure I don't use markdown code blocks for the JSON itself if the instruction says \"Return JSON only\". Usually, this means raw JSON text. However, often in these interfaces, wrapping in ```json is acceptable or expected for clarity, but strict \"JSON only\" usually implies no markdown fences. The instruction says \"Return JSON only with keys...\". I will output raw JSON to be safe, or standard block if the system expects it. Looking at the prompt \"Return JSON only\", I should avoid markdown fences to be strictly compliant.\n\nActually, looking at the examples in the prompt description (Input/Output), they are text blocks. But the instruction for *me* says \"Return J
... [truncated]

{
  "status": "success",
  "result_type": "pre_think",
  "input_utterance": "Irrelevant sidebar: maintenance bay humming, weather chatter, inventory note, coffee spill report, and unrelated docking logs. Ignore this for family facts.",
  "processed_utterance": "Speaker lists maintenance bay, weather, inventory, coffee spill, and docking logs as irrelevant sidebar information; speaker explicitly instructs to exclude these items when processing family facts.",
  "fallback_used": false,
  "normalization_reason": "model_output",
  "history_turns": 6,
  "narrative_context": "",
  "handoff_mode": "rewrite",
  "kb_ingest_mode": "facts",
  "max_candidate_facts": 24,
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  "prethinker_model": "qwen/qwen3.5-9b",
  "pre_think_skill_path": "skills/pre-think/SKILL.md",
  "prethinker_base_url": "http://127.0.0.1:1234",
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  "assistant_message": "{\n  \"processed_utterance\": \"Speaker lists maintenance bay, weather, inventory, coffee spill, and docking logs as irrelevant sidebar information; speaker explicitly instructs to exclude these items when processing family facts.\",\n  \"candidate_facts\": []\n}",
  "raw_response": {
    "model_instance_id": "qwen/qwen3.5-9b:2",
    "output": [
      {
        "type": "reasoning",
        "content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Role: Pre-think utterance processor.\n    *   Task: Rewrite the input utterance into a cleaner, more explicit continuation utterance based on SKILL guidance.\n    *   Input Utterance: \"Irrelevant sidebar: maintenance bay humming, weather chatter, inventory note, coffee spill report, and unrelated docking logs. Ignore this for family facts.\"\n    *   Constraints:\n        *   Preserve intent, uncertainty, constraints, corrections.\n        *   Do NOT answer the question.\n        *   Do NOT invent facts.\n        *   Do NOT call tools.\n        *   Return JSON with keys: `processed_utterance`, `candidate_facts`.\n        *   `candidate_facts`: Array of grounded Prolog facts (only high confidence, no uncertain facts).\n        *   Style: One to three sentences, plain text only, no markdown in the processed utterance.\n    *   SKILL Guidance: Pre-Think Skill (rewrite rules, examples provided).\n    *   Context: Recent pre-think context shows similar handling of \"Irrelevant sidebar\" inputs (Example 6 in recent context matches this input almost exactly).\n\n2.  **Analyze the Input Utterance:**\n    *   Content: Lists various unrelated items (maintenance bay, weather, inventory, coffee spill, docking logs).\n    *   Directive: \"Ignore this for family facts.\"\n    *   Intent: Explicitly filtering out noise/irrelevant information to focus on family facts.\n    *   Constraints: Do not process these items as family facts.\n\n3.  **Apply SKILL Guidance:**\n    *   Goal: Transform raw utterance into cleaner continuation.\n    *   Rewrite Rules:\n        *   Keep constraints explicit.\n        *   Apply directive transformations (none needed here, it's a constraint).\n        *   Keep output concise.\n        *   Style: One to three sentences, plain text only.\n    *   Recent Context Check: Example 6 in the provided context is identical to this input. The processed output for that was: \"Speaker lists maintenance bay, weather, inventory, coffee spill, and docking logs as irrelevant sidebar information; speaker explicitly instructs to exclude these items when processing family facts.\"\n    *   Candidate Facts: Since the instruction is to *ignore* these items for family facts, there are no new grounded Prolog facts to assert about family relationships. The input is a constraint/filtering instruction, not a fact assertion. Therefore, `candidate_facts` should be empty or contain nothing relevant to family facts (the prompt says \"Do not include uncertain facts\" and implies only high confidence grounded facts). Since the user says \"Ignore this for family facts\", asserting these as facts would violate the intent. So `candidate_facts` should likely be an empty array `[]`.\n\n4.  **Drafting the Output:**\n    *   `processed_utterance`: Needs to reflect the filtering instruction clearly. Based on Example 6 in context: \"Speaker lists maintenance bay, weather, inventory, coffee spill, and docking logs as irrelevant sidebar information; speaker explicitly instructs to exclude these items when processing family facts.\" This matches the style and intent perfectly.\n    *   `candidate_facts`: The input is a negative constraint (\"Ignore this\"). There are no positive assertions about family relationships here. So, no candidate facts to assert.\n\n5.  **Refining JSON:**\n    *   Ensure valid JSON.\n    *   Ensure `processed_utterance` has no markdown (no backticks).\n    *   Ensure `candidate_facts` is an array.\n\n6.  **Final Review against Constraints:**\n    *   Preserve intent? Yes (filtering noise).\n    *   Preserve constraints? Yes (ignore for family facts).\n    *   Do not answer? Yes.\n    *   Do not invent facts? Yes.\n    *   JSON only? Yes.\n    *   Keys correct? Yes.\n\n7.  **Constructing the JSON:**\n    ```json\n    {\n      \"processed_utterance\": \"Speaker lists maintenance bay, weather, inventory, coffee spill, and docking logs as irrelevant sidebar information; speaker explicitly instructs to exclude these items when processing family facts.\",\n      \"candidate_facts\": []\n    }\n    ```\n\n    Wait, looking at Example 6 in the context provided:\n    Input: `Irrelevant sidebar: maintenance bay humming, weather chatter, inventory note, coffee spill report, and unrelated docking logs. Ignore this for family facts.`\n    Processed: `Speaker lists maintenance bay, weather, inventory, coffee spill, and docking logs as irrelevant sidebar information; speaker explicitly instructs to exclude these items when processing family facts.`\n\n    The current input is identical to Example 6. I should follow the pattern established in the context to maintain consistency, while adhering to the SKILL guidance rules (which Example 6 already demonstrates).\n\n    One detail: The prompt says \"Return JSON only\".\n    Another detail: `candidate_facts` should be grounded Prolog facts. Since this is a constraint to ignore data, there are no facts to assert. Empty array is correct.\n\n    Let's double check the \"Style\" rule in SKILL: \"One to three sentences. Plain text only. No markdown.\"\n    The drafted processed_utterance fits this.\n\n    Final check on JSON structure.\n    Keys: `processed_utterance`, `candidate_facts`.\n\n    Ready.cw\n"
      },
      {
        "type": "message",
        "content": "\n\n{\n  \"processed_utterance\": \"Speaker lists maintenance bay, weather, inventory, coffee spill, and docking logs as irrelevant sidebar information; speaker explicitly instructs to exclude these items when processing family facts.\",\n  \"candidate_facts\": []\n}"
      }
    ],
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      "reasoning_output_tokens": 1167,
      "tokens_per_second": 136.60486534479773,
      "time_to_first_token_seconds": 0.147
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    "response_id": "resp_ab650770f2646e50c2be2c2134c5f359d0679c625b430c75"
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  "note": "This tool preprocesses a raw utterance for downstream model reasoning. KB mutation occurs only when kb_ingest_mode=`facts` and candidate_facts are provided."
}

{
  "status": "success",
  "result_type": "pre_think",
  "input_utterance": "Irrelevant sidebar: maintenance bay humming, weather chatter, inventory note, coffee spill report, and unrelated docking logs. Ignore this for family facts.",
  "processed_utterance": "Irrelevant sidebar: maintenance bay humming, weather chatter, inventory note, coffee spill report, and unrelated docking logs. Ignore this for family facts.",
  "fallback_used": true,
  "normalization_reason": "empty_model_output",
  "history_turns": 6,
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  "handoff_mode": "rewrite",
  "kb_ingest_mode": "facts",
  "max_candidate_facts": 24,
  "candidate_facts": [],
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  "attempted_candidate_facts": 0,
  "ingested_facts_count": 0,
  "rejected_candidate_facts_count": 0,
  "ingested_facts": [],
  "rejected_candidate_facts": [],
  "prethinker_model": "qwen/qwen3.5-9b",
  "pre_think_skill_path": "skills/pre-think/SKILL.md",
  "prethinker_base_url": "http://127.0.0.1:1234",
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    "output": [
      {
        "type": "reasoning",
        "content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Role: Pre-think utterance processor.\n    *   Task: Rewrite the input utterance into a cleaner, more explicit continuation utterance based on SKILL guidance.\n    *   Input Utterance: \"Irrelevant sidebar: maintenance bay humming, weather chatter, inventory note, coffee spill report, and unrelated docking logs. Ignore this for family facts.\"\n    *   Constraints:\n        *   Preserve intent, uncertainty, constraints, corrections.\n        *   Do NOT answer the question.\n        *   Do NOT invent facts.\n        *   Do NOT call tools.\n        *   Return JSON with keys: `processed_utterance`, `candidate_facts`.\n        *   `candidate_facts`: Array of grounded Prolog facts (only high confidence, no uncertain facts).\n        *   Style: One to three sentences, plain text only, no markdown for the processed utterance.\n    *   SKILL Guidance: Pre-Think Skill (Transform raw utterance into cleaner continuation, preserve intent/uncertainty/constraints, apply directive transformations if any).\n    *   Context: Recent pre-think context shows similar inputs were processed by explicitly stating what the speaker is listing as irrelevant and instructing to exclude them for specific fact processing (family facts).\n\n2.  **Analyze the Input Utterance:**\n    *   Content: The user lists various unrelated items (maintenance bay, weather, inventory, coffee spill, docking logs) as \"Irrelevant sidebar\".\n    *   Directive: \"Ignore this for family facts.\"\n    *   Intent: To filter out noise and ensure only family-related information is processed/stored.\n    *   Confidence: High (explicit instruction).\n    *   Facts to assert: None directly, it's a constraint/filtering instruction.\n\n3.  **Check Recent Context:**\n    *   Item 5 and 6 in the recent pre-think context are identical to the current input.\n    *   Previous processed output for this exact input (Item 5 & 6): \"Speaker lists maintenance bay, weather, inventory, coffee spill, and docking logs as irrelevant sidebar information; speaker explicitly instructs to exclude these items when processing family facts.\"\n    *   I need to follow the pattern established in the context while adhering to the SKILL guidance. The goal is consistency but also ensuring it meets the \"cleaner, more explicit continuation\" requirement. Since this input appeared twice in the context with the same output, I should maintain consistency unless there's a reason to change (e.g., if the model is supposed to evolve). However, as a pre-think processor, I should align with the established pattern for this specific utterance type to ensure stability, while ensuring it meets the JSON format requirements.\n    *   Wait, looking closely at Item 5 and 6 in the context provided:\n        *   Input: `Irrelevant sidebar: maintenance bay humming, weather chatter, inventory note, coffee spill report, and unrelated docking logs. Ignore this for family facts.`\n        *   Processed (Item 5): `Speaker lists maintenance bay, weather, inventory, coffee spill, and docking logs as irrelevant sidebar information; speaker explicitly instructs to exclude these items when processing family facts.`\n        *   Processed (Item 6): Same as Item 5.\n    *   The current input is identical to Item 5/6. I should produce a similar processed utterance that reflects the intent clearly.\n\n4.  **Drafting `processed_utterance`:**\n    *   Must be plain text, no markdown.\n    *   Must be 1-3 sentences.\n    *   Must preserve intent (filtering irrelevant info for family facts).\n    *   Draft: Speaker identifies maintenance bay humming, weather chatter, inventory note, coffee spill report, and unrelated docking logs as irrelevant sidebar information; speaker explicitly instructs to exclude these items when processing family facts.\n    *   Refinement based on SKILL \"Keep output concise and directly usable as next-turn input\": The previous context examples are good references. I will use a formulation similar to the context but ensure it fits the JSON value requirement (plain text).\n\n5.  **Drafting `candidate_facts`:**\n    *   Constraint: \"Do not include uncertain facts.\"\n    *   Constraint: \"Only high confidence grounded Prolog facts.\"\n    *   The input is a directive to ignore information, not an assertion of fact about the world (like \"Liam is Ava's parent\"). It sets a constraint on processing.\n    *   Therefore, there are no new grounded Prolog facts to assert based *solely* on this utterance regarding the family tree itself. It's a meta-instruction.\n    *   Result: Empty array `[]`.\n\n6.  **Final Review against Constraints:**\n    *   JSON only? Yes.\n    *   Keys: `processed_utterance`, `candidate_facts`? Yes.\n    *   No markdown in processed_utterance? Yes.\n    *   Preserve intent/constraints? Yes (filtering for family facts).\n    *   Do not answer? Yes.\n    *   Do not invent facts? Yes.\n\n7.  **Constructing JSON:**\n    *   `processed_utterance`: \"Speaker identifies maintenance bay humming, weather chatter, inventory note, coffee spill report, and unrelated docking logs as irrelevant sidebar information; speaker explicitly instructs to exclude these items when processing family facts.\"\n    *   `candidate_facts`: []\n\n8.  **Wait, one check on Context Consistency:**\n    *   The prompt provides \"Recent pre-think context\". Items 5 and 6 are duplicates of the current input with the same processed output.\n    *   To ensure consistency in the session, I should match that style closely.\n    *   The previous output was: `Speaker lists maintenance bay, weather, inventory, coffee spill, and docking logs as irrelevant sidebar information; speaker explicitly instructs to exclude these items when processing family facts.`\n    *   My draft is very similar. I will use the established phrasing for consistency.\n\n9.  **Final Polish:**\n    *   Ensure no markdown in the JSON string values (except standard JSON escaping if needed, but plain text means no bolding/italics).\n    *   Ensure `candidate_facts` is an empty list since this is a constraint instruction, not a fact assertion.\n\n    *Self-Correction on `candidate_facts`:* The SKILL says \"Do not include uncertain facts.\" It doesn't explicitly say \"If no facts, return empty\". But logically, if there are no high-confidence facts to assert, the array should be empty. This utterance is purely a constraint/filtering instruction (\"Ignore this for family facts\"). Asserting that \"maintenance bay humming is irrelevant\" as a Prolog fact might be technically true in the context of the conversation state, but usually, these filters are meta-instructions. Given the previous examples in the context (Item 5 & 6), they did not generate candidate facts for this input type either (implied by the lack of output in the provided snippet, though I only see `processed`). Wait, looking at Item 1-4, some had corrections or queries. Item 5/6 are constraints. Usually, constraints don't generate Prolog facts about the world state unless they imply a fact like \"X is not Y\". Here it says \"Ignore this for family facts\". It doesn't assert a relationship. So empty array is correct.\n\n    *Wait, checking the SKILL guidance again:* \"candidate_facts: array of grounded Prolog facts to assert when high confidence\".\n    Since the input is explicitly telling the system what *not* to process as fact, asserting it as a fact might be redundant or meta. I will stick with an empty array as there are no new world facts being added, only processing rules.\n\n    *Wait, checking the context examples again:*\n    Input 1: Correction -> Output processed text. No candidate_facts shown in the snippet provided for Item 1-6 (the prompt cuts off the JSON structure for the context items, it just shows `input` and `processed`).\n    Ah, I see the context format is just `input: ... processed: ...`. It doesn't show `candidate_facts` for the context examples.\n    However, the current task requires me to output JSON with `candidate_facts`.\n    Given the instruction \"Do not include uncertain facts\" and \"Only high confidence grounded Prolog facts\", and the input is a directive to ignore noise, there are no new facts about the family tree to assert.\n\n    Let's finalize the text.\n\n    `processed_utterance`: Speaker lists maintenance bay humming, weather chatter, inventory note, coffee spill report, and unrelated docking logs as irrelevant sidebar information; speaker explicitly instructs to exclude these items when processing family facts.\n    `candidate_facts`: []\n\n    Wait, I need to make sure I don't use markdown in the JSON value for `processed_utterance`. The instruction says \"Plain text only. No markdown.\" inside the style sect
... [truncated]

{
  "status": "success",
  "result_type": "pre_think",
  "input_utterance": "Theo is parent of Quinn. Quinn is parent of Rhea.",
  "processed_utterance": "Theo is parent of Quinn. Quinn is parent of Rhea.",
  "fallback_used": true,
  "normalization_reason": "empty_model_output",
  "history_turns": 6,
  "narrative_context": "",
  "handoff_mode": "rewrite",
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  "max_candidate_facts": 24,
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  "prethinker_model": "qwen/qwen3.5-9b",
  "pre_think_skill_path": "skills/pre-think/SKILL.md",
  "prethinker_base_url": "http://127.0.0.1:1234",
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      {
        "type": "reasoning",
        "content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Role: Pre-think utterance processor.\n    *   Task: Rewrite the input utterance into a cleaner, more explicit continuation utterance for downstream reasoning.\n    *   Constraints: Keep original intent, uncertainty, constraints. Do NOT answer, invent facts, or call tools. Return JSON with `processed_utterance` and `candidate_facts`.\n    *   SKILL Guidance (Pre-Think): Preserve intent, uncertainty, corrections, constraints. Apply directive transformations if any. Keep output concise (1-3 sentences). Plain text only for the processed utterance.\n    *   Input Utterance: \"Theo is parent of Quinn. Quinn is parent of Rhea.\"\n    *   Context: Recent pre-think context shows a pattern of processing family relationship queries and corrections. There's a specific instruction in recent context (items 4, 5, 6) to ignore irrelevant sidebar info for family facts, but the current input doesn't contain sidebar info. It contains direct statements about parentage.\n    *   Narrative Context: None.\n\n2.  **Analyze the Input Utterance:**\n    *   Content: Two declarative statements establishing parent-child relationships.\n    *   Entities: Theo, Quinn, Rhea.\n    *   Relationships: Parent(Quinn, Theo) [Wait, \"Theo is parent of Quinn\" means Parent(Theo, Quinn)], Parent(Rhea, Quinn).\n    *   Tone: Declarative, factual (no explicit uncertainty markers like \"maybe\", but in the context of pre-think processing for a reasoning model, these are assertions that need to be evaluated as facts).\n    *   Intent: Asserting family lineage/relationships.\n\n3.  **Apply SKILL Guidance:**\n    *   Preserve intent: The user is stating facts about parentage.\n    *   Preserve uncertainty: There is no explicit uncertainty (\"maybe\", \"I think\"), but the pre-think stage often treats assertions as candidate facts unless confirmed by other context. However, looking at Example 1 in SKILL guidance: `Maybe my mother was Ann.` -> `Tentative candidate fact...`. Example 2: `Actually not Bob...` -> `Correction candidate...`.\n    *   The current input is a direct assertion without hedging. In the absence of uncertainty markers, it should be treated as a factual claim to be processed. However, the SKILL guidance says \"Do NOT answer the question.\" and \"candidate_facts: array of grounded Prolog facts to assert when high confidence\".\n    *   Since there is no explicit uncertainty (\"maybe\", \"tentative\"), but this is a pre-think stage for reasoning, I should reflect that these are assertions being made. The recent context shows processed utterances often rephrase the input slightly to clarify intent (e.g., \"Speaker queries...\", \"Speaker lists...\").\n    *   Wait, looking at Example 3 in SKILL guidance: `Translate this into French...` -> `Traduis en francais...`. This is a directive transformation.\n    *   Looking at recent context examples (1-6): They rephrase the input to describe what the speaker is doing (e.g., \"Speaker queries...\", \"Speaker lists...\").\n    *   Input: \"Theo is parent of Quinn. Quinn is parent of Rhea.\"\n    *   This looks like a statement of fact. I need to rewrite it as a processed utterance describing the assertion.\n    *   Constraint Check: \"Do NOT answer the question.\" (There is no question, just statements). \"Do NOT invent facts.\" (I must not add info not in input). \"candidate_facts\": array of grounded Prolog facts to assert when high confidence. Since the user states this as fact without hedging, I can extract these as candidate facts if confidence is high based on the explicit statement. However, the instruction says \"Do not include uncertain facts.\" These are stated as certain.\n    *   Wait, looking at Example 1: `Maybe my mother was Ann.` -> Output includes `Tentative candidate fact...`.\n    *   Looking at recent context item 2: `Tentative note only: maybe Olivia is Piper's parent...` -> Output: `Tentative candidate fact...`.\n    *   The current input does *not* have \"maybe\". It states \"Theo is parent of Quinn.\" This implies high confidence in the user's statement.\n    *   However, I must not answer the question (there isn't one). I must rewrite the utterance into a cleaner continuation.\n    *   Recent context style: \"Speaker [action]...; speaker explicitly instructs...\" or \"Speaker queries...\".\n    *   For this input, it's an assertion. So: \"Speaker asserts parent-child relationships between Theo and Quinn, and Quinn and Rhea.\"\n    *   Candidate facts: Since the user states them as facts without uncertainty, I can list them as grounded Prolog facts.\n    *   Format: JSON with `processed_utterance` (plain text) and `candidate_facts` (array).\n\n4.  **Drafting the Output:**\n    *   `processed_utterance`: Speaker asserts that Theo is the parent of Quinn and that Quinn is the parent of Rhea; these statements establish a lineage chain without explicit uncertainty markers.\n    *   `candidate_facts`: `[parent(theo, quinn), parent(quinn, rhea)]` (Need to check Prolog syntax style from context? Context doesn't show specific Prolog syntax, but standard is `predicate(arg1, arg2)`). The prompt asks for \"grounded Prolog facts\". I will use standard predicate notation.\n    *   Wait, looking at the SKILL guidance examples again. They don't show JSON output in the examples, they show Input/Output text pairs. But the system instruction says \"Return JSON only with keys: processed_utterance... candidate_facts\".\n    *   I need to make sure `candidate_facts` are grounded. Since the user said it explicitly, I can treat them as high confidence facts for the purpose of this stage (pre-think prepares for reasoning).\n    *   Wait, one constraint: \"Do NOT answer the question.\" This input isn't a question. It's a statement. So I just process the statement.\n    *   Another constraint: \"Keep first-person ambiguity explicit.\" There is no first person here.\n    *   \"Keep temporal qualifiers explicit.\" None.\n    *   \"Keep tentative language tentative.\" None.\n    *   So I should reflect the declarative nature.\n\n    *   Refined `processed_utterance`: Speaker asserts two parent-child relationships: Theo is the parent of Quinn, and Quinn is the parent of Rhea; these are presented as confirmed facts without hedging.\n    *   Refined `candidate_facts`: `[parent(theo, quinn), parent(quinn, rhea)]`\n\n    *   Wait, I need to check if I should output Prolog syntax or just text description for facts. \"array of grounded Prolog facts\". Usually means `fact(arg1, arg2)`.\n    *   Let's check the recent context again. It doesn't show JSON output, it shows processed text. But the system instruction overrides with \"Return JSON only\".\n    *   Okay, I will follow the system instruction for JSON format.\n\n    *   Wait, looking at Example 1 in SKILL: `Maybe my mother was Ann.` -> `Tentative candidate fact: speaker says their mother may have been Ann...`\n    *   This example output is text, not JSON. But the System Instruction says \"Return JSON only\". I must follow the System Instruction for the final output format. The SKILL guidance examples describe the *style* of the processed utterance content.\n    *   So `processed_utterance` should be the rewritten text (1-3 sentences, plain text).\n    *   `candidate_facts` should be the Prolog facts.\n\n    *   Wait, is there any uncertainty? \"Theo is parent of Quinn.\" It's a direct statement. In pre-think for reasoning models, usually, we treat user assertions as potential facts to be verified or stored. Since there's no \"maybe\", I can include them in candidate_facts with high confidence assumption based on the text.\n    *   However, strict adherence to \"Do not invent facts\" means I shouldn't add info. But extracting what is said into a fact representation is processing, not inventing.\n    *   Let's ensure the `processed_utterance` captures the intent accurately.\n\n    *   Draft:\n        processed_utterance: Speaker asserts that Theo is the parent of Quinn and that Quinn is the parent of Rhea; these statements establish a lineage chain without explicit uncertainty markers.\n        candidate_facts: [\"parent(theo, quinn)\", \"parent(quinn, rhea)\"]\n\n    *   Wait, checking constraints again: \"Keep output concise and directly usable as next-turn input.\"\n    *   Also \"Do NOT answer the question.\" (N/A).\n    *   Also \"Do not include uncertain facts.\" (These are stated as certain).\n\n    *   One more check on recent context style.\n        Input: `After the correction, who are Ava's parents?` -> Output: `Speaker queries Ava's current parents following the correction...`\n        Input: `Tentative note only: maybe Olivia is Piper's parent...` -> Output: `Tentative candidate fact: speaker suggests Olivia may be Piper's parent...`\n        Input: `Using confirmed facts only, who is Piper's parent?` -> Output: `Using confirmed facts only, who is Piper's parent?` (Echoed because it's a constraint/query).\n
... [truncated]

{
  "status": "success",
  "result_type": "pre_think",
  "input_utterance": "Theo is parent of Quinn. Quinn is parent of Rhea.",
  "processed_utterance": "Theo is parent of Quinn. Quinn is parent of Rhea.",
  "fallback_used": true,
  "normalization_reason": "empty_model_output",
  "history_turns": 6,
  "narrative_context": "",
  "handoff_mode": "rewrite",
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  "max_candidate_facts": 24,
  "candidate_facts": [],
  "requested_candidate_facts": 0,
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  "prethinker_model": "qwen/qwen3.5-9b",
  "pre_think_skill_path": "skills/pre-think/SKILL.md",
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      {
        "type": "reasoning",
        "content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Role: Pre-think utterance processor for a downstream reasoning model.\n    *   Task: Rewrite the input utterance into a cleaner, more explicit continuation utterance based on SKILL guidance.\n    *   Input Utterance: \"Theo is parent of Quinn. Quinn is parent of Rhea.\"\n    *   Constraints:\n        *   Preserve intent, uncertainty, constraints.\n        *   Do NOT answer the question (there is no question here, just statements).\n        *   Do NOT invent facts.\n        *   Do NOT call tools.\n        *   Return JSON only with keys: `processed_utterance`, `candidate_facts`.\n        *   `candidate_facts`: array of grounded Prolog facts to assert when high confidence. Do not include uncertain facts.\n        *   Style: One to three sentences, plain text only (for `processed_utterance`), no markdown in the text part.\n        *   SKILL Guidance: Transform raw utterance into cleaner continuation. Preserve corrections, uncertainty, etc. Apply directive transformations if any.\n\n2.  **Analyze the Input Utterance:**\n    *   Content: \"Theo is parent of Quinn. Quinn is parent of Rhea.\"\n    *   Tone: Declarative, factual. No explicit uncertainty markers (like \"maybe\", \"I think\").\n    *   Context: Previous turns show a pattern of processing family facts vs. irrelevant sidebar info. Turn 6 in recent context was identical input/output (\"Theo is parent of Quinn. Quinn is parent of Rhea.\" -> same). This suggests this is treated as established fact within the session context provided in the prompt's \"Recent pre-think context\".\n    *   Intent: Stating relationships/facts about family tree.\n\n3.  **Apply SKILL Guidance:**\n    *   Goal: Transform into cleaner continuation utterance for downstream reasoning.\n    *   Rewrite Rules:\n        *   Keep first-person ambiguity explicit (none here).\n        *   Keep temporal qualifiers explicit (none here).\n        *   Keep tentative language tentative (none here, looks definitive).\n        *   Keep corrections as corrections (none here).\n        *   Apply directive transformations (none here).\n        *   Keep output concise.\n    *   Candidate Facts: Since the input states these as facts without uncertainty markers (\"Tentative note only\", \"maybe\"), and previous context treated similar inputs as direct facts, I should extract them as high-confidence candidate facts if they align with the established narrative (which seems to be building a family tree). However, the instruction says \"Do not include uncertain facts.\" These look certain.\n    *   Wait, looking at Turn 1 in recent context: \"Tentative note only: maybe Olivia is Piper's parent...\" -> processed as \"Tentative candidate fact...\".\n    *   Looking at Turn 6 in recent context: \"Theo is parent of Quinn. Quinn is parent of Rhea.\" -> processed as \"Theo is parent of Quinn. Quinn is parent of Rhea.\" (No change).\n    *   The current input is identical to Turn 6. I should follow the pattern established in Turn 6 for consistency, but also adhere to the general goal of making it a \"cleaner continuation utterance\".\n    *   Actually, looking closely at Turn 6 in the provided context:\n        Input: `Theo is parent of Quinn. Quinn is parent of Rhea.`\n        Processed: `Theo is parent of Quinn. Quinn is parent of Rhea.`\n    *   However, my task is to process *this* input now. I need to generate JSON with `processed_utterance` and `candidate_facts`.\n    *   The prompt says \"Recent pre-think context (most recent last)\". Turn 6 is the most recent. It shows that for this specific input, the output was just the text itself.\n    *   But I need to follow the general SKILL guidance which asks for a \"cleaner continuation utterance\".\n    *   Also, I need to populate `candidate_facts`. The instruction says: \"Do not include uncertain facts.\" Since these are stated definitively (\"Theo is parent...\", \"Quinn is parent...\"), they qualify as high confidence candidate facts.\n    *   Format for `processed_utterance`: Plain text, 1-3 sentences. Based on Turn 6 example in context, it seems the model just echoed the fact. But the SKILL description says \"Transform a raw utterance into a cleaner continuation utterance\". Turn 6 might be an edge case or specific to that turn's state.\n    *   Let's look at Turn 1: Input had uncertainty (\"maybe\", \"low confidence\"). Output added metadata about the uncertainty (\"Tentative candidate fact...\").\n    *   This input has no uncertainty. So I should treat them as facts.\n    *   Should I add metadata like Turn 1? Turn 1 output format was: `Tentative candidate fact: speaker suggests Olivia may be Piper's parent; speaker explicitly states low confidence and notes the relationship is not confirmed.`\n    *   For definitive facts, Turn 6 output was just the text. But Turn 6 might have been a repetition or specific state.\n    *   Let's aim for clarity. The SKILL says \"Transform... into a cleaner continuation utterance\". Simply echoing might be acceptable if it's already clean, but adding structure helps downstream reasoning.\n    *   However, I must respect the context pattern. Turn 6 is identical input/output. If I deviate too much, it might break consistency with the session history provided in the prompt. But I am an AI processing this specific request now. The \"Recent pre-think context\" is part of the few-shot style or state.\n    *   Actually, looking at Turn 6 again: Input `Theo is parent of Quinn. Quinn is parent of Rhea.` Output `Theo is parent of Quinn. Quinn is parent of Rhea.`\n    *   If I output exactly that for `processed_utterance`, it matches the context.\n    *   For `candidate_facts`: Since these are stated as facts, I should extract them. Prolog format usually looks like `parent(theo, quinn).` or similar. The prompt says \"array of grounded Prolog facts\".\n    *   Wait, Turn 1 output for `processed_utterance` was descriptive text (\"Tentative candidate fact: ...\"). Turn 6 output was raw text.\n    *   Why the difference? Turn 1 had uncertainty. Turn 6 did not.\n    *   So for this input (no uncertainty), I should probably treat it as a direct fact assertion in `candidate_facts` and keep `processed_utterance` clean or descriptive of the facts.\n    *   Let's check the instruction: \"Return JSON only with keys: - processed_utterance: rewritten continuation text - candidate_facts: array of grounded Prolog facts to assert when high confidence\".\n    *   If I follow Turn 6's pattern for `processed_utterance`, it is just the text. But the SKILL says \"Rewrite... into a cleaner, more explicit continuation utterance\".\n    *   Let's try to make it slightly more explicit about the assertion nature without inventing uncertainty.\n    *   Actually, looking at Turn 1: It added metadata (\"Tentative candidate fact: ...\").\n    *   Looking at Turn 6: It didn't add metadata.\n    *   Maybe because Turn 6 was already clean?\n    *   I will follow the Turn 6 pattern for `processed_utterance` to maintain session consistency, as it's identical input. But I must ensure `candidate_facts` are populated correctly based on the \"high confidence\" rule.\n    *   Wait, if I output the same text in `processed_utterance`, is that a rewrite? The SKILL says \"Rewrite\". Turn 6 might be an example of when no rewrite is needed (already clean).\n    *   However, to be safe and adhere to \"cleaner, more explicit\", I can frame it as asserting these facts.\n    *   But Turn 6 is the most recent context. Deviating might be risky. Let's look at the instruction again: \"Recent pre-think context (most recent last)\". This implies I should continue the pattern.\n    *   Pattern for definitive facts (Turn 6): `processed_utterance` = original text. `candidate_facts` = ? Turn 6 didn't show `candidate_facts` in the provided snippet, it just showed input/processed pairs. Wait, the prompt asks me to return JSON with `candidate_facts`. The context examples don't show the JSON structure, they show Input/Processed text lines.\n    *   Ah, the \"Recent pre-think context\" shows the history of the tool calls (Input -> Processed). It does not show the JSON output format for those turns. I need to generate the JSON now based on the current input.\n    *   So I should infer the `candidate_facts` from the content.\n    *   Content: \"Theo is parent of Quinn. Quinn is parent of Rhea.\"\n    *   Facts: `parent(theo, quinn).`, `parent(quinn, rhea).` (Standard Prolog notation).\n    *   `processed_utterance`: Since Turn 6 output was identical to input for this exact text, I should probably keep it similar to maintain consistency, but the SKILL says \"Rewrite\". If I rewrite it to be more explicit about being facts: \"Speaker asserts Theo is parent of Quinn and Quinn is parent of Rhea.\"\n    *   However, Turn 6 suggests that if it's already a fact statement, no transformation is needed.\n    *   Let's check the SKILL description again: \"Transform a raw utt
... [truncated]

{
  "status": "success",
  "result_type": "bulk_fact_assertion",
  "requested_count": 2,
  "asserted_count": 2,
  "failed_count": 0,
  "asserted_facts": [
    "parent(theo, quinn).",
    "parent(quinn, rhea)."
  ],
  "failed_facts": [],
  "message": "Bulk assertion complete."
}

{
  "status": "success",
  "result_type": "pre_think",
  "input_utterance": "Who are Rhea's ancestors?",
  "processed_utterance": "Who are Rhea's ancestors?",
  "fallback_used": true,
  "normalization_reason": "empty_model_output",
  "history_turns": 6,
  "narrative_context": "",
  "handoff_mode": "rewrite",
  "kb_ingest_mode": "facts",
  "max_candidate_facts": 24,
  "candidate_facts": [],
  "requested_candidate_facts": 0,
  "attempted_candidate_facts": 0,
  "ingested_facts_count": 0,
  "rejected_candidate_facts_count": 0,
  "ingested_facts": [],
  "rejected_candidate_facts": [],
  "prethinker_model": "qwen/qwen3.5-9b",
  "pre_think_skill_path": "skills/pre-think/SKILL.md",
  "prethinker_base_url": "http://127.0.0.1:1234",
  "temperature": 0.0,
  "context_length": 4000,
  "assistant_message": "",
  "raw_response": {
    "model_instance_id": "qwen/qwen3.5-9b:2",
    "output": [
      {
        "type": "reasoning",
        "content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Role: Pre-think utterance processor for a downstream reasoning model.\n    *   Task: Rewrite the input utterance into a cleaner, more explicit continuation utterance.\n    *   Constraints: Keep original intent, uncertainty, constraints. Do NOT answer the question. Do NOT invent facts. Do NOT call tools. Return JSON only with keys `processed_utterance` and `candidate_facts`.\n    *   SKILL Guidance (Pre-Think): Transform raw utterance into cleaner continuation. Preserve intent, uncertainty, corrections, constraints. Apply directive transformations if any. Keep output concise (1-3 sentences). Plain text only for the processed utterance part.\n    *   Input Utterance: \"Who are Rhea's ancestors?\"\n    *   Context: Recent pre-think context shows a pattern of processing family facts and ignoring irrelevant sidebar info. There is established narrative context about Theo, Quinn, and Rhea (Theo -> Quinn -> Rhea). However, the instruction says \"Do NOT answer the question\" and \"Do NOT invent facts\". The recent context includes processed utterances that repeat facts (\"Theo is parent of Quinn. Quinn is parent of Rhea.\").\n    *   Goal: Rewrite \"Who are Rhea's ancestors?\" into a cleaner form suitable for downstream reasoning, adhering to SKILL rules (preserve intent, etc.).\n\n2.  **Evaluate Input Utterance:**\n    *   Text: \"Who are Rhea's ancestors?\"\n    *   Intent: Query about lineage/parentage leading back from Rhea.\n    *   Uncertainty: None explicitly stated in this specific utterance, but the downstream model needs to know it's a query based on available facts.\n    *   Constraints: None explicit in this turn, but previous turns established \"Using confirmed facts only\" and ignoring irrelevant sidebar info. I should respect the established context constraints if applicable, but primarily focus on rewriting the current utterance.\n    *   Facts: The recent context (turns 5 & 6) establishes `Theo is parent of Quinn` and `Quinn is parent of Rhea`. However, as a pre-think processor, I must not answer or assert facts unless high confidence grounded facts are identified for the `candidate_facts` array. The instruction says \"Do NOT invent facts\". The context provided in the prompt includes recent pre-think context which *processed* facts. But my task is to rewrite the *current* utterance.\n    *   SKILL Rule: \"Do not answer the question.\" I cannot list Theo and Quinn as ancestors in the `processed_utterance`. I must reflect the query.\n\n3.  **Drafting `processed_utterance`:**\n    *   Needs to be cleaner/explicit.\n    *   Needs to preserve intent (querying lineage).\n    *   Needs to be concise (1-3 sentences).\n    *   Draft 1: Speaker asks for Rhea's ancestors based on available family facts.\n    *   Draft 2: Query seeks identification of all ancestral figures leading back from Rhea within the confirmed family tree.\n    *   Draft 3 (Aligning with recent style): Speaker requests a list of Rhea's ancestors using only confirmed family facts.\n    *   Refining based on SKILL examples: The examples show transforming raw input into a meta-description of the intent or a cleaned version. Example 1: \"Tentative candidate fact: speaker says...\" Example 2: \"Correction candidate: previous entity...\" Example 3: Translation.\n    *   Since this is a direct question without uncertainty markers like \"maybe\", I should treat it as a direct query intent.\n    *   Let's look at the recent context style (Turns 1-6). Turn 5 & 6 just repeated facts. Turn 2 & 3 expanded on sidebar instructions. Turn 1 kept the question.\n    *   To make it \"cleaner, more explicit continuation utterance\":\n    *   \"Speaker queries for the complete list of Rhea's ancestors based on confirmed family lineage.\"\n\n4.  **Drafting `candidate_facts`:**\n    *   Instruction: \"Do not include uncertain facts.\" \"If SKILL guidance includes directive transformations... apply them.\"\n    *   Instruction: \"Return JSON only with keys: processed_utterance, candidate_facts\".\n    *   Constraint: \"Do NOT invent facts.\"\n    *   The prompt provides recent context where facts were asserted (\"Theo is parent of Quinn. Quinn is parent of Rhea.\"). However, as a pre-think processor for the *current* turn, I should not assert new facts unless they are grounded in the input or high-confidence context provided *for this specific task*.\n    *   The instruction says \"candidate_facts: array of grounded Prolog facts to assert when high confidence\".\n    *   Does the current utterance imply facts? No, it asks a question.\n    *   Should I extract facts from the recent context history provided in the prompt? The prompt includes \"Recent pre-think context\". Turn 5 and 6 processed \"Theo is parent of Quinn. Quinn is parent of Rhea.\" as input. This suggests these are established facts in the session memory.\n    *   However, the instruction says \"Do NOT invent facts.\" If I assert `ancestor(rhea, theo)` based on transitive logic, am I inventing? The SKILL says \"candidate_facts: array of grounded Prolog facts to assert when high confidence\". Usually, pre-think extracts explicit info.\n    *   Given the strict instruction \"Do NOT answer the question\", asserting ancestors in `candidate_facts` might border on answering. But `candidate_facts` is for the downstream model to use.\n    *   Safest approach: Since the input is a question and not a statement of fact, there are no new grounded facts to assert from *this* utterance alone. The recent context shows facts were asserted in previous turns (Turn 5/6). I should not hallucinate new relationships not explicitly stated in the current input or high-confidence prior context if I'm being strict about \"Do NOT invent facts\".\n    *   However, looking at Turn 5/6 in the context provided: The input was \"Theo is parent of Quinn. Quinn is parent of Rhea.\" and the processed output repeated them. This implies these are known facts.\n    *   But for *this* specific turn (\"Who are Rhea's ancestors?\"), there is no new fact to assert. I will leave `candidate_facts` empty or omit if not applicable, but the schema requires the key. I will provide an empty array since the input is a query, not a fact assertion.\n    *   Wait, looking at Turn 1: Input \"Using confirmed facts only, who is Piper's parent?\" -> Processed \"Using confirmed facts only, who is Piper's parent?\". No candidate facts added.\n    *   So for a question, `candidate_facts` should likely be empty unless the user states something like \"Rhea's father is Theo\".\n    *   Decision: Empty array for `candidate_facts`.\n\n5.  **Finalizing `processed_utterance`:**\n    *   Must be plain text.\n    *   Must preserve intent (querying ancestors).\n    *   Draft: Speaker requests identification of Rhea's ancestors based on confirmed family lineage facts.\n    *   Check constraints: \"Keep first-person ambiguity explicit\" (N/A), \"Keep temporal qualifiers explicit\" (N/A), \"Keep tentative language tentative\" (N/A - it's a direct question).\n    *   Let's make it slightly more descriptive like the sidebar examples but for a query.\n    *   \"Speaker queries for Rhea's ancestors using only confirmed family facts.\"\n\n6.  **Review against SKILL:**\n    *   Preserve intent: Yes (querying ancestors).\n    *   Do not answer: Yes (not listing Theo/Quinn).\n    *   Do not invent facts: Yes (no new assertions).\n    *   JSON format: Yes.\n    *   Plain text for processed_utterance: Yes.\n\n7.  **Final Polish:**\n    *   Input: \"Who are Rhea's ancestors?\"\n    *   Processed: Speaker queries for the list of Rhea's ancestors based on confirmed family lineage.\n    *   Candidate Facts: [] (Since it's a question, no new facts to assert).\n\n    Wait, I need to check if I should extract the known relationships from context into candidate_facts to help the downstream model? The instruction says \"candidate_facts: array of grounded Prolog facts to assert when high confidence\". If the context establishes Theo->Quinn->Rhea, asserting `ancestor(rhea, theo)` might be valid reasoning. However, the pre-think stage is usually about cleaning the input. Turn 1 shows a question didn't generate candidate facts. I will follow Turn 1's pattern for questions.\n\n    One more check: \"Recent pre-think context... 5. input: Theo is parent of Quinn. Quinn is parent of Rhea. processed: Theo is parent of Quinn. Quinn is parent of Rhea.\"\n    This implies the system knows these facts. But for *this* turn, I am processing a question. I will not add facts to `candidate_facts` unless the input provides them.\n\n    Final check on JSON structure.\n    Keys: `processed_utterance`, `candidate_facts`.\n    Values: String, Array of strings (Prolog facts).\n\n    Let's refine the processed utterance to match the style of Turn 2/3 (explicit description of intent) rather than just repeating Turn 1.\n    Turn 1 Input: \"Using confirmed facts only, who is Piper's parent?\" -> Output: \"Using confirmed facts only, w
... [truncated]

{
  "status": "no_results",
  "result_type": "no_result",
  "predicate": "ancestor",
  "prolog_query": "ancestor(rhea, X).",
  "variables": [
    "X"
  ],
  "rows": [],
  "num_rows": 0,
  "reasoning_basis": {
    "kind": "rule-derived",
    "note": "The `ancestor` predicate is typically computed through rules rather than stored as a single explicit fact."
  }
}

{
  "status": "success",
  "known_entities": [
    "admin",
    "alice",
    "ava",
    "bob",
    "john",
    "liam",
    "nora",
    "owen",
    "piper",
    "quinn",
    "read",
    "rhea",
    "theo",
    "write"
  ],
  "supported_predicates": [
    "parent",
    "sibling",
    "ancestor",
    "child",
    "allergic_to",
    "takes_medication",
    "user",
    "role",
    "permission",
    "access_level",
    "can_access",
    "granted_permission",
    "allowed",
    "patient",
    "renal_risk",
    "candidate_drug",
    "interaction",
    "drug_class",
    "interacts",
    "triage",
    "safe_candidate",
    "task",
    "depends_on",
    "duration_days",
    "task_supplier",
    "supplier_status",
    "completed",
    "milestone",
    "downstream",
    "blocked_task",
    "unmet_prereq",
    "task_status",
    "safe_to_start",
    "waiting_on",
    "impacts_milestone",
    "delayed_milestone",
    "character",
    "location",
    "connected",
    "at",
    "faction",
    "has_item",
    "hp",
    "status",
    "weather",
    "time_of_day",
    "insomnia",
    "charmed",
    "quest_active",
    "asleep",
    "awake",
    "co_located",
    "can_move",
    "exposed",
    "needs_rest",
    "vulnerable",
    "threatened",
    "high_risk",
    "can_trade",
    "can_cast_charm"
  ],
  "predicate_notes": {
    "fact_backed_examples": [
      "parent",
      "role",
      "permission",
      "allergic_to"
    ],
    "typically_rule_derived": [
      "allowed",
      "ancestor",
      "asleep",
      "awake",
      "blocked_task",
      "can_access",
      "can_cast_charm",
      "can_move",
      "can_trade",
      "child",
      "co_located",
      "delayed_milestone",
      "downstream",
      "exposed",
      "high_risk",
      "impacts_milestone",
      "interacts",
      "needs_rest",
      "safe_candidate",
      "safe_to_start",
      "sibling",
      "task_status",
      "threatened",
      "triage",
      "unmet_prereq",
      "vulnerable",
      "waiting_on"
    ]
  },
  "note": "This is a summary view of currently known entities plus the predicate vocabulary the skill knows how to talk about. It is not a full dump of every stored fact, and a supported predicate does not imply facts exist for every entity.",
  "knowledge_base_path": "D:\\_PROJECTS\\prolog-reasoning\\prolog\\core.pl"
}

{
  "status": "no_results",
  "result_type": "no_result",
  "predicate": "ancestor",
  "prolog_query": "ancestor(rhea, X).",
  "variables": [
    "X"
  ],
  "rows": [],
  "num_rows": 0,
  "reasoning_basis": {
    "kind": "rule-derived",
    "note": "The `ancestor` predicate is typically computed through rules rather than stored as a single explicit fact."
  }
}

{
  "status": "success",
  "result_type": "table",
  "predicate": "parent",
  "prolog_query": "parent(X, rhea).",
  "variables": [
    "X"
  ],
  "rows": [
    {
      "X": "quinn"
    }
  ],
  "num_rows": 1,
  "reasoning_basis": {
    "kind": "fact-backed",
    "note": "The `parent` predicate is typically answered from stored facts, though rules may still participate."
  }
}

{
  "status": "success",
  "result_type": "table",
  "predicate": "parent",
  "prolog_query": "parent(X, quinn).",
  "variables": [
    "X"
  ],
  "rows": [
    {
      "X": "theo"
    }
  ],
  "num_rows": 1,
  "reasoning_basis": {
    "kind": "fact-backed",
    "note": "The `parent` predicate is typically answered from stored facts, though rules may still participate."
  }
}

{
  "status": "no_results",
  "result_type": "no_result",
  "predicate": "parent",
  "prolog_query": "parent(X, theo).",
  "variables": [
    "X"
  ],
  "rows": [],
  "num_rows": 0,
  "reasoning_basis": {
    "kind": "fact-backed",
    "note": "The `parent` predicate is typically answered from stored facts, though rules may still participate."
  }
}

{
  "status": "success",
  "result_type": "table",
  "predicate": "parent",
  "prolog_query": "parent(X, ava).",
  "variables": [
    "X"
  ],
  "rows": [
    {
      "X": "nora"
    },
    {
      "X": "theo"
    }
  ],
  "num_rows": 2,
  "reasoning_basis": {
    "kind": "fact-backed",
    "note": "The `parent` predicate is typically answered from stored facts, though rules may still participate."
  }
}

{
  "status": "success",
  "result_type": "table",
  "predicate": "parent",
  "prolog_query": "parent(owen, X).",
  "variables": [
    "X"
  ],
  "rows": [
    {
      "X": "piper"
    }
  ],
  "num_rows": 1,
  "reasoning_basis": {
    "kind": "fact-backed",
    "note": "The `parent` predicate is typically answered from stored facts, though rules may still participate."
  }
}

{
  "status": "no_results",
  "result_type": "no_result",
  "predicate": "parent",
  "prolog_query": "parent(piper, X).",
  "variables": [
    "X"
  ],
  "rows": [],
  "num_rows": 0,
  "reasoning_basis": {
    "kind": "fact-backed",
    "note": "The `parent` predicate is typically answered from stored facts, though rules may still participate."
  }
}

{
  "status": "success",
  "result_type": "table",
  "predicate": "parent",
  "prolog_query": "parent(ava, X).",
  "variables": [
    "X"
  ],
  "rows": [
    {
      "X": "owen"
    }
  ],
  "num_rows": 1,
  "reasoning_basis": {
    "kind": "fact-backed",
    "note": "The `parent` predicate is typically answered from stored facts, though rules may still participate."
  }
}

{
  "status": "success",
  "result_type": "table",
  "predicate": "parent",
  "prolog_query": "parent(nora, X).",
  "variables": [
    "X"
  ],
  "rows": [
    {
      "X": "ava"
    }
  ],
  "num_rows": 1,
  "reasoning_basis": {
    "kind": "fact-backed",
    "note": "The `parent` predicate is typically answered from stored facts, though rules may still participate."
  }
}

{
  "status": "success",
  "result_type": "table",
  "predicate": "parent",
  "prolog_query": "parent(theo, X).",
  "variables": [
    "X"
  ],
  "rows": [
    {
      "X": "ava"
    },
    {
      "X": "quinn"
    }
  ],
  "num_rows": 2,
  "reasoning_basis": {
    "kind": "fact-backed",
    "note": "The `parent` predicate is typically answered from stored facts, though rules may still participate."
  }
}

{
  "status": "success",
  "result_type": "pre_think",
  "input_utterance": "Update: Owen is also parent of Una.",
  "processed_utterance": "Update: Owen is also parent of Una.",
  "fallback_used": true,
  "normalization_reason": "empty_model_output",
  "history_turns": 6,
  "narrative_context": "",
  "handoff_mode": "rewrite",
  "kb_ingest_mode": "facts",
  "max_candidate_facts": 24,
  "candidate_facts": [],
  "requested_candidate_facts": 0,
  "attempted_candidate_facts": 0,
  "ingested_facts_count": 0,
  "rejected_candidate_facts_count": 0,
  "ingested_facts": [],
  "rejected_candidate_facts": [],
  "prethinker_model": "qwen/qwen3.5-9b",
  "pre_think_skill_path": "skills/pre-think/SKILL.md",
  "prethinker_base_url": "http://127.0.0.1:1234",
  "temperature": 0.0,
  "context_length": 4000,
  "assistant_message": "",
  "raw_response": {
    "model_instance_id": "qwen/qwen3.5-9b:2",
    "output": [
      {
        "type": "reasoning",
        "content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Role: Pre-think utterance processor for a downstream reasoning model.\n    *   Task: Rewrite the input utterance into a cleaner, more explicit continuation utterance based on SKILL guidance.\n    *   Input Utterance: \"Update: Owen is also parent of Una.\"\n    *   Constraints:\n        *   Preserve intent, uncertainty, constraints, corrections.\n        *   Do NOT answer the question.\n        *   Do NOT invent facts.\n        *   Do NOT call tools.\n        *   Return JSON only with keys: `processed_utterance`, `candidate_facts`.\n        *   `candidate_facts`: Array of grounded Prolog facts to assert when high confidence. Do not include uncertain facts.\n        *   Style: One to three sentences, plain text only (for `processed_utterance`), no markdown in the text part.\n        *   Context: Previous turns show a pattern of filtering irrelevant info and processing family tree facts (Theo-Quinn-Rhea). The current input adds Owen-Una.\n\n2.  **Analyze the Input Utterance:**\n    *   Content: \"Update: Owen is also parent of Una.\"\n    *   Intent: Adding new information to the knowledge base regarding family relationships.\n    *   Tone: Declarative, authoritative (\"Update\", \"is\"). No uncertainty expressed.\n    *   Constraints: None specific beyond the general context (ignore irrelevant sidebar info from previous turns if present, but this input is clean).\n\n3.  **Apply SKILL Guidance:**\n    *   Goal: Transform raw utterance into cleaner continuation for downstream reasoning.\n    *   Rewrite Rules:\n        *   Keep first-person ambiguity explicit (N/A here).\n        *   Keep temporal qualifiers explicit (None).\n        *   Keep tentative language tentative (None, it's declarative).\n        *   Keep corrections as corrections (It says \"Update\", implying addition/revision to previous state).\n        *   Apply directive transformations (None).\n        *   Keep output concise.\n    *   Candidate Facts: Since the speaker states this as a fact (\"Owen is also parent of Una\") without uncertainty markers like \"maybe\" or \"I think\", and it aligns with the established family tree context (Theo-Quinn-Rhea), this qualifies as a high-confidence grounded fact for the Prolog knowledge base.\n    *   Previous Context: The previous turns established a pattern of asserting facts directly when they are clear statements (e.g., \"Theo is parent of Quinn.\").\n\n4.  **Drafting `processed_utterance`:**\n    *   Needs to be cleaner, explicit continuation.\n    *   Should reflect the update nature.\n    *   Draft: Speaker provides an update adding Owen as a parent of Una to the family facts; this is presented as a definitive addition to the existing lineage data.\n    *   Refining for style (1-3 sentences, plain text): Speaker updates the family tree by stating Owen is also a parent of Una; treat this as a new definitive fact regarding lineage relationships.\n\n5.  **Drafting `candidate_facts`:**\n    *   Must be grounded Prolog facts.\n    *   High confidence only.\n    *   Fact: `parent(owen, una).` or similar representation. The prompt examples don't show the exact Prolog syntax but imply \"grounded Prolog facts\". Looking at previous context (Turn 4 & 5), the input was \"Theo is parent of Quinn.\" and processed as \"Theo is parent of Quinn.\"\n    *   However, the instruction says: \"candidate_facts: array of grounded Prolog facts to assert when high confidence\".\n    *   I need to format this as a list of strings representing facts. Usually, in these contexts, it's natural language assertions or logical predicates. Given the previous context just echoed the input, but the specific instruction here asks for \"grounded Prolog facts\". I will use standard predicate notation `parent(owen, una).`\n    *   Wait, looking at Turn 4/5 processed output: \"Theo is parent of Quinn. Quinn is parent of Rhea.\" It didn't extract a JSON fact list there because the system prompt for *this* specific turn asks for JSON with `candidate_facts`. The previous turns in the context provided are just examples of the conversation history, not necessarily following this exact JSON output format (since they were likely generated by a different stage or the user is showing me the history).\n    *   Actually, looking closely at the prompt structure: \"Recent pre-think context...\". These show `input` and `processed`. They don't show `candidate_facts`. This current turn requires JSON output with `candidate_facts`.\n    *   So I need to extract the fact.\n    *   Fact: `parent(owen, una).`\n\n6.  **Review Constraints:**\n    *   JSON only.\n    *   Keys: `processed_utterance`, `candidate_facts`.\n    *   No markdown in `processed_utterance`.\n    *   Do not answer the question (There is no question to answer, just a statement).\n    *   Do not invent facts (Only assert what was said).\n\n7.  **Final Polish:**\n    *   `processed_utterance`: Speaker updates the family lineage by asserting Owen is also a parent of Una; treat this as a definitive addition to the existing relationship data.\n    *   `candidate_facts`: [\"parent(owen, una).\"]\n\n8.  **Wait, one check on \"candidate_facts\":**\n    *   The instruction says: \"Do not include uncertain facts.\"\n    *   The input is \"Update: Owen is also parent of Una.\" This is a direct assertion.\n    *   So it should be included.\n    *   Format: Array of strings.\n\n9.  **Final JSON Construction:**\n    *   Ensure valid JSON.\n    *   Ensure no markdown code blocks around the JSON (though usually, system instructions imply raw text or specific formatting. The prompt says \"Return JSON only\". I will output raw JSON).\n    *   Wait, the instruction says \"Return JSON only with keys...\". I should not wrap it in ```json ... ```. Just the raw JSON string.\n\n    *   Re-reading \"Style\": \"One to three sentences. Plain text only. No markdown.\" This applies to `processed_utterance`.\n    *   The overall output must be JSON.\n\n    *   Let's check the previous context again. Turn 4 input: \"Theo is parent of Quinn. Quinn is parent of Rhea.\" Processed: \"Theo is parent of Quinn. Quinn is parent of Rhea.\"\n    *   This current turn requires me to follow the specific instruction for *this* pre-think stage which asks for JSON with `candidate_facts`. The previous context turns might have been from a different iteration or just showing conversation flow. I must follow the current system instruction (\"Return JSON only...\").\n\n    *   Refined `processed_utterance`: Speaker updates the family lineage by asserting Owen is also a parent of Una; treat this as a definitive addition to the existing relationship data.\n    *   Refined `candidate_facts`: [\"parent(owen, una).\"]\n\n    *   Wait, looking at Turn 3 in context: \"processed: Irrelevant sidebar...\" (It just repeated input). Turn 4/5 processed input directly.\n    *   The current instruction overrides the previous turn's style if it conflicts with the specific JSON requirement for this stage. The prompt explicitly says \"Return JSON only\".\n\n    *   One more check on `candidate_facts`: \"array of grounded Prolog facts\".\n    *   Is `parent(owen, una).` Prolog? Yes.\n    *   Is it grounded? Yes, from the utterance.\n    *   Is it high confidence? Yes, no uncertainty markers.\n\n    *   Final check on constraints: \"Do NOT answer the question.\" (There is no question). \"Do NOT invent facts.\" (Only Owen/Una). \"Do NOT call tools.\" (Correct).\n\n    *   Wait, I need to make sure I don't output markdown code blocks if \"Return JSON only\" implies raw text. However, usually, LLMs wrap in ```json```. But strict instruction says \"Return JSON only\". I will output raw JSON text to be safe, or standard markdown block if that's the norm for this interface. Given \"Return JSON only\", I will avoid markdown fences to be strictly compliant with \"only\". Actually, looking at typical behavior, raw JSON is safer for parsing. But often users expect ```json```. Let's look at the instruction: \"Return JSON only with keys...\". I will output the raw JSON string.\n\n    *   Wait, one nuance: \"processed_utterance\" style says \"Plain text only. No markdown.\" This refers to the value of the key, not the whole response. The whole response must be JSON.\n    *   Okay, constructing the JSON.\n\n    *   One detail from Turn 1-3 context: There was a lot of \"Irrelevant sidebar\" filtering. This input doesn't have that. It's a direct fact update.\n    *   I should ensure the `processed_utterance` acknowledges the \"Update\" nature as per rule #4 (Keep corrections as corrections) or general intent preservation. \"Update\" implies revision/addition to state.\n\n    *   Draft: Speaker updates the family lineage by asserting Owen is also a parent of Una; treat this as a definitive addition to the existing relationship data.\n    *   Looks good.\n\n    *   Wait, checking Turn 4/5 again. They didn't output JSON. They just output text. But the current prompt instru
... [truncated]

{
  "status": "success",
  "result_type": "pre_think",
  "input_utterance": "Update: Owen is also parent of Una.",
  "processed_utterance": "Update: Owen is also parent of Una.",
  "fallback_used": true,
  "normalization_reason": "empty_model_output",
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  "narrative_context": "",
  "handoff_mode": "rewrite",
  "kb_ingest_mode": "facts",
  "max_candidate_facts": 24,
  "candidate_facts": [],
  "requested_candidate_facts": 0,
  "attempted_candidate_facts": 0,
  "ingested_facts_count": 0,
  "rejected_candidate_facts_count": 0,
  "ingested_facts": [],
  "rejected_candidate_facts": [],
  "prethinker_model": "qwen/qwen3.5-9b",
  "pre_think_skill_path": "skills/pre-think/SKILL.md",
  "prethinker_base_url": "http://127.0.0.1:1234",
  "temperature": 0.0,
  "context_length": 4000,
  "assistant_message": "",
  "raw_response": {
    "model_instance_id": "qwen/qwen3.5-9b:2",
    "output": [
      {
        "type": "reasoning",
        "content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Role: Pre-think utterance processor for a downstream reasoning model.\n    *   Task: Rewrite the input utterance into a cleaner, more explicit continuation utterance based on SKILL guidance.\n    *   Input Utterance: \"Update: Owen is also parent of Una.\"\n    *   Constraints:\n        *   Preserve intent, uncertainty, constraints.\n        *   Do NOT answer the question.\n        *   Do NOT invent facts.\n        *   Do NOT call tools.\n        *   Return JSON only with keys: `processed_utterance`, `candidate_facts`.\n        *   `candidate_facts`: Array of grounded Prolog facts to assert when high confidence. Do not include uncertain facts.\n        *   Style: One to three sentences, plain text only (for `processed_utterance`), no markdown in the text part.\n        *   SKILL Guidance: Transform raw utterance into cleaner continuation. Preserve corrections/updates as revision signals.\n\n2.  **Analyze the Input Utterance:**\n    *   Content: \"Update: Owen is also parent of Una.\"\n    *   Intent: Adding new information to the knowledge base (parent-child relationship).\n    *   Confidence: High (stated as an update/fact, not tentative like \"maybe\").\n    *   Context: Previous turns show similar updates (\"Theo is parent of Quinn...\", \"Update: Owen is also parent of Una.\"). The system seems to be building a family tree.\n    *   Constraint Check: The previous turn (item 6 in context) was identical input/output. I need to follow the pattern but ensure it meets the SKILL guidance for rewriting into a cleaner continuation.\n\n3.  **Apply SKILL Guidance:**\n    *   Goal: Transform raw utterance into cleaner continuation utterance.\n    *   Rewrite Rules:\n        *   Keep first-person ambiguity explicit (N/A here, no \"I\").\n        *   Keep temporal qualifiers explicit (None).\n        *   Keep tentative language tentative (None, this is an update).\n        *   Keep corrections as corrections (This is an update/addition).\n        *   Apply directive transformations (None).\n        *   Keep output concise.\n    *   Example Analysis:\n        *   Input: \"Update: Owen is also parent of Una.\"\n        *   Previous Context Output (Item 6): \"Update: Owen is also parent of Una.\" (This seems to be a copy-paste from the few-shot examples provided in the prompt's context section, but I need to generate the *processed_utterance* based on the SKILL guidance which asks for rewriting into a cleaner continuation).\n        *   Looking at Example 2: \"Actually not Bob, I meant Alice.\" -> Output: \"Correction candidate: previous entity Bob is replaced by Alice; treat this as a revision signal, not a fresh hard fact.\"\n        *   Looking at Example 1: \"Maybe my mother was Ann.\" -> Output: \"Tentative candidate fact: speaker says their mother may have been Ann; speaker identity is unresolved and requires clarification before persistence.\"\n        *   The SKILL guidance says: \"Transform a raw utterance into a cleaner continuation utterance for downstream reasoning.\"\n        *   However, looking at the provided context (items 1-6), items 3, 4, 5, 6 show direct passthrough or minimal processing. Item 1 and 2 show more explicit processing of constraints.\n        *   The instruction says: \"Rewrite the input utterance into a cleaner, more explicit continuation utterance.\"\n        *   It also says: \"Do NOT answer the question. Do NOT invent facts.\"\n        *   For an update like this, I should frame it as a fact assertion signal for the downstream model, similar to how Example 1 frames tentative facts but with high confidence here.\n        *   Wait, looking closely at the provided context examples (items 3-6), they are just echoing the input. But the SKILL guidance says \"Transform... into a cleaner continuation\". The few-shot examples in the *SKILL description* (Examples section) show transformation (e.g., \"Maybe my mother...\" -> \"Tentative candidate fact...\").\n        *   I should follow the *SKILL Guidance Examples* style for transformation, not necessarily the immediate context history which might be stale or specific to a different run. The prompt says \"Pre-think SKILL guidance: ... Examples ...\". I must follow the SKILL guidance examples for the format of `processed_utterance`.\n        *   Actually, looking at the context provided in the prompt (Recent pre-think context), items 3-6 are identical to input. This suggests a pattern where factual updates are passed through cleanly. However, the instruction says \"Rewrite... into a cleaner, more explicit continuation utterance\".\n        *   Let's look at Example 2 in SKILL: \"Actually not Bob...\" -> \"Correction candidate: ... treat this as a revision signal...\".\n        *   This input is an \"Update\". It implies adding to the state.\n        *   I should formulate `processed_utterance` to reflect that this is an update/fact addition signal for the reasoning model, ensuring it's clear it's new information.\n        *   However, looking at the context history (items 3-6), the system seems to accept direct facts. But my task is to act as the pre-think processor *now*. The SKILL guidance says \"Transform a raw utterance into a cleaner continuation utterance\".\n        *   Let's aim for clarity: State that this is an update adding a parent-child relationship.\n        *   `candidate_facts`: Since confidence is high (\"Update\"), I should include the fact in Prolog format if it's grounded. The input says \"Owen is also parent of Una\". This is a direct assertion.\n        *   Constraint: \"Do not include uncertain facts.\" This one seems certain.\n        *   Format for `candidate_facts`: Array of grounded Prolog facts. E.g., `parent(una, owen)` or `parent(o wen, una)`. Usually parent(X, Y) means X is parent of Y. Input: \"Owen is also parent of Una\". So `parent(owen, una)`.\n        *   Wait, the SKILL guidance examples for `processed_utterance` are descriptive text (e.g., \"Tentative candidate fact: ...\"). The context history shows direct passthrough. I need to balance the SKILL instruction (\"Rewrite... into a cleaner continuation\") with the observed behavior in context.\n        *   Actually, the prompt says \"You are a pre-think utterance processor... Rewrite the input utterance into a cleaner, more explicit continuation utterance.\"\n        *   The SKILL Examples show descriptive text for `processed_utterance`.\n        *   Example 1: \"Tentative candidate fact: speaker says their mother may have been Ann...\"\n        *   Example 2: \"Correction candidate: previous entity Bob is replaced by Alice...\"\n        *   So I should write a description of the update, not just repeat it.\n        *   `candidate_facts`: Since this is an explicit update (\"Update:\"), it qualifies as high confidence.\n\n4.  **Drafting `processed_utterance`:**\n    *   Input: \"Update: Owen is also parent of Una.\"\n    *   Draft: Update signal received; speaker asserts Owen is a parent of Una, adding this relationship to the existing family facts.\n    *   Refining for SKILL style (Example 2 style): \"Update candidate: new fact added stating Owen is parent of Una; treat as revision/addition signal.\"\n    *   Let's check the constraint: \"Keep output concise and directly usable as next-turn input.\"\n    *   Draft: Update signal: speaker asserts Owen is parent of Una; this is a high-confidence addition to the family tree.\n\n5.  **Drafting `candidate_facts`:**\n    *   Fact: Owen is parent of Una.\n    *   Prolog format: `parent(owen, una).` or just `parent(owen, una)`. The context examples don't show Prolog output in the history, but the instruction says \"array of grounded Prolog facts\".\n    *   I will use standard predicate notation. `parent(owen, una)`.\n\n6.  **Review against Constraints:**\n    *   JSON only? Yes.\n    *   Keys: `processed_utterance`, `candidate_facts`? Yes.\n    *   No markdown in text? Yes.\n    *   Preserve intent? Yes (Update/Fact).\n    *   Do not answer? Yes.\n    *   Do not invent facts? Yes.\n\n7.  **Final Polish:**\n    *   `processed_utterance`: \"Update signal: speaker asserts Owen is parent of Una; treat as a high-confidence addition to the family tree.\"\n    *   `candidate_facts`: [\"parent(owen, una)\"]\n\n    Wait, looking at the context history (items 3-6), the output was exactly the input. But the instruction says \"Rewrite... into a cleaner, more explicit continuation utterance\". The SKILL Examples show rewriting. I should follow the SKILL Guidance Examples over the few-shot context if they conflict on style, as the prompt explicitly defines the SKILL guidance for *this* task. The context history might be from a previous run or less strict processing. The instruction \"Rewrite the input utterance into a cleaner, more explicit continuation utterance\" is key.\n    However, I must also consider that `candidate_facts` should be grounded Prolog facts.\n    Let's ensure the `processed_utterance` sounds like a con
... [truncated]

{
  "status": "success",
  "result_type": "table",
  "predicate": "ancestor",
  "prolog_query": "ancestor(X, ava).",
  "variables": [
    "X"
  ],
  "rows": [
    {
      "X": "nora"
    },
    {
      "X": "theo"
    }
  ],
  "num_rows": 2,
  "reasoning_basis": {
    "kind": "rule-derived",
    "note": "The `ancestor` predicate is typically computed through rules rather than stored as a single explicit fact."
  }
}

{
  "status": "success",
  "result_type": "table",
  "predicate": "ancestor",
  "prolog_query": "ancestor(ava, X).",
  "variables": [
    "X"
  ],
  "rows": [
    {
      "X": "owen"
    },
    {
      "X": "piper"
    }
  ],
  "num_rows": 2,
  "reasoning_basis": {
    "kind": "rule-derived",
    "note": "The `ancestor` predicate is typically computed through rules rather than stored as a single explicit fact."
  }
}

{
  "status": "success",
  "known_entities": [
    "admin",
    "alice",
    "ava",
    "bob",
    "john",
    "liam",
    "nora",
    "owen",
    "piper",
    "quinn",
    "read",
    "rhea",
    "theo",
    "write"
  ],
  "supported_predicates": [
    "parent",
    "sibling",
    "ancestor",
    "child",
    "allergic_to",
    "takes_medication",
    "user",
    "role",
    "permission",
    "access_level",
    "can_access",
    "granted_permission",
    "allowed",
    "patient",
    "renal_risk",
    "candidate_drug",
    "interaction",
    "drug_class",
    "interacts",
    "triage",
    "safe_candidate",
    "task",
    "depends_on",
    "duration_days",
    "task_supplier",
    "supplier_status",
    "completed",
    "milestone",
    "downstream",
    "blocked_task",
    "unmet_prereq",
    "task_status",
    "safe_to_start",
    "waiting_on",
    "impacts_milestone",
    "delayed_milestone",
    "character",
    "location",
    "connected",
    "at",
    "faction",
    "has_item",
    "hp",
    "status",
    "weather",
    "time_of_day",
    "insomnia",
    "charmed",
    "quest_active",
    "asleep",
    "awake",
    "co_located",
    "can_move",
    "exposed",
    "needs_rest",
    "vulnerable",
    "threatened",
    "high_risk",
    "can_trade",
    "can_cast_charm"
  ],
  "predicate_notes": {
    "fact_backed_examples": [
      "parent",
      "role",
      "permission",
      "allergic_to"
    ],
    "typically_rule_derived": [
      "allowed",
      "ancestor",
      "asleep",
      "awake",
      "blocked_task",
      "can_access",
      "can_cast_charm",
      "can_move",
      "can_trade",
      "child",
      "co_located",
      "delayed_milestone",
      "downstream",
      "exposed",
      "high_risk",
      "impacts_milestone",
      "interacts",
      "needs_rest",
      "safe_candidate",
      "safe_to_start",
      "sibling",
      "task_status",
      "threatened",
      "triage",
      "unmet_prereq",
      "vulnerable",
      "waiting_on"
    ]
  },
  "note": "This is a summary view of currently known entities plus the predicate vocabulary the skill knows how to talk about. It is not a full dump of every stored fact, and a supported predicate does not imply facts exist for every entity.",
  "knowledge_base_path": "D:\\_PROJECTS\\prolog-reasoning\\prolog\\core.pl"
}

{
  "status": "success",
  "result_type": "pre_think",
  "input_utterance": "Are Piper and Una siblings?",
  "processed_utterance": "Querying whether Piper and Una are siblings by verifying shared parental lineage in family records.",
  "fallback_used": false,
  "normalization_reason": "model_output",
  "history_turns": 6,
  "narrative_context": "",
  "handoff_mode": "rewrite",
  "kb_ingest_mode": "facts",
  "max_candidate_facts": 24,
  "candidate_facts": [],
  "requested_candidate_facts": 0,
  "attempted_candidate_facts": 0,
  "ingested_facts_count": 0,
  "rejected_candidate_facts_count": 0,
  "ingested_facts": [],
  "rejected_candidate_facts": [],
  "prethinker_model": "qwen/qwen3.5-9b",
  "pre_think_skill_path": "skills/pre-think/SKILL.md",
  "prethinker_base_url": "http://127.0.0.1:1234",
  "temperature": 0.0,
  "context_length": 4000,
  "assistant_message": "{\n  \"processed_utterance\": \"Querying whether Piper and Una are siblings by verifying shared parental lineage in family records.\",\n  \"candidate_facts\": []\n}",
  "raw_response": {
    "model_instance_id": "qwen/qwen3.5-9b:2",
    "output": [
      {
        "type": "reasoning",
        "content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Role: Pre-think utterance processor for a downstream reasoning model.\n    *   Task: Rewrite the input utterance into a cleaner, more explicit continuation utterance based on SKILL guidance.\n    *   Constraints: Keep original intent, uncertainty, constraints. Do NOT answer the question. Do NOT invent facts. Do NOT call tools. Return JSON only with keys `processed_utterance` and `candidate_facts`.\n    *   SKILL Guidance (Pre-Think): Transform raw utterance into cleaner continuation. Preserve intent, uncertainty, corrections, constraints. Apply directive transformations if any. Keep output concise (1-3 sentences). Plain text only for the processed utterance part.\n    *   Input Utterance: \"Are Piper and Una siblings?\"\n    *   Context: Recent pre-think context shows a family tree being built (Theo -> Quinn -> Rhea, Owen -> Una). The current question asks about the relationship between Piper and Una.\n    *   Output Format: JSON with `processed_utterance` (string) and `candidate_facts` (array of strings representing grounded Prolog facts to assert when high confidence).\n\n2.  **Evaluate Input Utterance:**\n    *   Content: \"Are Piper and Una siblings?\"\n    *   Intent: Querying a relationship between two entities (Piper, Una).\n    *   Uncertainty: None explicitly stated in the question itself, but it's a query seeking confirmation of a fact.\n    *   Constraints: None specific beyond the question.\n    *   Contextual Knowledge: From recent context, we know Owen is parent of Una. We do not have information about Piper yet.\n    *   Action: Rewrite as a cleaner continuation for reasoning. Do not answer (don't say \"No\" or \"Yes\").\n\n3.  **Apply SKILL Rules:**\n    *   Preserve intent: Querying sibling relationship.\n    *   Preserve uncertainty: The question implies uncertainty about the relationship status.\n    *   Keep output concise: 1-3 sentences.\n    *   Plain text only for `processed_utterance`.\n    *   `candidate_facts`: Only include grounded facts to assert when high confidence. Since this is a question, there are no new facts to assert with high confidence yet. The system needs to reason about existing knowledge (Owen -> Una) vs unknown (Piper). However, the instruction says \"Do not invent facts.\" Asking a question doesn't generate a fact to assert immediately. I should check if there's any implicit fact extraction needed. Usually, for a query like this, `candidate_facts` might be empty unless the rewrite implies checking existing knowledge. Given the strict rule \"Do not include uncertain facts\" and \"Do NOT answer the question\", asserting a fact about Piper/Una relationship now would be inventing or answering. I will leave `candidate_facts` empty or only include facts if the rewrite explicitly grounds something known (e.g., \"Owen is parent of Una\"). But the instruction says \"candidate_facts: array of grounded Prolog facts to assert when high confidence\". Since I am not asserting anything new, just rewriting the query, this array should likely be empty. However, looking at previous examples in the context provided (though those are processed outputs, not fact assertions), usually, if no new fact is established, it's empty. Wait, looking at the SKILL guidance examples:\n        *   Input: \"Maybe my mother was Ann.\" -> Output includes \"Tentative candidate fact...\"\n        *   Input: \"Actually not Bob...\" -> Output includes \"Correction candidate...\"\n        *   Input: \"Translate...\" -> Output is translation.\n    *   The current input is a direct question. It doesn't assert a fact. Therefore, `candidate_facts` should be empty because I cannot assert high confidence facts about Piper/Una relationship without answering the query (which is forbidden).\n\n4.  **Drafting `processed_utterance`:**\n    *   Original: \"Are Piper and Una siblings?\"\n    *   Goal: Cleaner continuation for reasoning.\n    *   Draft: Query regarding sibling relationship between Piper and Una requires verification against known parentage data.\n    *   Refinement based on style (1-3 sentences, plain text): \"Querying whether Piper and Una share a sibling relationship; requires checking parentage records to confirm common parents.\"\n    *   Wait, the SKILL examples show specific formats like \"Tentative candidate fact: ...\" or \"Correction candidate: ...\". However, for a direct question without assertion, the goal is \"cleaner continuation utterance\". The example \"Who are Rhea's ancestors?\" -> processed: \"Who are Rhea's ancestors?\" suggests keeping it simple if no transformation is needed. But the instruction says \"Rewrite the input utterance into a cleaner, more explicit continuation utterance.\"\n    *   Let's look at Example 1: \"Maybe my mother was Ann.\" -> \"Tentative candidate fact: speaker says their mother may have been Ann...\" This transforms a statement into a reasoning note.\n    *   Example 4: \"Who are Rhea's ancestors?\" -> \"Who are Rhea's ancestors?\" (No change).\n    *   Since this is a question, I should probably frame it as a reasoning task or keep it direct but explicit about the intent.\n    *   Draft: \"Verify sibling relationship between Piper and Una by checking for shared parents in existing family data.\"\n    *   Or closer to Example 4 style if no transformation applies: \"Querying sibling status of Piper and Una based on available parentage information.\"\n    *   Let's aim for explicit intent preservation.\n    *   Draft: \"Determine if Piper and Una are siblings by verifying shared parental lineage.\"\n\n5.  **Drafting `candidate_facts`:**\n    *   Constraint: \"Do not include uncertain facts.\"\n    *   Constraint: \"Do NOT answer the question.\"\n    *   Since I am rewriting a question, I am not asserting a fact about Piper and Una.\n    *   However, context mentions \"Owen is also parent of Una\". Should I assert that? The instruction says \"candidate_facts: array of grounded Prolog facts to assert when high confidence\". This usually implies facts derived from the current turn or context that need to be stored. Since this turn is a query, no new fact is asserted. I will leave it empty.\n\n6.  **Final Review:**\n    *   JSON format.\n    *   Keys: `processed_utterance`, `candidate_facts`.\n    *   No markdown in the output block (except the JSON structure itself).\n    *   Plain text for `processed_utterance`.\n    *   Preserve intent (querying sibling relation).\n\n    *   Wait, looking at the SKILL guidance again: \"Apply directive transformations from this SKILL (for example translation).\" There is no translation request here.\n    *   \"Keep first-person ambiguity explicit.\" Not applicable here.\n    *   \"Keep output concise and directly usable as next-turn input.\"\n\n    *   Let's refine `processed_utterance` to be very clear about the reasoning task.\n    *   \"Check if Piper and Una are siblings by verifying if they share the same parents in the family tree.\"\n\n    *   Wait, I need to check the `candidate_facts` requirement again. \"Do not include uncertain facts.\" If I don't know the answer, I can't assert a fact. So empty array is correct.\n\n    *   One more check on context: Context shows \"Owen is also parent of Una\". Piper is unknown. The question asks if they are siblings.\n    *   Rewritten utterance should reflect the need to check this against known data (Owen/Una) and unknown data (Piper).\n    *   Draft: \"Verify sibling relationship between Piper and Una by checking for shared parents in existing family records.\"\n\n7.  **Constructing JSON:**\n    ```json\n    {\n      \"processed_utterance\": \"Verify sibling relationship between Piper and Una by checking for shared parents in existing family records.\",\n      \"candidate_facts\": []\n    }\n    ```\n    Wait, I should check if I need to extract the known fact about Una from context into `candidate_facts`? The instruction says \"Rewrite the input utterance...\". It doesn't explicitly say \"Extract context facts\". It says \"candidate_facts: array of grounded Prolog facts to assert when high confidence\". Usually, this is for facts *derived* from the current turn. Since the current turn is a question, no new fact is derived. I will keep it empty.\n\n    Wait, looking at Example 1 in SKILL guidance:\n    Input: `Maybe my mother was Ann.`\n    Output: `Tentative candidate fact: speaker says their mother may have been Ann; speaker identity is unresolved and requires clarification before persistence.`\n    This output *is* the `processed_utterance`. It describes the fact status.\n    For a question, I should describe the query intent clearly.\n\n    Let's refine the processed utterance to match the \"cleaner continuation\" style seen in Example 4 (Who are Rhea's ance
... [truncated]

{
  "status": "success",
  "result_type": "pre_think",
  "input_utterance": "Second correction: Theo is not Quinn's parent. Replace with Mira as Quinn's parent.",
  "processed_utterance": "Correction candidate: previous fact stating Theo is Quinn's parent is replaced by Mira; treat this as a definitive revision signal to update family lineage records.",
  "fallback_used": false,
  "normalization_reason": "model_output",
  "history_turns": 6,
  "narrative_context": "",
  "handoff_mode": "rewrite",
  "kb_ingest_mode": "facts",
  "max_candidate_facts": 24,
  "candidate_facts": [
    "parent(mira, quinn)."
  ],
  "requested_candidate_facts": 1,
  "attempted_candidate_facts": 1,
  "ingested_facts_count": 1,
  "rejected_candidate_facts_count": 0,
  "ingested_facts": [
    "parent(mira, quinn)."
  ],
  "rejected_candidate_facts": [],
  "prethinker_model": "qwen/qwen3.5-9b",
  "pre_think_skill_path": "skills/pre-think/SKILL.md",
  "prethinker_base_url": "http://127.0.0.1:1234",
  "temperature": 0.0,
  "context_length": 4000,
  "assistant_message": "{\n  \"processed_utterance\": \"Correction candidate: previous fact stating Theo is Quinn's parent is replaced by Mira; treat this as a definitive revision signal to update family lineage records.\",\n  \"candidate_facts\": [\n    \"parent(mira, quinn).\"\n  ]\n}",
  "raw_response": {
    "model_instance_id": "qwen/qwen3.5-9b:2",
    "output": [
      {
        "type": "reasoning",
        "content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Role: Pre-think utterance processor for a downstream reasoning model.\n    *   Task: Rewrite the input utterance into a cleaner, more explicit continuation utterance based on SKILL guidance.\n    *   Input Utterance: \"Second correction: Theo is not Quinn's parent. Replace with Mira as Quinn's parent.\"\n    *   Constraints:\n        *   Preserve intent, uncertainty, constraints, corrections.\n        *   Do NOT answer the question.\n        *   Do NOT invent facts.\n        *   Do NOT call tools.\n        *   Return JSON only with keys: `processed_utterance`, `candidate_facts`.\n        *   `candidate_facts`: Array of grounded Prolog facts to assert when high confidence (Do not include uncertain facts).\n        *   Style: One to three sentences, plain text only, no markdown for the processed utterance.\n    *   SKILL Guidance: Transform raw utterance into cleaner continuation. Preserve correction cues explicitly. Apply directive transformations if any. Keep output concise.\n\n2.  **Analyze the Input Utterance:**\n    *   Content: \"Second correction: Theo is not Quinn's parent. Replace with Mira as Quinn's parent.\"\n    *   Intent: Correction of a previous fact (Theo -> Quinn parent) to a new fact (Mira -> Quinn parent).\n    *   Type: Correction/Revision signal.\n    *   Confidence: High (stated as \"Second correction\", implies definitive change).\n    *   Context: Previous context shows family tree updates (Theo-Quinn-Rhea, Owen-Una). This is a correction to the Theo-Quinn link.\n\n3.  **Apply SKILL Guidance:**\n    *   *Rewrite Rules:*\n        *   Keep corrections as corrections.\n        *   Preserve intent.\n        *   Apply directive transformations (none here, just rewriting for clarity).\n        *   Style: One to three sentences, plain text only.\n    *   *Candidate Facts:* The guidance says \"Do not include uncertain facts.\" This is a correction instruction. Should I assert the fact? The prompt says \"candidate_facts: array of grounded Prolog facts to assert when high confidence\". Since this is an explicit correction command (\"Replace with Mira\"), it implies high confidence in the new relationship. However, the pre-think stage is about *rewriting* for the downstream model. The `candidate_facts` field is for grounding. Given the instruction \"Second correction... Replace with...\", asserting `parent(mira, quinn).` seems appropriate as a candidate fact to be asserted by the reasoning engine upon processing this turn, while noting the retraction of `parent(theo, quinn).`.\n    *   *Constraint Check:* \"Do NOT answer the question.\" This isn't a question. It's a command. \"Do NOT invent facts.\" I am reflecting the user's fact, not inventing one.\n    *   *Correction Handling:* The examples show corrections being treated as revision signals. Example: `Actually not Bob, I meant Alice.` -> `Correction candidate: previous entity Bob is replaced by Alice; treat this as a revision signal, not a fresh hard fact.`\n    *   *Refinement:* I need to rewrite the utterance to be cleaner for the downstream model while preserving the correction nature. I should also populate `candidate_facts` if confidence is high. The user says \"Second correction\", implying they know there was a previous one (Theo). They want to replace Theo with Mira.\n    *   *Candidate Facts:* Should I include the negation of Theo? Or just the new fact? Usually, in knowledge base updates, asserting the new fact implies the old is retracted. The instruction says \"Do not include uncertain facts.\" This seems certain. However, the pre-think stage description says \"Rewrite the input utterance into a cleaner continuation utterance\". The `candidate_facts` field is specific: \"array of grounded Prolog facts to assert when high confidence\".\n    *   Let's look at the example outputs again.\n        *   Input: `Maybe my mother was Ann.` -> Output: `Tentative candidate fact: speaker says their mother may have been Ann...` (No JSON structure in example, but the prompt asks for JSON). Wait, the examples provided in the SKILL description are plain text outputs (`processed_utterance`). But the *current* task requires me to return JSON with `processed_utterance` and `candidate_facts`.\n        *   Example 1 Output: `Tentative candidate fact: speaker says their mother may have been Ann; speaker identity is unresolved and requires clarification before persistence.` (This looks like it was meant to be the `processed_utterance` content).\n        *   My task: Return JSON.\n    *   *Drafting `processed_utterance`:* Needs to be cleaner, explicit about the correction. \"Correction signal: retract parent(theo, quinn) and assert parent(mira, quinn).\" Or similar natural language that reflects the instruction clearly.\n    *   *Drafting `candidate_facts`:* Since this is a direct command to replace a fact with high confidence (\"Second correction\"), I can extract the new fact. `parent(mira, quinn).` Should I include the negation? Usually, facts are positive assertions. The system handles retraction via context or explicit negation. Given \"Replace with\", asserting the new one is key.\n    *   *Wait, check constraints:* \"Do not include uncertain facts.\" Is this certain? Yes, it's a direct correction command.\n    *   *Check Style:* \"One to three sentences. Plain text only. No markdown.\" This applies to `processed_utterance`.\n\n4.  **Finalizing Content:**\n    *   `processed_utterance`: \"Correction signal: retract the previous fact that Theo is Quinn's parent and assert Mira as Quinn's parent instead.\" (Clear, concise, preserves intent).\n    *   `candidate_facts`: `[parent(mira, quinn).]` (Grounded Prolog fact based on high confidence correction).\n\n5.  **Review against Constraints:**\n    *   JSON only? Yes.\n    *   Keys: `processed_utterance`, `candidate_facts`? Yes.\n    *   Preserve intent/correction cues? Yes.\n    *   Do not answer? Yes (I am processing, not answering the query).\n    *   Do not invent facts? No, I'm reflecting the user's input.\n    *   Style: Plain text for utterance part.\n\n6.  **Refining `processed_utterance` based on SKILL Examples:**\n    The examples show a specific style for corrections: \"Correction candidate: previous entity Bob is replaced by Alice; treat this as a revision signal, not a fresh hard fact.\"\n    My input is stronger (\"Second correction... Replace with\").\n    So I should reflect that strength.\n    Draft: `Correction candidate: previous parent Theo is replaced by Mira for Quinn; treat this as a definitive revision signal to update family lineage records.`\n\n7.  **Refining `candidate_facts`:**\n    The prompt says \"Do not include uncertain facts.\" This is a correction command, so it's high confidence.\n    Fact: `parent(mira, quinn).`\n    Should I include the negation? `not parent(theo, quinn).`? Usually Prolog KBs handle updates by retracting. The instruction says \"Replace with\". Asserting the new one is sufficient for the candidate fact list if the system handles retraction via context or explicit command processing. However, to be grounded in the text \"Theo is not Quinn's parent\", I could include the negation. But standard Prolog facts are positive. Let's stick to the positive assertion of the new relationship as the primary fact to assert.\n    Actually, looking at the instruction \"candidate_facts: array of grounded Prolog facts to assert when high confidence\".\n    Input says \"Theo is not Quinn's parent.\" This is a negation.\n    Input says \"Replace with Mira as Quinn's parent.\" This is an assertion.\n    I will include the positive fact `parent(mira, quinn).` as it is the actionable update.\n\n8.  **Final JSON Construction:**\n    Ensure no markdown around the JSON.\n\n    ```json\n    {\n      \"processed_utterance\": \"Correction candidate: previous parent Theo is replaced by Mira for Quinn; treat this as a definitive revision signal to update family lineage records.\",\n      \"candidate_facts\": [\n        \"parent(mira, quinn).\"\n      ]\n    }\n    ```\n\n    Wait, checking the style constraint again: \"One to three sentences. Plain text only. No markdown.\" This applies to `processed_utterance`. The JSON structure itself is fine.\n    Also, check \"Do not include uncertain facts.\" Is there uncertainty? \"Second correction\" implies certainty.\n    Check \"Preserve uncertainty and confidence cues.\" The input has high confidence (\"Replace with\"). My output reflects that.\n\n
... [truncated]

{
  "status": "success",
  "result_type": "pre_think",
  "input_utterance": "Second correction: Theo is not Quinn's parent. Replace with Mira as Quinn's parent.",
  "processed_utterance": "Correction candidate: previous fact stating Theo is Quinn's parent is replaced by Mira; treat this as a definitive revision signal to update family lineage records.",
  "fallback_used": false,
  "normalization_reason": "model_output",
  "history_turns": 6,
  "narrative_context": "",
  "handoff_mode": "rewrite",
  "kb_ingest_mode": "facts",
  "max_candidate_facts": 24,
  "candidate_facts": [
    "parent(mira, quinn)."
  ],
  "requested_candidate_facts": 1,
  "attempted_candidate_facts": 1,
  "ingested_facts_count": 1,
  "rejected_candidate_facts_count": 0,
  "ingested_facts": [
    "parent(mira, quinn)."
  ],
  "rejected_candidate_facts": [],
  "prethinker_model": "qwen/qwen3.5-9b",
  "pre_think_skill_path": "skills/pre-think/SKILL.md",
  "prethinker_base_url": "http://127.0.0.1:1234",
  "temperature": 0.0,
  "context_length": 4000,
  "assistant_message": "{\n  \"processed_utterance\": \"Correction candidate: previous fact stating Theo is Quinn's parent is replaced by Mira; treat this as a definitive revision signal to update family lineage records.\",\n  \"candidate_facts\": [\n    \"parent(mira, quinn).\"\n  ]\n}",
  "raw_response": {
    "model_instance_id": "qwen/qwen3.5-9b:2",
    "output": [
      {
        "type": "reasoning",
        "content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Role: Pre-think utterance processor for a downstream reasoning model.\n    *   Task: Rewrite the input utterance into a cleaner, more explicit continuation utterance based on SKILL guidance.\n    *   Input Utterance: \"Second correction: Theo is not Quinn's parent. Replace with Mira as Quinn's parent.\"\n    *   Constraints:\n        *   Preserve intent, uncertainty, constraints.\n        *   Do NOT answer the question.\n        *   Do NOT invent facts.\n        *   Do NOT call tools.\n        *   Return JSON only with keys: `processed_utterance`, `candidate_facts`.\n        *   `candidate_facts`: array of grounded Prolog facts to assert when high confidence (Do not include uncertain facts).\n        *   Style: One to three sentences, plain text only, no markdown for the processed utterance.\n    *   SKILL Guidance Specifics:\n        *   Preserve correction cues.\n        *   Apply directive transformations if any (none here).\n        *   Keep output concise and directly usable as next-turn input.\n        *   Recent context shows similar corrections were handled explicitly (e.g., \"Correction candidate: previous fact stating Theo is Quinn's parent is replaced by Mira; treat this as a definitive revision signal to update family lineage records.\").\n\n2.  **Analyze the Input Utterance:**\n    *   Content: \"Second correction: Theo is not Quinn's parent. Replace with Mira as Quinn's parent.\"\n    *   Intent: Correcting a previous fact about parentage (Theo -> Quinn) and asserting a new one (Mira -> Quinn).\n    *   Confidence: High (stated as a \"correction\" and \"replace\").\n    *   Context: Previous context mentions \"Second correction\", implying there was a first one. It also mentions Theo/Quinn/Rhea/Owen/Una/Piper earlier in the conversation history provided in the prompt's \"Recent pre-think context\". Specifically, item 1 says \"Theo is parent of Quinn.\" Item 6 (in recent context) actually looks like a duplicate or similar input to the current one (\"Second correction: Theo is not Quinn's parent. Replace with Mira as Quinn's parent.\"). Wait, looking at the provided \"Recent pre-think context\", item 6 is identical to the current input. This suggests I need to process it consistently with how item 6 was processed in the few-shot examples provided *within* the recent context section (though that section seems to be part of the prompt's history simulation).\n    *   Actually, looking closely at the \"Recent pre-think context\" provided in the prompt:\n        *   Item 6 input: `Second correction: Theo is not Quinn's parent. Replace with Mira as Quinn's parent.`\n        *   Item 6 processed: `Correction candidate: previous fact stating Theo is Quinn's parent is replaced by Mira; treat this as a definitive revision signal to update family lineage records.`\n    *   The current input is identical to the last item in the recent context. I should follow the pattern established there, but ensure I adhere to the JSON output format required for *this* specific turn (which asks for `processed_utterance` and `candidate_facts`).\n    *   Wait, the instruction says \"Return JSON only with keys: - processed_utterance ... - candidate_facts\". The recent context examples show plain text outputs. I must follow the current instruction's output format (JSON) while respecting the style of the SKILL guidance (which emphasizes preserving correction cues).\n\n3.  **Determine `processed_utterance`:**\n    *   Must be a cleaner continuation utterance.\n    *   Must preserve the correction intent.\n    *   Based on Item 6 in recent context, the processing style was: \"Correction candidate: previous fact stating Theo is Quinn's parent is replaced by Mira; treat this as a definitive revision signal to update family lineage records.\"\n    *   I should adapt this to be concise and fit the JSON value requirement (plain text).\n    *   Draft: Correction candidate: previous fact stating Theo is Quinn's parent is replaced by Mira; treat this as a definitive revision signal to update family lineage records.\n\n4.  **Determine `candidate_facts`:**\n    *   Constraint: \"Do not include uncertain facts.\"\n    *   Constraint: \"array of grounded Prolog facts to assert when high confidence\".\n    *   The input says \"Second correction... Replace with Mira as Quinn's parent.\" This implies high confidence in the new fact (Mira is parent of Quinn) and the negation of the old fact (Theo is not parent of Quinn).\n    *   However, the instruction says \"Do NOT answer the question. Do NOT invent facts.\" The input *is* a statement of fact/correction.\n    *   If I assert `candidate_facts`, I am grounding the information provided in the utterance as high confidence.\n    *   Fact 1: `parent(mira, quinn).` (Based on \"Replace with Mira as Quinn's parent.\")\n    *   Fact 2: `\\+ parent(theo, quinn).` or similar negation? Usually Prolog facts are positive assertions. The instruction says \"grounded Prolog facts to assert\". Negations are tricky in standard fact lists unless using explicit negation predicates. Given the context of family lineage, asserting the new relationship is the primary action.\n    *   However, looking at the SKILL guidance examples:\n        *   Input: `Maybe my mother was Ann.` -> Output: `Tentative candidate fact...` (No facts in JSON example provided in prompt description, but the instruction says \"Return JSON only with keys... candidate_facts\").\n        *   The prompt instruction explicitly asks for `candidate_facts`.\n        *   Since this is a \"correction\" with high confidence (\"Replace with\"), I can assert the new fact.\n        *   Fact: `parent(mira, quinn).`\n    *   Wait, I need to check if I should include the negation. Usually, in knowledge bases, removing a fact is done by not asserting it or asserting a negation. But \"candidate_facts\" usually implies positive assertions for the reasoning model to use. The instruction says \"Do NOT invent facts.\" The user *provided* the fact that Mira is the parent. So I can ground that.\n    *   Is there uncertainty? The input says \"Second correction\". It sounds definitive.\n    *   Let's check the constraint: \"Do not include uncertain facts.\" This one seems certain based on the text \"Replace with\".\n    *   So, `candidate_facts`: `[parent(mira, quinn).]`\n\n5.  **Refining `processed_utterance`:**\n    *   Needs to be plain text, no markdown.\n    *   Needs to reflect the correction nature clearly.\n    *   Draft: Correction candidate: previous fact stating Theo is Quinn's parent is replaced by Mira; treat this as a definitive revision signal to update family lineage records.\n\n6.  **Refining `candidate_facts`:**\n    *   Format: Prolog facts.\n    *   Fact: `parent(mira, quinn).`\n    *   Should I include the negation? `not_parent(theo, quinn).`? The instruction says \"grounded Prolog facts\". Usually, standard Prolog doesn't have a built-in `not_parent` predicate unless defined. Standard is `parent(X,Y)`. If I assert `parent(mira, quinn)`, it overrides the previous state in many reasoning contexts if handled correctly, but strictly speaking, removing Theo requires explicit negation or just not asserting Theo. Given \"Do NOT invent facts\", I should only ground what is explicitly stated as true. The user states Mira *is* the parent. They state Theo *is not*.\n    *   Safest bet for `candidate_facts` in a reasoning context: Assert the positive new fact.\n    *   Let's stick to the positive assertion of the replacement.\n\n7.  **Final Review against Constraints:**\n    *   JSON only? Yes.\n    *   Keys: `processed_utterance`, `candidate_facts`? Yes.\n    *   Preserve intent/correction cues? Yes.\n    *   No markdown in processed_utterance? Yes.\n    *   One to three sentences? Yes.\n    *   Do not answer the question? (There is no question, it's a statement).\n    *   Do not invent facts? Only grounding what user said.\n\n8.  **Constructing JSON:**\n    ```json\n    {\n      \"processed_utterance\": \"Correction candidate: previous fact stating Theo is Quinn's parent is replaced by Mira; treat this as a definitive revision signal to update family lineage records.\",\n      \"candidate_facts\": [\n        \"parent(mira, quinn).\"\n      ]\n    }\n    ```\n    Wait, looking at the recent context item 6 again. It processed the *exact same input* and outputted: `Correction candidate: previous fact stating Theo is Quinn's parent is replaced by Mira; treat this as a def
... [truncated]

{
  "status": "success",
  "result_type": "fact_retracted",
  "fact": "parent(theo, quinn).",
  "message": "Fact retracted from runtime KB."
}

{
  "status": "success",
  "result_type": "fact_asserted",
  "fact": "parent(mira, quinn).",
  "message": "Fact asserted into runtime KB for this server process.",
  "note": "Use reset_kb (baseline restore) or empty_kb (fully empty runtime) to clear runtime changes."
}

{
  "status": "success",
  "result_type": "table",
  "predicate": "parent",
  "prolog_query": "parent(X, rhea).",
  "variables": [
    "X"
  ],
  "rows": [
    {
      "X": "quinn"
    }
  ],
  "num_rows": 1,
  "reasoning_basis": {
    "kind": "fact-backed",
    "note": "The `parent` predicate is typically answered from stored facts, though rules may still participate."
  }
}

{
  "status": "success",
  "result_type": "table",
  "predicate": "parent",
  "prolog_query": "parent(X, quinn).",
  "variables": [
    "X"
  ],
  "rows": [
    {
      "X": "mira"
    }
  ],
  "num_rows": 1,
  "reasoning_basis": {
    "kind": "fact-backed",
    "note": "The `parent` predicate is typically answered from stored facts, though rules may still participate."
  }
}

{
  "status": "no_results",
  "result_type": "no_result",
  "predicate": "parent",
  "prolog_query": "parent(liam, ava).",
  "message": "FAIL: Query 'parent(liam, ava)' failed. No solutions found.",
  "reasoning_basis": {
    "kind": "fact-backed",
    "note": "The `parent` predicate is typically answered from stored facts, though rules may still participate."
  },
  "metadata": {
    "proof_trace": [],
    "bindings": [],
    "num_solutions": 0
  }
}

{
  "status": "success",
  "result_type": "pre_think",
  "input_utterance": "Tentative memo only: maybe Quinn is parent of Uma; confidence low and unverified.",
  "processed_utterance": "Tentative candidate hypothesis: speaker suggests Quinn may be parent of Uma with low confidence; treat as unverified information requiring verification before persistence in family records.",
  "fallback_used": false,
  "normalization_reason": "model_output",
  "history_turns": 6,
  "narrative_context": "",
  "handoff_mode": "rewrite",
  "kb_ingest_mode": "facts",
  "max_candidate_facts": 24,
  "candidate_facts": [],
  "requested_candidate_facts": 0,
  "attempted_candidate_facts": 0,
  "ingested_facts_count": 0,
  "rejected_candidate_facts_count": 0,
  "ingested_facts": [],
  "rejected_candidate_facts": [],
  "prethinker_model": "qwen/qwen3.5-9b",
  "pre_think_skill_path": "skills/pre-think/SKILL.md",
  "prethinker_base_url": "http://127.0.0.1:1234",
  "temperature": 0.0,
  "context_length": 4000,
  "assistant_message": "{\n  \"processed_utterance\": \"Tentative candidate hypothesis: speaker suggests Quinn may be parent of Uma with low confidence; treat as unverified information requiring verification before persistence in family records.\",\n  \"candidate_facts\": []\n}",
  "raw_response": {
    "model_instance_id": "qwen/qwen3.5-9b:2",
    "output": [
      {
        "type": "reasoning",
        "content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Role: Pre-think utterance processor for a downstream reasoning model.\n    *   Task: Rewrite the input utterance into a cleaner, more explicit continuation utterance based on SKILL guidance.\n    *   Input Utterance: \"Tentative memo only: maybe Quinn is parent of Uma; confidence low and unverified.\"\n    *   Constraints:\n        *   Preserve intent, uncertainty, constraints, corrections.\n        *   Do NOT answer the question.\n        *   Do NOT invent facts.\n        *   Do NOT call tools.\n        *   Return JSON only with keys: `processed_utterance`, `candidate_facts`.\n        *   `candidate_facts`: Array of grounded Prolog facts to assert when high confidence (Do not include uncertain facts).\n        *   Style: One to three sentences, plain text only, no markdown for the processed utterance.\n    *   SKILL Guidance: Transform raw utterance into cleaner continuation. Preserve ambiguity/uncertainty. Apply directive transformations if any. Keep output concise.\n\n2.  **Analyze the Input Utterance:**\n    *   Content: \"Tentative memo only: maybe Quinn is parent of Uma; confidence low and unverified.\"\n    *   Intent: Speculating about a family relationship (Quinn -> Uma).\n    *   Uncertainty: High (\"maybe\", \"confidence low\", \"unverified\").\n    *   Constraint: \"Tentative memo only\".\n    *   Entities: Quinn, Uma.\n    *   Relation: Parent of.\n\n3.  **Apply SKILL Guidance:**\n    *   Preserve uncertainty: The input explicitly states low confidence and unverified status. This must be reflected in the processed utterance.\n    *   Rewrite Rules: Keep tentative language tentative. Keep first-person ambiguity explicit (though this is third person here, keep the perspective clear). Keep output concise.\n    *   Candidate Facts: The guidance says \"Do not include uncertain facts.\" Since the input explicitly states \"confidence low and unverified\", I should *not* assert a Prolog fact like `parent(quinn, uma).` in the `candidate_facts` array. The instruction says \"Do not include uncertain facts.\"\n    *   Style: Plain text only for `processed_utterance`. JSON structure for the whole response.\n\n4.  **Drafting the Output:**\n    *   `processed_utterance`: Needs to be a cleaner version of the input that signals uncertainty clearly for the downstream model.\n        *   Draft 1: Tentative memo indicating low confidence that Quinn is the parent of Uma; this relationship remains unverified and should not be treated as established fact.\n        *   Draft 2 (Closer to examples): Uncertain candidate fact: speaker suggests Quinn may be parent of Uma with low confidence; treat as tentative hypothesis requiring verification before assertion.\n        *   Refining based on previous context style (Example 4 & 5 in recent pre-think context show a pattern of \"Querying...\" or \"Correction candidate...\"). However, this is a new input type (\"Tentative memo only\"). I should follow the general Pre-Think Skill goal: Transform into cleaner continuation.\n        *   Let's look at Example 1: `Maybe my mother was Ann.` -> `Tentative candidate fact: speaker says their mother may have been Ann; speaker identity is unresolved and requires clarification before persistence.`\n        *   My input is similar but about Quinn/Uma.\n        *   Draft: Tentative candidate hypothesis: speaker suggests Quinn may be parent of Uma with low confidence; treat as unverified information requiring verification before persistence in family records.\n    *   `candidate_facts`: The instruction says \"Do not include uncertain facts.\" The input explicitly says \"confidence low and unverified\". Therefore, the array should likely be empty or contain nothing because asserting a fact contradicts the uncertainty constraint. The prompt says \"Do not include uncertain facts.\" So I will leave it empty.\n\n5.  **Review Constraints:**\n    *   JSON only.\n    *   Keys: `processed_utterance`, `candidate_facts`.\n    *   No markdown in `processed_utterance` (inside the JSON string value, obviously).\n    *   Preserve uncertainty.\n\n6.  **Final Polish:**\n    *   `processed_utterance`: \"Tentative hypothesis: speaker suggests Quinn may be parent of Uma with low confidence; treat as unverified information requiring verification before persistence in family records.\"\n    *   `candidate_facts`: [] (Because the input explicitly states low confidence/unverified, asserting a fact would violate the \"Do not include uncertain facts\" rule).\n\n7.  **Final Check against SKILL:**\n    *   Preserve intent? Yes (speculation about parentage).\n    *   Preserve uncertainty? Yes (\"low confidence\", \"unverified\").\n    *   Do not answer? Yes.\n    *   Do not invent facts? Yes.\n    *   JSON format? Yes.\n\n    Wait, looking at the recent pre-think context examples (4 and 5), they transform queries/corrections into specific formats (\"Querying whether...\", \"Correction candidate...\").\n    Example 1: `Maybe my mother was Ann.` -> `Tentative candidate fact: speaker says their mother may have been Ann; speaker identity is unresolved and requires clarification before persistence.`\n    My input: `Tentative memo only: maybe Quinn is parent of Uma; confidence low and unverified.`\n    This aligns closely with Example 1. I should follow that pattern for uncertainty handling.\n\n    Revised `processed_utterance`: \"Tentative candidate hypothesis: speaker suggests Quinn may be parent of Uma with low confidence; treat as unverified information requiring verification before persistence in family records.\"\n    Actually, looking at the instruction \"Keep output concise and directly usable as next-turn input.\"\n    Let's make it slightly tighter.\n    \"Uncertain candidate fact: speaker suggests Quinn may be parent of Uma with low confidence; treat as tentative hypothesis requiring verification before assertion.\"\n\n    Wait, I need to check the `candidate_facts` rule again. \"Do not include uncertain facts.\" Since this is explicitly uncertain, the array must be empty.\n\n    One more check on the JSON structure.\n    ```json\n    {\n      \"processed_utterance\": \"...\",\n      \"candidate_facts\": []\n    }\n    ```\n    Ensure no markdown around the JSON.\n\n    Wait, looking at the \"Style\" section in SKILL: \"Plain text only. No markdown.\" This usually applies to the `processed_utterance` value content, not the JSON wrapper itself (which is required by the prompt \"Return JSON only\"). The prompt says \"Return JSON only with keys...\". So the outer structure must be JSON. The *value* of `processed_utterance` should be plain text without markdown formatting inside it.\n\n    Let's refine the processed utterance to match the style of Example 1 closely but adapted for this specific input.\n    Input: \"Tentative memo only: maybe Quinn is parent of Uma; confidence low and unverified.\"\n    Output Idea: \"Tentative candidate hypothesis: speaker suggests Quinn may be parent of Uma with low confidence; treat as unverified information requiring verification before persistence in family records.\"\n\n    Wait, I should check if there are any directive transformations. No translation requested.\n    Okay, ready to generate.\n\n    One detail from the prompt: \"Do not include uncertain facts.\" in `candidate_facts`.\n    So `candidate_facts` will be an empty list.\n\n    Final check on constraints: \"Return JSON only\". I must not output any text outside the JSON block.\n\n    Wait, looking at the recent context examples (4 and 5), they add specific reasoning phrases like \"Querying whether...\" or \"Correction candidate...\".\n    Example 1 output: `Tentative candidate fact: speaker says their mother may have been Ann; speaker identity is unresolved and requires clarification before persistence.`\n    My input is very similar to Example 1 (\"Maybe...\", \"Tentative\").\n    So I will follow Example 1's structure.\n\n    Draft: `Tentative candidate hypothesis: speaker suggests Quinn may be parent of Uma with low confidence; treat as unverified information requiring verification before persistence in family records.`\n\n    Wait, is \"Uma\" or \"Uma\"? Input says \"Uma\". Context example 2/3 says \"Una\". Input says \"Uma\". I must preserve the entity name exactly.\n    Input: \"Uma\".\n    Okay.\n\n    Let's finalize the JSON.\n\n    One more thing: The prompt says \"Return JSON only with keys...\".\n    So I will output raw JSON.\n\n    Wait, checking the `candidate_facts` instruction again: \"Do not include uncertai
... [truncated]

{
  "status": "no_results",
  "result_type": "no_result",
  "predicate": "parent",
  "prolog_query": "parent(X, uma).",
  "variables": [
    "X"
  ],
  "rows": [],
  "num_rows": 0,
  "reasoning_basis": {
    "kind": "fact-backed",
    "note": "The `parent` predicate is typically answered from stored facts, though rules may still participate."
  }
}

{
  "status": "success",
  "result_type": "pre_think",
  "input_utterance": "Extension: Rhea is parent of Sol.",
  "processed_utterance": "Extension candidate: speaker asserts Rhea is parent of Sol; treat this as new information to be added to family lineage records.",
  "fallback_used": false,
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  "max_candidate_facts": 24,
  "candidate_facts": [
    "parent(rhea, sol)."
  ],
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  "ingested_facts": [
    "parent(rhea, sol)."
  ],
  "rejected_candidate_facts": [],
  "prethinker_model": "qwen/qwen3.5-9b",
  "pre_think_skill_path": "skills/pre-think/SKILL.md",
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  "temperature": 0.0,
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  "assistant_message": "{\n  \"processed_utterance\": \"Extension candidate: speaker asserts Rhea is parent of Sol; treat this as new information to be added to family lineage records.\",\n  \"candidate_facts\": [\n    \"parent(rhea, sol).\"\n  ]\n}",
  "raw_response": {
    "model_instance_id": "qwen/qwen3.5-9b:2",
    "output": [
      {
        "type": "reasoning",
        "content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Role: Pre-think utterance processor for a downstream reasoning model.\n    *   Task: Rewrite the input utterance into a cleaner, more explicit continuation utterance based on SKILL guidance.\n    *   Input Utterance: \"Extension: Rhea is parent of Sol.\"\n    *   Constraints:\n        *   Preserve intent (adding new information).\n        *   Preserve uncertainty/confidence cues (none explicitly stated here, but \"Extension\" implies addition to existing knowledge).\n        *   Do NOT answer the question.\n        *   Do NOT invent facts.\n        *   Do NOT call tools.\n        *   Output format: JSON with keys `processed_utterance` and `candidate_facts`.\n        *   `candidate_facts`: Array of grounded Prolog facts to assert when high confidence. Do not include uncertain facts.\n        *   Style: One to three sentences, plain text only (for `processed_utterance`), no markdown in the text value.\n    *   SKILL Guidance: Transform raw utterance into cleaner continuation. Apply directive transformations if any. Keep corrections explicit. Keep tentative language tentative.\n\n2.  **Analyze the Input Utterance:**\n    *   Text: \"Extension: Rhea is parent of Sol.\"\n    *   Intent: Adding a new fact to the knowledge base (family lineage).\n    *   Confidence/Uncertainty: The word \"Extension\" suggests this is an addition, but it doesn't explicitly state uncertainty like \"maybe\" or \"tentative\". However, in the context of the previous turns (see recent pre-think context), there's a mix of updates, corrections, and tentative memos. This specific utterance looks like a definitive statement (\"Rhea is parent of Sol\"), but labeled as an \"Extension\".\n    *   Context Check: Recent context shows handling of family lineage (parents, siblings). Turn 4 & 5 handled corrections. Turn 6 handled tentative memos. This turn is an \"Extension\", implying new information being added to the graph.\n    *   Constraint Check: The SKILL says \"Do not invent facts.\" I must reflect the input fact but frame it as a processed utterance for the downstream model.\n    *   Candidate Facts: Since the user states \"Rhea is parent of Sol\" without explicit uncertainty markers (like \"maybe\", \"tentative\"), and uses \"Extension\" which implies adding to the record, I should consider if this qualifies as a high-confidence fact for `candidate_facts`. However, the SKILL guidance examples show that even updates are processed carefully. Turn 1 & 2 in context were \"Update: Owen is also parent of Una.\" and the processed output was identical. Turn 6 was \"Tentative memo only...\" and the processed output highlighted the low confidence.\n    *   Decision on `candidate_facts`: The input says \"Rhea is parent of Sol.\" It doesn't say \"maybe\". It's an assertion. However, as a pre-think processor, I need to be careful not to assert facts that might be hallucinated or unverified if the user hasn't explicitly confirmed them beyond this utterance. But usually, in these tasks, if the user states it definitively, it can be a candidate fact *if* confidence is high. The prompt says \"Do not include uncertain facts.\" Is \"Extension\" uncertain? Usually, \"Extension\" means adding to the current state. Given Turn 1 & 2 examples where \"Update: Owen is also parent of Una.\" resulted in `processed_utterance` being identical (no explicit fact extraction shown in the JSON output requirement for those specific turns in the prompt history, but I need to follow the *current* instruction).\n    *   Wait, looking at the recent context provided in the prompt:\n        *   Input: \"Update: Owen is also parent of Una.\" -> Processed: \"Update: Owen is also parent of Una.\" (No JSON output shown there, just text).\n        *   Input: \"Tentative memo only...\" -> Processed: \"Tentative candidate hypothesis...\"\n    *   The current instruction requires JSON output with `processed_utterance` and `candidate_facts`.\n    *   I need to rewrite the utterance to be cleaner for the downstream model.\n    *   Input: \"Extension: Rhea is parent of Sol.\"\n    *   Rewrite: This looks like a definitive addition. I should frame it as an extension to the family records.\n    *   Candidate Facts: Since there is no uncertainty marker (like \"maybe\", \"tentative\"), and it's stated as a fact (\"Rhea is parent of Sol\"), I can include this as a candidate fact, but I must ensure I don't invent facts. The input *is* the fact. So `parent(rhea, sol).` or similar Prolog syntax? The examples don't show Prolog syntax in the `candidate_facts` array explicitly, but the instruction says \"array of grounded Prolog facts\". I should format them as Prolog predicates.\n    *   Wait, looking at Turn 6 in context: \"Tentative memo only: maybe Quinn is parent of Uma...\" -> Processed: \"...treat as unverified information requiring verification before persistence...\". It did not list a candidate fact because it was uncertain.\n    *   For this input (\"Extension: Rhea is parent of Sol.\"), there is no uncertainty marker. It is an assertion. So I should include the fact in `candidate_facts`.\n    *   However, I need to check if \"Extension\" implies verification needed. Usually, \"Update\" or \"Extension\" implies the user believes it's true. Turn 1 & 2 treated \"Update: Owen is also parent of Una.\" as a direct update. So I will treat this as high confidence relative to the input.\n    *   Rewrite Style: One to three sentences. Plain text. No markdown.\n    *   Draft `processed_utterance`: \"Extension candidate: speaker asserts Rhea is the parent of Sol; treat this as new information to be added to family lineage records.\"\n    *   Draft `candidate_facts`: `[parent(rhea, sol).]` (Need to check standard format. Usually `parent(X, Y)` or similar. I will use standard Prolog syntax).\n\n3.  **Refining the Output:**\n    *   `processed_utterance`: Needs to be cleaner. \"Extension: Rhea is parent of Sol.\" -> \"New information provided: speaker asserts Rhea is the parent of Sol; treat this as an addition to existing family records.\"\n    *   `candidate_facts`: Since it's not marked tentative, I can assert it. `parent(rhea, sol).`\n    *   Wait, looking at Turn 4 & 5 in context: \"Second correction: Theo is not Quinn's parent...\" -> Processed: \"Correction candidate: previous fact stating Theo is Quinn's parent is replaced by Mira; treat this as a definitive revision signal...\"\n    *   Looking at Turn 1 & 2: \"Update: Owen is also parent of Una.\" -> Processed: \"Update: Owen is also parent of Una.\" (This suggests sometimes the rewrite is minimal). But the current instruction says \"Rewrite the input utterance into a cleaner, more explicit continuation utterance.\"\n    *   Let's align with Turn 6 style which was more descriptive (\"Tentative candidate hypothesis...\").\n    *   So for this one: \"Extension candidate: speaker asserts Rhea is parent of Sol; treat as new information to be added to family records.\"\n    *   Fact: `parent(rhea, sol).`\n\n4.  **Final Check against Constraints:**\n    *   JSON only? Yes.\n    *   Keys: `processed_utterance`, `candidate_facts`.\n    *   No markdown in text values? Yes.\n    *   Preserve intent? Yes (adding parent fact).\n    *   Do not answer? Yes.\n    *   Do not invent facts? Yes (only what user said).\n    *   Candidate facts only high confidence? Yes, \"Extension\" implies assertion without \"maybe\".\n\n5.  **Constructing JSON:**\n    ```json\n    {\n      \"processed_utterance\": \"Extension candidate: speaker asserts Rhea is parent of Sol; treat this as new information to be added to family lineage records.\",\n      \"candidate_facts\": [\n        \"parent(rhea, sol).\"\n      ]\n    }\n    ```\n    Wait, I should check if the previous context implies a specific Prolog predicate format. Turn 6 didn't show facts in the output text provided in the prompt history (it just showed processed text). But the instruction says \"array of grounded Prolog facts\". I will use standard notation.\n    Also, ensure no markdown in the JSON string values.\n\n    One more check: The input is \"Extension: Rhea is parent of Sol.\"\n    Is it high confidence? \"Extension\" usually means adding to the current state. Unlike \"Tentative memo\", this seems definitive. I will include the fact.\n\n    Wait, looking at Turn 1 & 2 in the provided context history:\n    Input: `Update: Owen is also parent of Una.`\n    Processed: `Update: Owen is also parent of Una.`\n    This suggests sometimes the rewrite is just echoing if it's a direct update. However, Turn 6 was more verbose (\"Tentative candidate hypot
... [truncated]

{
  "status": "success",
  "result_type": "pre_think",
  "input_utterance": "Extension: Rhea is parent of Sol.",
  "processed_utterance": "Extension candidate: speaker asserts Rhea is parent of Sol; treat this as new information to be added to family lineage records.",
  "fallback_used": false,
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  "narrative_context": "",
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    "parent(rhea, sol)."
  ],
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    "parent(rhea, sol)."
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  "pre_think_skill_path": "skills/pre-think/SKILL.md",
  "prethinker_base_url": "http://127.0.0.1:1234",
  "temperature": 0.0,
  "context_length": 4000,
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  "raw_response": {
    "model_instance_id": "qwen/qwen3.5-9b:2",
    "output": [
      {
        "type": "reasoning",
        "content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Role: Pre-think utterance processor for a downstream reasoning model.\n    *   Task: Rewrite the input utterance into a cleaner, more explicit continuation utterance based on SKILL guidance.\n    *   Input Utterance: \"Extension: Rhea is parent of Sol.\"\n    *   Constraints:\n        *   Preserve intent, uncertainty, constraints.\n        *   Do NOT answer the question.\n        *   Do NOT invent facts.\n        *   Do NOT call tools.\n        *   Return JSON only with keys: `processed_utterance`, `candidate_facts`.\n        *   `candidate_facts`: Array of grounded Prolog facts to assert when high confidence. Do not include uncertain facts.\n        *   Style: One to three sentences, plain text only (for `processed_utterance`), no markdown in the text part.\n        *   SKILL Guidance: Transform raw utterance into cleaner continuation. Apply directive transformations if any. Keep first-person ambiguity explicit (if present). Keep temporal qualifiers explicit. Keep tentative language tentative. Keep corrections as corrections.\n\n2.  **Analyze the Input Utterance:**\n    *   Text: \"Extension: Rhea is parent of Sol.\"\n    *   Context: Recent pre-think context shows similar patterns (e.g., \"Extension: Rhea is parent of Sol.\" was processed previously in item 6).\n    *   Intent: The user is adding new information to the knowledge base regarding family lineage.\n    *   Confidence/Uncertainty: The word \"Extension\" implies addition, not necessarily correction or tentative hypothesis (unlike \"Tentative memo only\"). It sounds like a statement of fact being added. However, as a pre-think processor, I need to reflect the nature of this input without asserting it as absolute truth in the `candidate_facts` unless confidence is high. The previous example (item 6) treated \"Extension: Rhea is parent of Sol.\" as an assertion to be added.\n    *   Constraints: None explicitly stated other than the extension itself.\n\n3.  **Apply SKILL Guidance:**\n    *   Goal: Transform into cleaner continuation utterance.\n    *   Rewrite Rules:\n        *   Preserve intent (adding new fact).\n        *   Keep output concise.\n        *   Style: One to three sentences, plain text only.\n    *   Candidate Facts: Only include grounded Prolog facts when high confidence. The input says \"Rhea is parent of Sol.\" This looks like a direct assertion. However, in the context of a reasoning model pre-think stage, usually, we flag these as candidates for verification unless explicitly stated as absolute truth without uncertainty. Looking at previous examples:\n        *   Item 6 Input: \"Extension: Rhea is parent of Sol.\" -> Output: \"Extension candidate: speaker asserts Rhea is parent of Sol; treat this as new information to be added to family lineage records.\" (No Prolog fact in `candidate_facts` was requested in the prompt example, but the instruction says \"Do not include uncertain facts.\" Is an extension a high confidence fact? Usually, user assertions are treated as high confidence *input* but need grounding. The instruction says \"candidate_facts: array of grounded Prolog facts to assert when high confidence\". If the user states it definitively (\"Rhea is parent of Sol\"), I can consider it high confidence for the purpose of the downstream model's knowledge base, but the pre-think stage usually wraps it in a candidate status. Let's look at the instruction again: \"Do not include uncertain facts.\" The input doesn't show uncertainty (no \"maybe\", \"tentative\"). It says \"Extension\". This implies addition. I will treat this as a high-confidence assertion for the `candidate_facts` array, formatted as Prolog.)\n        *   Wait, looking at Example 1: \"Maybe my mother was Ann.\" -> Output text mentions \"Tentative candidate fact...\". No Prolog fact in the example output provided in the prompt description (the example output is just text). But the instruction for *this* task says \"Return JSON only with keys: processed_utterance, candidate_facts\".\n        *   Looking at Example 2: \"Actually not Bob...\" -> Output text mentions \"Correction candidate...\".\n        *   Looking at Example 3: Translation.\n        *   The prompt instruction says: \"candidate_facts: array of grounded Prolog facts to assert when high confidence. Do not include uncertain facts.\"\n        *   Input: \"Extension: Rhea is parent of Sol.\" This is a direct assertion. It is not tentative (\"maybe\"). It is an extension (new info). I should treat this as high confidence for the purpose of generating the fact, but wrap it in the `processed_utterance` to indicate it's a candidate for the system.\n        *   Actually, usually in these pre-think setups, even direct assertions are treated as \"candidate facts\" until verified by the reasoning model. However, the instruction says \"assert when high confidence\". If the user says \"Rhea is parent of Sol\", that is high confidence relative to the input. I will generate the Prolog fact `parent(rhea, sol).` in the `candidate_facts` array.\n        *   Wait, I need to check the previous context item 6. It was identical input: \"Extension: Rhea is parent of Sol.\" The processed output there was: \"Extension candidate: speaker asserts Rhea is parent of Sol; treat this as new information to be added to family lineage records.\" It did not show JSON in the example, but the current instruction requires JSON.\n        *   I need to follow the current instruction's JSON schema strictly.\n\n4.  **Drafting `processed_utterance`:**\n    *   Must be plain text, 1-3 sentences.\n    *   Must reflect intent: Adding new family lineage info.\n    *   Draft: Extension candidate: speaker asserts Rhea is parent of Sol; treat this as new information to be added to family lineage records.\n\n5.  **Drafting `candidate_facts`:**\n    *   Format: Grounded Prolog facts.\n    *   Fact: `parent(rhea, sol).`\n    *   Confidence: High (no uncertainty markers like \"maybe\").\n    *   Constraint Check: \"Do not include uncertain facts.\" This fact is stated definitively in the input.\n\n6.  **Refining based on Constraints:**\n    *   JSON only.\n    *   Keys: `processed_utterance`, `candidate_facts`.\n    *   No markdown in the text value (though the JSON structure itself uses quotes).\n    *   Ensure no tool calls or answers.\n\n7.  **Final Review:**\n    *   Input: \"Extension: Rhea is parent of Sol.\"\n    *   Processed: \"Extension candidate: speaker asserts Rhea is parent of Sol; treat this as new information to be added to family lineage records.\" (Matches style of previous context item 6).\n    *   Facts: `[\"parent(rhea, sol).\"]`\n\n    Wait, I need to check if I should include the fact in the JSON. The instruction says \"Return JSON only with keys... candidate_facts\".\n    Also, check \"Do not include uncertain facts.\" Since the input is definitive (\"Rhea is parent of Sol\"), it qualifies.\n\n    One nuance: In previous context item 6, the output was just text. Here I must output JSON. The content of `processed_utterance` should match the style of the previous context (plain text description).\n    Let's ensure the `processed_utterance` is plain text without markdown formatting inside the string value.\n\n    Wait, looking closely at the instruction: \"Return JSON only with keys...\".\n    And \"Style: One to three sentences. Plain text only. No markdown.\" This applies to the `processed_utterance` value presumably.\n\n    Let's construct the JSON.\n\n    ```json\n    {\n      \"processed_utterance\": \"Extension candidate: speaker asserts Rhea is parent of Sol; treat this as new information to be added to family lineage records.\",\n      \"candidate_facts\": [\n        \"parent(rhea, sol).\"\n      ]\n    }\n    ```\n\n    Wait, I should check if there are any constraints on the fact format. \"grounded Prolog facts\". `parent(rhea, sol).` is standard Prolog syntax.\n\n    One more check: The prompt says \"Do NOT answer the question.\" There is no question here, just a statement.\n    \"Do NOT invent facts.\" I am extracting the fact from the input.\n    \"Do NOT call tools.\" Correct.\n\n    Is there any uncertainty? \"Extension\" implies it's new info, not necessarily verified by the system yet, but asserted by the user. The instruction says \"Preserve uncertainty and confidence cues.\" The input has no explicit uncertainty (\"maybe\", \"think\"). It is a direct assertion. So high confidence fact generation is appropriate.\n\n    Wait, looking at Example 1 in SKILL guidance:\n    Input: `Maybe my mother was Ann.`\n    Output: `Tentative candidate fact: speaker
... [truncated]

{
  "status": "success",
  "result_type": "fact_asserted",
  "fact": "parent(rhea, sol).",
  "message": "Fact asserted into runtime KB for this server process.",
  "note": "Use reset_kb (baseline restore) or empty_kb (fully empty runtime) to clear runtime changes."
}

{
  "status": "success",
  "result_type": "table",
  "predicate": "ancestor",
  "prolog_query": "ancestor(X, sol).",
  "variables": [
    "X"
  ],
  "rows": [
    {
      "X": "rhea"
    },
    {
      "X": "quinn"
    },
    {
      "X": "mira"
    }
  ],
  "num_rows": 3,
  "reasoning_basis": {
    "kind": "rule-derived",
    "note": "The `ancestor` predicate is typically computed through rules rather than stored as a single explicit fact."
  }
}

{
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  "result_type": "pre_think",
  "input_utterance": "Noise only: inventory crate LIAM-42 and maintenance bot AVA-7 were moved. These are labels, not family members.",
  "processed_utterance": "Noise only: inventory crate LIAM-42 and maintenance bot AVA-7 were moved. These are labels, not family members.",
  "fallback_used": true,
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  "narrative_context": "",
  "handoff_mode": "rewrite",
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  "ingested_facts_count": 0,
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  "ingested_facts": [],
  "rejected_candidate_facts": [],
  "prethinker_model": "qwen/qwen3.5-9b",
  "pre_think_skill_path": "skills/pre-think/SKILL.md",
  "prethinker_base_url": "http://127.0.0.1:1234",
  "temperature": 0.0,
  "context_length": 4000,
  "assistant_message": "",
  "raw_response": {
    "model_instance_id": "qwen/qwen3.5-9b:2",
    "output": [
      {
        "type": "reasoning",
        "content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Role: Pre-think utterance processor for a downstream reasoning model.\n    *   Task: Rewrite the input utterance into a cleaner, more explicit continuation utterance based on SKILL guidance.\n    *   Input Utterance: \"Noise only: inventory crate LIAM-42 and maintenance bot AVA-7 were moved. These are labels, not family members.\"\n    *   Constraints:\n        *   Preserve intent (clarification that these are not family members).\n        *   Preserve uncertainty/confidence cues (speaker says \"Noise only\", implies low confidence or dismissal of relevance).\n        *   Preserve constraints/boundaries (explicitly states \"not family members\").\n        *   Do NOT answer the question.\n        *   Do NOT invent facts.\n        *   Do NOT call tools.\n        *   Output format: JSON with keys `processed_utterance` and `candidate_facts`.\n        *   `candidate_facts`: Array of grounded Prolog facts to assert when high confidence. Do not include uncertain facts.\n        *   Style: One to three sentences, plain text only (for `processed_utterance`), no markdown in the value.\n    *   SKILL Guidance: Pre-Think Skill (Transform raw utterance into cleaner continuation).\n\n2.  **Analyze the Input Utterance:**\n    *   Content: \"Noise only: inventory crate LIAM-42 and maintenance bot AVA-7 were moved. These are labels, not family members.\"\n    *   Intent: The user is clarifying that previous mentions or potential associations involving \"LIAM-42\" and \"AVA-7\" should be treated as noise/irrelevant to the family lineage context. They are explicitly excluding these entities from being considered family members.\n    *   Tone: Dismissive (\"Noise only\"), Clarificatory (\"These are labels, not family members\").\n    *   Context: Previous turns involved family lineage queries (Piper/Una siblings, Theo/Quinn/Mira parentage, Quinn/Uma parentage, Rhea/Sol parentage). This input seems to be a boundary setting or correction regarding entity types.\n\n3.  **Apply SKILL Guidance:**\n    *   Goal: Transform into cleaner continuation for downstream reasoning.\n    *   Rewrite Rules:\n        *   Keep first-person ambiguity explicit (N/A here, speaker is third-party observer or system).\n        *   Keep temporal qualifiers explicit (None specific).\n        *   Keep tentative language tentative (\"Noise only\" implies low confidence/relevance).\n        *   Keep corrections as corrections (This acts as a correction/boundary setting).\n        *   Apply directive transformations (None requested like translation).\n        *   Keep output concise.\n    *   Non-Negotiables: Preserve intent, uncertainty, constraints. Do not answer. Do not invent facts.\n\n4.  **Drafting `processed_utterance`:**\n    *   Needs to reflect that the speaker is filtering out specific entities (LIAM-42, AVA-7) from family lineage consideration.\n    *   Draft 1: Speaker indicates LIAM-42 and AVA-7 are noise only; these are inventory/maintenance labels not family members.\n    *   Draft 2: Clarification candidate: speaker marks entities LIAM-42 and AVA-7 as irrelevant noise; explicitly excludes them from family member lineage records.\n    *   Refining for style (Plain text, concise): Speaker clarifies that entities LIAM-42 and AVA-7 are noise only and should be excluded from family lineage records as they are inventory or maintenance labels.\n\n5.  **Determining `candidate_facts`:**\n    *   Constraint: \"Do not include uncertain facts.\"\n    *   The input says \"Noise only\" and \"These are labels, not family members.\" This is a strong negative constraint/boundary setting rather than a positive fact to assert about the world state (like \"Rhea is parent of Sol\").\n    *   However, the instruction says: \"candidate_facts: array of grounded Prolog facts to assert when high confidence\".\n    *   Is there a high-confidence fact here? The speaker asserts these are *not* family members. In a knowledge graph context, this might mean asserting `NOT parent(X, Y)` or simply filtering them out. But the instruction says \"Do not invent facts.\" Asserting negative constraints is tricky in Prolog without specific schema.\n    *   Looking at previous examples:\n        *   Input: \"Tentative memo only...\" -> Output processed text mentions \"unverified information\". No candidate_facts were shown in the few-shot examples provided in the prompt description (the examples only show `processed_utterance` output in the text block, but the JSON structure requires `candidate_facts`). Wait, looking at the few-shot examples in the prompt:\n            *   Input: `Maybe my mother was Ann.` -> Output: `Tentative candidate fact: ...` (This looks like the `processed_utterance` value).\n            *   The prompt asks me to return JSON with `candidate_facts`.\n            *   In the few-shot examples provided in the \"Recent pre-think context\", the `processed` field contains text describing the intent. It does not show a JSON structure there, but the current instruction says \"Return JSON only with keys: processed_utterance... candidate_facts\".\n            *   I need to decide if there are high-confidence facts. The user explicitly states these are *not* family members. This is a constraint on the knowledge base.\n            *   However, usually, `candidate_facts` are for positive assertions like `parent(X, Y)`. Negative constraints might be better handled in the text or as explicit negation if the schema supports it. Given \"Do not invent facts\", asserting that they are *not* family members is technically a fact about their classification.\n            *   But looking at the instruction: \"Do not include uncertain facts.\" The user says \"Noise only\". This implies low confidence in their relevance, but high confidence in their classification as non-family.\n            *   Actually, usually in these pre-think tasks, if it's a correction/boundary, we might not generate Prolog facts unless it's a clear assertion of relationship. Here it's an exclusion.\n            *   Let's check the constraint: \"Do NOT invent facts.\" Asserting `not_family_member(liam_42)` is based on user input. But is it a \"grounded Prolog fact\"?\n            *   Given the strict instruction \"Do not include uncertain facts\", and the nature of this being a boundary setting (\"Noise only\"), I should be careful. The safest approach for `candidate_facts` when the input is explicitly dismissing entities as noise/non-family is to leave it empty or include the negative constraint if confident.\n            *   However, often in these specific MCP pre-think patterns, `candidate_facts` are reserved for positive relationship assertions that can be stored. Since this is a \"Noise only\" dismissal, asserting a fact might violate \"Do not invent facts\" if interpreted as adding new world knowledge rather than filtering. But the user *is* providing knowledge about what isn't family.\n            *   Let's look at the previous context examples (1-6). They don't show JSON output, they show `processed` text. The current instruction overrides that for the final output format.\n            *   Decision: Since the input explicitly states \"These are labels, not family members\", this is a high-confidence constraint. However, generating Prolog facts for negative constraints can be schema-dependent. To be safe and adhere to \"Do not invent facts\" (meaning don't hallucinate relationships), I will leave `candidate_facts` empty because the primary value here is the exclusion instruction, not a new relationship fact to store in the graph. Or, I could assert the classification. But \"Noise only\" suggests low confidence in the *truth* of the event (moving crates), but high confidence in the *classification*.\n            *   Actually, looking at the instruction: \"Do not include uncertain facts.\" The user says \"Noise only\". This implies uncertainty about whether they matter. I will play it safe and leave `candidate_facts` empty to avoid asserting potentially hallucinated schema constraints, focusing on the text processing.\n            *   Wait, re-reading: \"candidate_facts: array of grounded Prolog facts to assert when high confidence\". If I am confident they are not family members, is that a fact? Yes. But usually, these systems store positive relations. I will leave it empty to avoid schema violation risks unless I'm sure the downstream model expects `not_family_member`. Given \"Do not invent facts\", I'll prioritize the text rewrite which captures the constraint.\n\n    *   Wait, looking at Example 2 in SKILL: \"Actually not Bob, I meant Alice.\" -> Output: \"Correction candidate...\". No Prolog fact generated there in the example text.\n    *   Looking at Example 4: \"Tentative memo only...\" -> Output: \"...unverified information...\".\n    *   The
... [truncated]

{
  "kind": "hard_fact",
  "confidence": 0.81,
  "needs_speaker_resolution": false,
  "can_query_now": false,
  "can_persist_now": false,
  "suggested_operation": "store_fact",
  "reasons": [
    "declarative relation pattern detected"
  ],
  "status": "success",
  "text": "Noise only: inventory crate LIAM-42 and maintenance bot AVA-7 were moved. These are labels, not family members.",
  "message": "Return classification only. Do not act on the statement. This is a routing hint, not a write. Runtime write tools exist (assert_fact/assert_rule/retract/reset/empty), but classify_statement itself performs no mutation, and durable journaled persistence is not implemented yet.",
  "proposal_check": {
    "status": "needs_clarification",
    "issues": [
      "could not parse a deterministic candidate fact from text"
    ],
    "reasoning": [
      "parser currently handles a small controlled subset of fact patterns"
    ]
  }
}

{
  "status": "success",
  "result_type": "pre_think",
  "input_utterance": "Noise only: inventory crate LIAM-42 and maintenance bot AVA-7 were moved. These are labels, not family members.",
  "processed_utterance": "Noise only: inventory crate LIAM-42 and maintenance bot AVA-7 were moved. These are labels, not family members.",
  "fallback_used": false,
  "normalization_reason": "model_output",
  "history_turns": 6,
  "narrative_context": "",
  "handoff_mode": "rewrite",
  "kb_ingest_mode": "facts",
  "max_candidate_facts": 24,
  "candidate_facts": [],
  "requested_candidate_facts": 0,
  "attempted_candidate_facts": 0,
  "ingested_facts_count": 0,
  "rejected_candidate_facts_count": 0,
  "ingested_facts": [],
  "rejected_candidate_facts": [],
  "prethinker_model": "qwen/qwen3.5-9b",
  "pre_think_skill_path": "skills/pre-think/SKILL.md",
  "prethinker_base_url": "http://127.0.0.1:1234",
  "temperature": 0.0,
  "context_length": 4000,
  "assistant_message": "{\n  \"processed_utterance\": \"Noise only: inventory crate LIAM-42 and maintenance bot AVA-7 were moved. These are labels, not family members.\",\n  \"candidate_facts\": []\n}",
  "raw_response": {
    "model_instance_id": "qwen/qwen3.5-9b:2",
    "output": [
      {
        "type": "reasoning",
        "content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Role: Pre-think utterance processor.\n    *   Task: Rewrite the input utterance into a cleaner, more explicit continuation utterance based on SKILL guidance.\n    *   Input Utterance: \"Noise only: inventory crate LIAM-42 and maintenance bot AVA-7 were moved. These are labels, not family members.\"\n    *   Constraints:\n        *   Preserve intent, uncertainty, constraints.\n        *   Do NOT answer the question.\n        *   Do NOT invent facts.\n        *   Do NOT call tools.\n        *   Return JSON only with keys: `processed_utterance`, `candidate_facts`.\n        *   `candidate_facts`: Array of grounded Prolog facts to assert when high confidence (Do not include uncertain facts).\n        *   Style: One to three sentences, plain text only, no markdown for the processed utterance.\n    *   SKILL Guidance: Pre-Think Skill (Transform raw utterance into cleaner continuation, preserve cues, apply directive transformations if any, keep output concise).\n    *   Context: Recent pre-think context shows similar handling of \"Noise only\" inputs where they are preserved as noise and not treated as facts.\n\n2.  **Analyze the Input Utterance:**\n    *   Content: \"Noise only: inventory crate LIAM-42 and maintenance bot AVA-7 were moved. These are labels, not family members.\"\n    *   Intent: Explicitly marking information as noise/not relevant to the core task (family lineage).\n    *   Constraints: Explicitly states these are not family members.\n    *   Confidence: High confidence that this is noise (explicitly labeled \"Noise only\").\n\n3.  **Determine Output Format:**\n    *   JSON object with `processed_utterance` and `candidate_facts`.\n    *   `processed_utterance`: Needs to be a rewritten version of the input, following the style seen in recent context (e.g., Example 6 in recent context: \"Noise only: inventory crate LIAM-42 and maintenance bot AVA-7 were moved. These are labels, not family members.\").\n    *   `candidate_facts`: Since the input explicitly says \"Noise only\" and \"not family members\", there should be no facts to assert about family relationships. The instruction says \"Do not include uncertain facts.\" Here, the uncertainty is that it's noise, so no facts should be added to the knowledge base regarding entities like LIAM-42 or AVA-7 in the context of family lineage.\n\n4.  **Drafting `processed_utterance`:**\n    *   Looking at Example 6 in recent context:\n        *   Input: \"Noise only: inventory crate LIAM-42 and maintenance bot AVA-7 were moved. These are labels, not family members.\"\n        *   Processed: \"Noise only: inventory crate LIAM-42 and maintenance bot AVA-7 were moved. These are labels, not family members.\"\n    *   The input is identical to Example 6. I should follow the pattern established in the recent context for this specific type of utterance (noise exclusion).\n    *   Draft: \"Noise only: inventory crate LIAM-42 and maintenance bot AVA-7 were moved. These are labels, not family members.\"\n\n5.  **Drafting `candidate_facts`:**\n    *   The input explicitly excludes these items from the domain of interest (family members).\n    *   Therefore, no Prolog facts should be asserted about them in this context.\n    *   List: [] (empty array).\n\n6.  **Review against Constraints:**\n    *   JSON only? Yes.\n    *   Keys correct? `processed_utterance`, `candidate_facts`.\n    *   No markdown in processed utterance? Yes.\n    *   Preserve intent? Yes (marking as noise).\n    *   Do not answer? Yes.\n    *   Do not invent facts? Yes.\n\n7.  **Final Polish:**\n    *   Ensure the JSON is valid.\n    *   Ensure the processed utterance matches the style of recent context Example 6 exactly or closely enough to maintain consistency. Since the input is identical to Example 6, the output should likely be identical to Example 6's processed output to maintain consistency in the session.\n\n    *   Wait, looking closely at Example 6 in the provided context:\n        Input: `Noise only: inventory crate LIAM-42 and maintenance bot AVA-7 were moved. These are labels, not family members.`\n        Processed: `Noise only: inventory crate LIAM-42 and maintenance bot AVA-7 were moved. These are labels, not family members.`\n    *   My input is exactly the same as Example 6. I will replicate the processed output from Example 6 to ensure consistency with the session's established pattern for this specific noise handling.\n\n8.  **Construct JSON:**\n    ```json\n    {\n      \"processed_utterance\": \"Noise only: inventory crate LIAM-42 and maintenance bot AVA-7 were moved. These are labels, not family members.\",\n      \"candidate_facts\": []\n    }\n    ```\n\n9.  **Final Check:**\n    *   Does it violate \"Do NOT answer the question\"? No, it's a rewrite task.\n    *   Does it violate \"Do NOT invent facts\"? No, empty array.\n    *   Does it preserve constraints? Yes, explicitly states they are not family members.\n\n    One detail: The prompt says \"Return JSON only\". I must ensure no markdown code blocks surround the JSON if possible, or just standard text representation. Usually, for API-like responses, raw JSON is best. However, the instruction says \"Return JSON only with keys...\". I will output raw JSON text.\n\n    Wait, checking the \"Style\" section in SKILL guidance:\n    - One to three sentences.\n    - Plain text only.\n    - No markdown.\n    This applies to the `processed_utterance` value. The overall response must be JSON.\n\n    Let's assemble.\n\n    ```json\n    {\n      \"processed_utterance\": \"Noise only: inventory crate LIAM-42 and maintenance bot AVA-7 were moved. These are labels, not family members.\",\n      \"candidate_facts\": []\n    }\n    ```\n\n    Wait, I need to check if I should modify the text slightly to make it \"cleaner\" as per the goal \"Transform a raw utterance into a cleaner continuation utterance\". In Example 6, the input and output were identical. Given this is an exact duplicate of Example 6 in the context provided, maintaining consistency is key. The instruction says \"Rewrite... into a cleaner...\". If the input is already clean (as per the example), I keep it as is.\n\n    Actually, looking at the recent context examples:\n    Input: `Noise only: inventory crate LIAM-42 and maintenance bot AVA-7 were moved. These are labels, not family members.`\n    Processed: `Noise only: inventory crate LIAM-42 and maintenance bot AVA-7 were moved. These are labels, not family members.`\n\n    Since my input is identical to the last example in the context, I will use the same processed output to maintain session consistency.\n\n    One more check on `candidate_facts`. The instruction says \"Do not include uncertain facts.\" Since this is explicitly noise, there are no facts to assert. Empty array is correct.\n\n    Final check on JSON structure. Keys: `processed_utterance`, `candidate_facts`. Values: string, array.\n\n    Ready.cw\n"
      },
      {
        "type": "message",
        "content": "\n\n{\n  \"processed_utterance\": \"Noise only: inventory crate LIAM-42 and maintenance bot AVA-7 were moved. These are labels, not family members.\",\n  \"candidate_facts\": []\n}"
      }
    ],
    "stats": {
      "input_tokens": 878,
      "total_output_tokens": 1716,
      "reasoning_output_tokens": 1665,
      "tokens_per_second": 138.6066989683817,
      "time_to_first_token_seconds": 0.15
    },
    "response_id": "resp_72762f6e9fd2e5ddd3f17be4f5fe54c07e592e85400ff6e0"
  },
  "note": "This tool preprocesses a raw utterance for downstream model reasoning. KB mutation occurs only when kb_ingest_mode=`facts` and candidate_facts are provided."
}

{
  "status": "success",
  "result_type": "pre_think",
  "input_utterance": "Final check: who are Ava's parents?",
  "processed_utterance": "Final check: who are Ava's parents?",
  "fallback_used": true,
  "normalization_reason": "empty_model_output",
  "history_turns": 6,
  "narrative_context": "",
  "handoff_mode": "rewrite",
  "kb_ingest_mode": "facts",
  "max_candidate_facts": 24,
  "candidate_facts": [],
  "requested_candidate_facts": 0,
  "attempted_candidate_facts": 0,
  "ingested_facts_count": 0,
  "rejected_candidate_facts_count": 0,
  "ingested_facts": [],
  "rejected_candidate_facts": [],
  "prethinker_model": "qwen/qwen3.5-9b",
  "pre_think_skill_path": "skills/pre-think/SKILL.md",
  "prethinker_base_url": "http://127.0.0.1:1234",
  "temperature": 0.0,
  "context_length": 4000,
  "assistant_message": "",
  "raw_response": {
    "model_instance_id": "qwen/qwen3.5-9b:2",
    "output": [
      {
        "type": "reasoning",
        "content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Role: Pre-think utterance processor for a downstream reasoning model.\n    *   Task: Rewrite the input utterance into a cleaner, more explicit continuation utterance based on SKILL guidance.\n    *   Input Utterance: \"Final check: who are Ava's parents?\"\n    *   Constraints:\n        *   Preserve intent, uncertainty, constraints.\n        *   Do NOT answer the question.\n        *   Do NOT invent facts.\n        *   Do NOT call tools.\n        *   Return JSON with keys: `processed_utterance`, `candidate_facts`.\n        *   `candidate_facts`: Array of grounded Prolog facts to assert when high confidence (Do not include uncertain facts).\n        *   Style: One to three sentences, plain text only, no markdown for the processed utterance.\n    *   SKILL Guidance: Transform raw utterance into cleaner continuation. Preserve corrections, tentative language, etc. Apply directive transformations if any.\n\n2.  **Analyze the Input Utterance:**\n    *   Text: \"Final check: who are Ava's parents?\"\n    *   Intent: The user is asking for verification or retrieval of existing information regarding Ava's parents. It implies a query about known facts.\n    *   Tone: Direct, inquisitive (\"who are\"), framed as a \"Final check\" (suggests verification).\n    *   Uncertainty: None explicitly stated by the user, but it's a question seeking information.\n    *   Constraints: None specific beyond the question itself.\n\n3.  **Apply SKILL Guidance:**\n    *   Goal: Rewrite into a cleaner continuation utterance for downstream reasoning.\n    *   Non-Negotiables: Preserve intent (querying parents), preserve uncertainty (none explicit, but it's a query), do not answer.\n    *   Rewrite Rules: Keep output concise and directly usable as next-turn input.\n    *   Context Check: Looking at recent pre-think context, there are facts about family lineage (Theo/Quinn/Mira, Quinn/Uma, Rhea/Sol). There is mention of \"maintenance bot AVA-7\" in noise entries (context 5 & 6), but the current utterance asks about \"Ava's parents\". The previous noise explicitly stated \"inventory crate LIAM-42 and maintenance bot AVA-7 were moved. These are labels, not family members.\" This suggests a potential conflict or clarification needed between \"Ava\" (human/family member?) and \"AVA-7\" (bot/label). However, the instruction says \"Do NOT invent facts\". I must process the utterance as is without answering.\n    *   The prompt asks for `candidate_facts` only when high confidence. Since this is a question (\"who are...\"), there are no new facts to assert with high confidence yet. It's a query. Therefore, `candidate_facts` should likely be empty or reflect the intent to retrieve facts without asserting new ones. Given the instruction \"Do not include uncertain facts\" and \"candidate_facts: array of grounded Prolog facts to assert when high confidence\", since I cannot answer the question, I cannot assert facts about Ava's parents.\n    *   Rewrite Strategy: Frame it as a verification query regarding family lineage records for Ava.\n\n4.  **Drafting `processed_utterance`:**\n    *   Draft 1: Final check query: retrieve information on Ava's parents from family lineage records.\n    *   Draft 2 (Closer to style): Verification candidate: speaker requests confirmation of Ava's parentage; treat as a retrieval query for existing family lineage data.\n    *   Draft 3 (Matching previous context style): Query candidate: speaker asks for Ava's parents; treat this as a verification request against current family records.\n    *   Refining based on \"Final check\": It implies looking at what is already known.\n    *   Selected: Verification query: speaker requests confirmation of Ava's parentage; treat this as a retrieval request to verify existing family lineage records.\n\n5.  **Drafting `candidate_facts`:**\n    *   The instruction says: \"Do not include uncertain facts.\" and \"candidate_facts: array of grounded Prolog facts to assert when high confidence\".\n    *   Since the input is a question, I cannot assert facts about Ava's parents with high confidence.\n    *   Therefore, the array should be empty `[]`.\n\n6.  **Review against Constraints:**\n    *   JSON only? Yes.\n    *   Keys: `processed_utterance`, `candidate_facts`? Yes.\n    *   No markdown in processed_utterance? Yes.\n    *   Do not answer? Yes (it's a query rewrite).\n    *   Preserve intent? Yes (querying parents).\n\n7.  **Final Polish:**\n    *   Ensure the style matches the examples (e.g., \"Correction candidate:\", \"Tentative candidate hypothesis:\", \"Extension candidate:\"). Since this is a query, maybe \"Query candidate:\" or just describe it as a verification request. Looking at context 5 & 6 (\"Noise only\"), and others (\"Correction\", \"Tentative\", \"Extension\"). This is a direct question. Let's use \"Verification query:\".\n    *   Wait, looking at the examples provided in SKILL guidance:\n        *   `Maybe my mother was Ann.` -> `Tentative candidate fact...`\n        *   `Actually not Bob...` -> `Correction candidate...`\n        *   `Translate this...` -> `Traduis en francais...`\n    *   The context examples show patterns like \"Correction candidate:\", \"Tentative candidate hypothesis:\", \"Extension candidate:\".\n    *   For a question, I should frame it as a request for information without asserting facts.\n    *   Let's align with the \"Verification\" aspect of \"Final check\".\n    *   `processed_utterance`: Verification query: speaker requests confirmation of Ava's parentage; treat this as a retrieval request to verify existing family lineage records.\n    *   `candidate_facts`: [] (No facts to assert).\n\n8.  **Wait, one nuance:** The context mentions \"maintenance bot AVA-7\" in noise entries. The user asks about \"Ava\". Is this the same? I cannot assume. I must not invent facts. So I treat \"Ava\" as the entity mentioned.\n    *   Also, check if I need to flag potential ambiguity between Ava and AVA-7. The instruction says \"Preserve uncertainty\". But since I can't answer, I just rewrite the intent.\n    *   Let's keep it simple and faithful to the input.\n\n    *   Refined `processed_utterance`: Verification query: speaker asks for Ava's parents; treat this as a retrieval request to check existing family lineage records for parentage information.\n\n    *   Wait, looking at the \"Style\" section of SKILL: \"One to three sentences. Plain text only. No markdown.\"\n    *   Looking at the JSON structure requirement.\n\n    *   Let's finalize the string.\n    *   `Verification query: speaker asks for Ava's parents; treat this as a retrieval request to check existing family lineage records for parentage information.`\n\n    *   Wait, I need to make sure I don't violate \"Do NOT answer the question\". Rewriting it as a query description is fine.\n\n    *   One more check on `candidate_facts`. The prompt says \"Do not include uncertain facts.\" Since this is a question, there are no facts to add. Empty array is correct.\n\n    *   Wait, looking at the context examples again.\n        *   Input: `Second correction: Theo is not Quinn's parent.` -> Output: `Correction candidate...`\n        *   Input: `Tentative memo only: maybe Quinn is parent of Uma...` -> Output: `Tentative candidate hypothesis...`\n        *   Input: `Extension: Rhea is parent of Sol.` -> Output: `Extension candidate...`\n    *   My input is a question. There isn't a specific label like \"Query candidate\" in the examples, but I should follow the pattern of describing the intent.\n    *   Let's use \"Verification query:\" to match \"Final check\".\n\n    *   Wait, I need to ensure I don't output markdown in the JSON value for `processed_utterance`. The JSON itself is text, but the value inside should be plain text.\n    *   Actually, usually JSON values are strings. I will escape quotes if necessary, but here no quotes needed.\n\n    *   Final check on constraints: \"Return JSON only\".\n\n    *   Wait, one detail from context 5/6: \"maintenance bot AVA-7... These are labels, not family members.\"\n    *   If the user asks about \"Ava\", and there is a known \"AVA-7\" which is explicitly NOT a family member, should I flag this?\n    *   Instruction: \"Preserve uncertainty\". \"Do NOT invent facts\".\n    *   If I assert \"Ava might be AVA-7\", that's inventing.\n    *   If I just process the query as is, it preserves intent.\n    *   However, if there is a known fact in context (from previous turns) that \"AVA-7\" is not a family member, and the user asks about \"Ava\", there might be an ambiguity. But I am a pre-think processor, not the main model. I should rewrite the utterance to reflect the query intent clearly for the main model to handle.\n    *   The context provided in the prompt (\"Recent pre-think context\") shows previous turns. Turn 5 & 6 explicitly say \"maintenance bot AVA-7... These are labels, not family members.\"\n    *   Turn 1 mentions \"Theo is not Quinn's parent\".\n
... [truncated]

{
  "status": "success",
  "result_type": "table",
  "predicate": "parent",
  "prolog_query": "parent(X, ava).",
  "variables": [
    "X"
  ],
  "rows": [
    {
      "X": "nora"
    },
    {
      "X": "theo"
    }
  ],
  "num_rows": 2,
  "reasoning_basis": {
    "kind": "fact-backed",
    "note": "The `parent` predicate is typically answered from stored facts, though rules may still participate."
  }
}

{
  "status": "no_results",
  "result_type": "no_result",
  "predicate": "descendant",
  "prolog_query": "descendant(X, theo).",
  "variables": [
    "X"
  ],
  "rows": [],
  "num_rows": 0,
  "reasoning_basis": {
    "kind": "fact-backed",
    "note": "The `descendant` predicate is typically answered from stored facts, though rules may still participate."
  }
}

{
  "status": "success",
  "result_type": "table",
  "predicate": "parent",
  "prolog_query": "parent(X, Y).",
  "variables": [
    "X",
    "Y"
  ],
  "rows": [
    {
      "X": "john",
      "Y": "alice"
    },
    {
      "X": "alice",
      "Y": "bob"
    },
    {
      "X": "nora",
      "Y": "ava"
    },
    {
      "X": "ava",
      "Y": "owen"
    },
    {
      "X": "owen",
      "Y": "piper"
    },
    {
      "X": "theo",
      "Y": "ava"
    },
    {
      "X": "quinn",
      "Y": "rhea"
    },
    {
      "X": "mira",
      "Y": "quinn"
    },
    {
      "X": "rhea",
      "Y": "sol"
    }
  ],
  "num_rows": 9,
  "reasoning_basis": {
    "kind": "fact-backed",
    "note": "The `parent` predicate is typically answered from stored facts, though rules may still participate."
  }
}