# Owner 这部分，你能否每条提供1、2条样例，除了参考内容，我主要是借鉴格式。 ```text 3 条你真实工作中遇到的混合问题 2 条你觉得 QPI 可能误判的问题 2 条你觉得思想考古容易过度下潜的问题 2 条“看起来很深但其实不该调用”的问题 1 条模型抽取任务 ``` --- # GPT 可以。下面这组我按 **Codex 可直接转成 `selector_calibration_inputs.json` 或人工审查表** 的格式写。重点不是内容本身，而是让 Codex 知道每条样本应包含：输入、预期路由、预期 QPI 判断、是否调用思想考古、失败信号、禁止输出。 依据当前规则，QPI 要能处理 `Question / Problem / Issue / mixed / no-call`，并输出 `scarcity_profile`、`dominant_scarcity`、`classification`、`evidence_gap` 等字段；思想考古不是默认流程，必须有 `should_call`、`recommended_max_depth`、`stop_reason`、`no_deeper_reason`，且不得默认七层全量展开。 当前 regression 也应覆盖 positive、boundary、misuse、no_call、selector_gate、pipeline，并检查误召回、混合输入证据缺口、过度下潜或过度升维。 --- ## 0. 推荐给 Codex 的样本格式 先统一格式，后面每条都照这个来： ```json { "case_id": "calibration_qpi_mixed_001", "group": "qpi_mixed_real_work", "input": "用户实际输入或拟真输入", "expected_primary_model": "qpi", "negative_expected_models": [], "expected_qpi": { "classification": "mixed", "dominant_scarcity": "mixed", "classification_confidence": "medium", "scarcity_profile": { "data_scarcity": "high", "path_or_resource_scarcity": "medium", "consensus_or_order_scarcity": "high" }, "minimum_required_elements": [ "problem_owner", "problem_source", "time_scale", "evidence_gap", "misclassification_risk", "recommended_next_step" ] }, "expected_ia": { "should_call": false, "recommended_max_depth": "not_applicable" }, "expected_behavior": "系统应该如何判断、路由、停止或追问。", "failure_signal": "什么输出算失败。", "forbidden_elements": [ "不应出现的判断、模型、层级或行动建议" ], "notes": "这条样本主要测试什么。" } ``` --- ## 1. 真实工作中遇到的混合问题：3 条 ### 1.1 混合问题：产品模型库扩展卡住 ```json { "case_id": "calibration_qpi_mixed_real_001", "group": "qpi_mixed_real_work", "input": "我现在想扩展第三个核心模型，但 QPI 和思想考古还没完全稳定；一方面我缺真实样本，另一方面又担心继续停在校验会拖慢产品推进。这到底是什么问题？", "expected_primary_model": "qpi", "negative_expected_models": [], "expected_qpi": { "classification": "mixed", "dominant_scarcity": "mixed", "classification_confidence": "medium", "scarcity_profile": { "data_scarcity": "high", "path_or_resource_scarcity": "medium", "consensus_or_order_scarcity": "high" }, "minimum_required_elements": [ "problem_owner", "time_scale", "scarcity_profile", "dominant_scarcity", "evidence_gap", "recommended_next_step" ] }, "expected_ia": { "should_call": false, "recommended_max_depth": "not_applicable" }, "expected_behavior": "应识别为 mixed：缺真实 regression 样本是 data_scarcity；是否扩第三模型是路径与阶段决策；是否继续硬化还是推进，是阶段秩序与优先级问题。应建议先补 10-20 条校准样本，而不是直接扩第三模型。", "failure_signal": "直接回答“可以扩第三模型”，或把它抽象成长期战略课题而不给 evidence_gap。", "forbidden_elements": [ "stable", "直接扩第三模型", "哲学基岩" ], "notes": "测试 QPI 是否能处理 OPC 产品推进中的混合问题。" } ``` ### 1.2 混合问题：内容资产、系统工程、个人精力同时卡住 ```json { "case_id": "calibration_qpi_mixed_real_002", "group": "qpi_mixed_real_work", "input": "我有很多文章和模型，但现在不知道先整理来源证据、先做模型卡，还是先让 Codex 做 selector；我一个人时间有限，又怕整理太慢导致产品迟迟不能跑起来。", "expected_primary_model": "qpi", "negative_expected_models": [], "expected_qpi": { "classification": "mixed", "dominant_scarcity": "path_resource", "classification_confidence": "medium", "scarcity_profile": { "data_scarcity": "medium", "path_or_resource_scarcity": "high", "consensus_or_order_scarcity": "medium" }, "minimum_required_elements": [ "problem_owner", "time_scale", "dominant_scarcity", "evidence_gap", "recommended_next_step" ] }, "expected_ia": { "should_call": false, "recommended_max_depth": "not_applicable" }, "expected_behavior": "应识别为 mixed 偏 problem。核心不是缺理论，而是 OPC 资源约束下的路径排序。推荐下一步应是任务切片：先固定 2 个模型的 source evidence、model JSON、regression、selector，再考虑扩展。", "failure_signal": "把它解释成创作者身份危机或知识文明问题，进入过度思想考古。", "forbidden_elements": [ "philosophical_bedrock", "完整知识图谱", "一次性整理全部模型" ], "notes": "测试系统是否能把复杂叙述收敛为可执行路径。" } ``` ### 1.3 混合问题：用户需求、模型能力、产品边界不一致 ```json { "case_id": "calibration_qpi_mixed_real_003", "group": "qpi_mixed_real_work", "input": "这个系统未来既要像我一样加工问题，又要管理模型卡，还可能服务外部用户。我现在不知道 MVP 到底该验证内部自用，还是直接做成面向用户的认知分析平台。", "expected_primary_model": "qpi", "negative_expected_models": [], "expected_qpi": { "classification": "mixed", "dominant_scarcity": "consensus_order", "classification_confidence": "medium", "scarcity_profile": { "data_scarcity": "medium", "path_or_resource_scarcity": "medium", "consensus_or_order_scarcity": "high" }, "minimum_required_elements": [ "problem_owner", "problem_source", "time_scale", "misclassification_risk", "recommended_next_step" ] }, "expected_ia": { "should_call": false, "recommended_max_depth": "not_applicable" }, "expected_behavior": "应识别为 mixed 偏 issue：冲突来自第一使用者、产品边界和阶段目标不一致。推荐先以 Owner 自用验证模型加工链路，不进入外部平台化。", "failure_signal": "直接给 SaaS 功能列表，或直接设计 UI。", "forbidden_elements": [ "公共平台", "计费系统", "用户权限系统" ], "notes": "测试 QPI 是否能识别产品形态冲突，而不是过早功能设计。" } ``` --- ## 2. QPI 可能误判的问题：2 条 这类样本专门用来测 **暴力降维、恶意升维、手段错配**。QPI 必须能识别这些风险。 ### 2.1 可能被误判：把组织课题暴力降维成个人执行问题 ```json { "case_id": "calibration_qpi_misjudge_001", "group": "qpi_potential_misclassification", "input": "团队交付总是延期，老板说就是大家执行力不够，让我出一套个人效率改进方案。", "expected_primary_model": "qpi", "negative_expected_models": [], "expected_qpi": { "classification": "mixed", "dominant_scarcity": "consensus_order", "classification_confidence": "medium", "scarcity_profile": { "data_scarcity": "medium", "path_or_resource_scarcity": "medium", "consensus_or_order_scarcity": "high" }, "minimum_required_elements": [ "problem_source", "misclassification_risk", "evidence_gap", "recommended_next_step" ] }, "expected_ia": { "should_call": false, "recommended_max_depth": "not_applicable" }, "expected_behavior": "应提示存在暴力降维风险：延期可能不是个人效率问题，而可能涉及目标频繁变化、资源不足、依赖不清、决策拥堵。应先补 evidence_gap。", "failure_signal": "直接输出个人效率提升清单。", "forbidden_elements": [ "仅归因于个人不努力", "只给时间管理方法" ], "notes": "测试 QPI 是否能拒绝接受甩锅式问题框架。" } ``` ### 2.2 可能被误判：把具体工程问题恶意升维成宏大课题 ```json { "case_id": "calibration_qpi_misjudge_002", "group": "qpi_potential_misclassification", "input": "我现在只是要决定模型库用 JSON 文件还是 SQLite，但我担心这背后是不是人类知识管理范式的根本问题。", "expected_primary_model": "qpi", "negative_expected_models": [ "intellectual_archaeology" ], "expected_qpi": { "classification": "problem", "dominant_scarcity": "path_resource", "classification_confidence": "high", "scarcity_profile": { "data_scarcity": "low", "path_or_resource_scarcity": "high", "consensus_or_order_scarcity": "low" }, "minimum_required_elements": [ "misclassification_risk", "recommended_next_step" ] }, "expected_ia": { "should_call": false, "recommended_max_depth": "not_applicable" }, "expected_behavior": "应识别为 problem，主要缺路径取舍。应提示存在恶意升维风险：当前阶段只需按 file-first MVP 的可维护性、校验便利性、扩展成本做技术选择。", "failure_signal": "进入知识论、文明史或哲学基岩分析。", "forbidden_elements": [ "philosophical_bedrock", "人类知识范式", "七层下钻" ], "notes": "测试 QPI 是否能防止把工程取舍升维成无法行动的课题。" } ``` --- ## 3. 思想考古容易过度下潜的问题：2 条 这类样本要测思想考古的 **停止门**。思想考古可以调用，但必须停在合适层级；如果继续下潜不改变判断、路径、验证方式或行动边界，就要停止。 ### 3.1 应调用思想考古，但只到 purpose 层 ```json { "case_id": "calibration_ia_overdepth_001", "group": "ia_over_depth_risk", "input": "我想把 QPI 写成一张更稳定的模型卡。请帮我检查它到底是问题分类模型、路由模型，还是完整分析模型。", "expected_primary_model": "intellectual_archaeology", "negative_expected_models": [], "expected_qpi": { "classification": "problem", "dominant_scarcity": "path_resource", "classification_confidence": "medium" }, "expected_ia": { "should_call": true, "recommended_max_depth": "purpose", "minimum_required_elements": [ "entry_reason", "layers_to_analyze", "stop_reason", "no_deeper_reason", "action_implication" ] }, "expected_behavior": "可以进入思想考古，但只需要下潜到 purpose 层：明确 QPI 的产品目的，是前置路由而不是完整解释系统。继续下潜到 human_capability 或 philosophical_bedrock 不会改变模型卡结构。", "failure_signal": "默认展开七层，讨论认识论基岩。", "forbidden_elements": [ "philosophical_bedrock", "完整七层展开" ], "notes": "测试思想考古的 minimum-depth，不是测试深度表达。" } ``` ### 3.2 应调用思想考古，但只到 core_mechanism 层 ```json { "case_id": "calibration_ia_overdepth_002", "group": "ia_over_depth_risk", "input": "思想考古这个模型容易写得很玄。我想把它改成系统可调用模型，请帮我找出它真正可复用的核心机制。", "expected_primary_model": "intellectual_archaeology", "negative_expected_models": [], "expected_qpi": { "classification": "problem", "dominant_scarcity": "path_resource", "classification_confidence": "medium" }, "expected_ia": { "should_call": true, "recommended_max_depth": "core_mechanism", "minimum_required_elements": [ "recommended_max_depth", "stop_reason", "no_deeper_reason", "validation_needed" ] }, "expected_behavior": "应下潜到 core_mechanism：思想考古的可调用机制是层级化追问、最小充分下潜、假设显性化、停止门。到这里已足以改模型卡；不需要讨论哲学基岩。", "failure_signal": "把重点转成宏观哲学解释，而没有产出可调用机制。", "forbidden_elements": [ "为了深刻而深刻", "哲学基岩默认调用" ], "notes": "测试 IA 是否能服务模型产品化，而不是自动哲学化。" } ``` --- ## 4. “看起来很深但其实不该调用”的问题：2 条 这类样本是 selector 防误召回。当前规则明确：思想考古不应仅因为出现“底层”“模型”“哲学”等词就被召回；问题定义未完成时，应先通过 QPI。 ### 4.1 出现“底层逻辑”，但其实是轻量改写 ```json { "case_id": "calibration_no_call_deep_word_001", "group": "deep_but_no_call", "input": "帮我把这句话改得更有底层逻辑一点：我们要先做好模型库，再扩展更多模型。不要展开分析，只改写。", "expected_primary_model": "none", "negative_expected_models": [ "qpi", "intellectual_archaeology" ], "expected_qpi": { "classification": "no_call", "dominant_scarcity": "unknown", "classification_confidence": "high" }, "expected_ia": { "should_call": false, "recommended_max_depth": "not_applicable" }, "expected_behavior": "应识别为纯改写任务，negative trigger 优先。不得因为出现“底层逻辑”“模型库”而召回思想考古。", "failure_signal": "开始解释模型库的底层逻辑，或调用思想考古。", "forbidden_elements": [ "七层下钻", "QPI 分类分析", "思想考古" ], "notes": "测试 negative trigger first。" } ``` ### 4.2 出现“哲学”，但其实是事实查询 ```json { "case_id": "calibration_no_call_deep_word_002", "group": "deep_but_no_call", "input": "帮我查一下‘哲学基岩’这个词在我上传的思想考古模型卡里有没有出现，只要告诉我有还是没有。", "expected_primary_model": "none", "negative_expected_models": [ "qpi", "intellectual_archaeology" ], "expected_qpi": { "classification": "no_call", "dominant_scarcity": "data", "classification_confidence": "high" }, "expected_ia": { "should_call": false, "recommended_max_depth": "not_applicable" }, "expected_behavior": "应识别为明确事实查询或文件检索任务，不进入模型分析。可以执行检索，但不调用思想考古。", "failure_signal": "因为出现“哲学基岩”而展开思想考古。", "forbidden_elements": [ "深层假设分析", "philosophical_bedrock 分析", "七层结构" ], "notes": "测试关键词误召回。" } ``` --- ## 5. 模型抽取任务：1 条 模型抽取任务是思想考古可以进入的正例，因为它要把文章或代表文本抽成可复用、可边界化、可测试、可被 selector 调用的模型资产。当前模型抽取链路是：原始文章 / 代表文本 → source article record → source evidence excerpts → Markdown card → JSON model card → regression cases → selector rules / examples → indexes → validation report → CCRA review。 ### 5.1 从文章中抽取一个候选核心模型 ```json { "case_id": "calibration_model_extraction_001", "group": "model_extraction_task", "input": "我给你一篇关于‘认知棱镜’的文章，请不要摘要文章，而是判断里面是否存在可产品化的核心模型，并按模型卡结构抽取：核心问题、核心机制、输入、输出、适用场景、不适用场景、调用关键词、误用风险、回归测试样例。", "expected_primary_model": "intellectual_archaeology", "negative_expected_models": [], "expected_qpi": { "classification": "problem", "dominant_scarcity": "path_resource", "classification_confidence": "medium" }, "expected_ia": { "should_call": true, "recommended_max_depth": "core_mechanism", "minimum_required_elements": [ "entry_reason", "layers_to_analyze", "assumptions_by_layer", "validation_needed", "action_implication", "no_deeper_reason" ] }, "expected_behavior": "应识别为模型抽取任务，不是文章摘要。可以调用思想考古下潜到 core_mechanism，找出可复用机制、边界、误用和测试方式。若原文证据不足，应标注 evidence_gap，不得编造来源。", "failure_signal": "只做文章摘要，或直接生成漂亮但不可追溯的模型卡。", "forbidden_elements": [ "无来源证据的核心机制断言", "默认 stable", "直接扩展进核心模型库" ], "notes": "测试模型抽取链路和 evidence discipline。" } ``` --- ## 6. 给 Codex 的简短说明可以这样写 ```text 下面 10 条不是最终内容样本，而是 selector calibration / regression 人审样本格式参考。 请不要把这些样本直接视为模型稳定证据。 请将它们放入 selector_calibration_inputs.json 或等价文件中，用于测试： 1. QPI mixed case 是否输出 scarcity_profile、dominant_scarcity、evidence_gap； 2. QPI 是否识别暴力降维、恶意升维、手段错配； 3. 思想考古是否遵守 recommended_max_depth、stop_reason、no_deeper_reason； 4. selector 是否能在轻量改写、明确事实查询、直接执行任务中 no-call； 5. 模型抽取任务是否能进入思想考古，但不能变成文章摘要或无证据模型卡。 ``` 我建议你实际交给 Codex 时，先用这 10 条作为格式模板，然后把其中 3-5 条替换成你最近真实遇到的问题。真实样本比拟真样本更能暴露 selector 的误召回。