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Lanqiao-LucaLanqiao-Luca/ai-java-workflow/skills/conclusion-challenge/SKILL.md

conclusion-challenge

Skill220 starsChanged 8 days agoMITView on GitHub

复核已形成的高影响技术根因或修复判断,组织竞争解释、共同证据矩阵、主动反证和敏感性分析;不因普通格式质疑触发,不自动取证或改业务。

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SKILL.md

目的:把重要技术判断适配成可追溯的反证报告,交回限定结论与最小补证。

适用于:责任 Agent 已接收原判断、当前候选、取证范围与预算的结论复核。

结论反证

消费 CH01–CH04,复用诊断的原观察;需新增材料时只提出范围和区分问题,由当前取证职责取得。方法阈值不以凑解释或证据数量代替场景判断。

  1. 绑定候选及原命题,标事实、推断、来源范围和已知缺口。
  2. 使用同一证据集评估合理竞争解释,逐格填写关系与理由,保同源组及可靠性限制。
  3. 实际尝试推翻最初首选,记录期待反例、动作与观察;未执行保 NOT_RUN,缺来源保 UNAVAILABLE,不把预期当结果。
  4. 对决定性证据作移除分析,输出限定结论、尚存解释与下一责任。候选变化按原子回到失效点。
  5. 若采用 JSON 合同,用结构工具的 check(report, candidate_sha256);第二参数须由调用方核当前候选实际字节取得。返回 STRUCTURE_VALID 只表示表内结构完整,semantic_acceptance 始终 NOT_ASSESSED,pending_checks 明确保缺证。

可按调用方提供的报告空表保存;最小 JSON 字段与实际执行见离线案例。纯自然语言审查不强制序列化为 JSON。保存文档继续沿当前文档维护职责,不安装角色、不发请求或启动后台流程。

返回:Skills。

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