Individual skill
agentsop-trajectory-to-semantic-ops
SOP for distilling reusable semantic operators (data-science operation skills) from agent execution trajectories: read action/observation traces, classify per-task failures, bind data-semantic constraints (input semantics / operation decision / output constraints / validation), and feed bounded edits back through an optimizer such as SkillOpt. Use when mining agent runs for cross-task operation knowledge, when a data-science skill keeps failing on the same operation family (join cardinality, group granularity, unit, time alignment), or when wiring trajectory history into a skill optimizer without polluting the skill body.
skills/agentsop-trajectory-to-semantic-ops/SKILL.md
Source commit cf4376869e5f23f82404c3021a2a1315dfca318d
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- Last checked
- Nov 6, 2026
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- 465
- Repository last updated
- Oct 24, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- agent-skill Repository topic
- skill-creation Repository topic
- ai-agent Repository topic
- llm-agent Repository topic
- skill-engineering Repository topic
- skill-generation Repository topic
- skill-pipeline Repository topic
- skill-construction Repository topic
- agent-skills Repository topic
- skill-acquisition Repository topic
- data Derived category
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README.mddoc · 3,745 bytesSKILL.mdcore · 11,917 bytesintermediate/operation_candidates.jsonasset · 8,788 bytesreferences/R1-architecture.mddoc · 5,903 bytesreferences/R2-sop-workflow.mddoc · 4,647 bytesreferences/R3-dilemma-cases.mddoc · 3,865 bytesreferences/R4-anti-patterns.mddoc · 3,176 bytesreferences/R5-ecosystem-context.mddoc · 4,223 bytes
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# 执行轨迹 → 语义算子 提炼 SOP
> 一句话：把 agent 的一次运行轨迹（动作 + 观察 + 退出码 + 分数）压成「失败证据」，再把它翻译成**带数据语义约束的可复用算子**——不是把轨迹原样塞回提示词，而是提炼出「为什么这一步会错」的跨任务决策规则。
## 1. 何时激活本技能
下列任一情形成立时，按本 SOP 进入「轨迹提炼」工作模式：
- 你手里有一批 agent 运行产物：`trajectory.json`（结构化动作流）、`agent_trace.txt`（可读的「动作 → 观察」）、`results.jsonl`（逐题分数/失败原因）。
- 你要**从失败里长出新技能**，或让一个现有数据科学技能在某类操作上不再重复犯错。
- 你在跑 SkillOpt（或类似轨迹优化器），需要把历史轨迹喂进去，但**不希望污染技能正文**。
- 你关心的是**跨任务可复用**的操作知识，而不是某一题的具体答案。
**不应激活的反面信号**：见 §6 反模式与边界。