template-skill
anthropics/skills180k
anthropics/skills180kprovenance
收集系统全链路操作日志，生成可追溯的执行证据链与向量索引，是多智能体系统可观测性与安全审计的底座。
Install
Send this to Claude Code, Codex or Cursor. The agent checks the Skill for safety first and installs it only after you confirm.
读取 https://funcoding.ai/skills/anbeime/skill/provenance/install.md ，按里面的步骤帮我安装这个 Skill。
SKILL.md
Provenance 留痕 Skill（太史阁）
使用方式
- 由各官署在关键操作节点调用（或通过事件总线异步推送），写入证据链。
- 提供按
trace_id/ 时间窗 / 官署维度的检索接口，支撑审计面板与回滚定位。
输入（Input）
event：操作事件，含actor（官署名）、action、target、timestamp、trace_idpayload：（可选）与事件关联的结构化产物引用
输出（Output）
evidence_chain：按 trace_id 串联的可追溯证据链vector_index：用于语义检索的向量索引条目query_api：按条件检索历史证据的接口描述
依赖（Dependencies）
- Qdrant（向量存储，经 MCP 接入）
- SQLite（结构化事件落地，本地兜底）
- 各官署的事件上报协议（统一 schema）
失败处理（Failure Handling）
- 向量库写入失败 → 本地 SQLite 缓存事件，恢复后异步补写，不阻塞主流程。
- 单条事件 schema 非法 → 记录并丢弃该条，不影响整链写入。
- 检索超时 → 返回最近一次成功快照并标注
stale。
复用价值（Reuse Value）
- 可观测性底座：任何多 Agent 系统都能直接挂载，获得开箱即用的审计与回放能力。
- 契合评审：Agent Infra 赛道「工程落地与运行验证及安全审计（20%）」维度的天然得分点。
复赛代码包执行（runnable package）
- 真实入口：
scripts/run_provenance.py - 执行等价于
core.runtime.AgentSession.run_stage("provenance")，调用memory.taishige.TaiShiGeAgent.writeback（把全链路事件与四色卡片回流证据链，纯 Python 可离线）。 - 运行：
python skills/provenance/scripts/run_provenance.py - 产物：
examples/snse_survey/provenance/（trace.jsonl + trace_summary.json，含每一条军机处派发与官署执行事件）。
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