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Agent Skill · 研究检索

agent-provenance(Agent 出处)

agent-provenance 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

agent-provenance 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为只读;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 18,550。

总安装 6,030周安装 259GitHub Stars 公开资料未说明下载 2,113核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
2.1.4

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:agent-provenance(Agent 出处)
来源仓库:https://github.com/richgoodson/agent-provenance
安装命令:
openclaw skills install agent-provenance
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install agent-provenance

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

跟踪文件来源、权限级别与提交约定,确保变更责任可追溯。适用于代码仓库、文档协作与审计合规场景。支持治理策略制定与权限分级管理机制。agent-provenance 属于研究检索类 Skill,可作为该场景下的辅助能力补充。使用前应建立清晰的提交规范与审批流程。建议定期审查日志以防范未授权修改行为。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install agent-provenance;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

agent-provenance 怎么安装?

在终端执行 openclaw skills install agent-provenance。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

agent-provenance 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

agent-provenance 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

agent-provenance 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

agent-provenance 用的人多吗?

公开数据是累计安装 6,030 次,近一周安装 259 次,下载 2,113 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

agent-provenance 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
agent-provenance

Agent 出处 · 本页

6,030—只读MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
agent-provenance
description
>-
license
MIT
compatibility
OpenClaw 2026.4.x or later.
metadata
openclaw
requires
bins
["openclaw", "git"]
paths
write
["AGENTS.md", "IDENTITY.md", "TOOLS.md", "BOOT.md", "LEARNINGS.md", "HEARTBEAT.md", "MEMORY.md", "memory/topics/", "memory/contacts/"]
read
["SOUL.md", "PRINCIPLES.md", "USER.md", "AGENTS.md", "IDENTITY.md", "TOOLS.md", "BOOT.md", "LEARNINGS.md", "HEARTBEAT.md", "MEMORY.md", "memory/"]
version
2.1.4
clawhub
{"category": "governance", "tags": ["provenance", "audit", "review", "ttl", "git"]}

Agent Provenance v2.1.4

Agents modify their own instruction files, topic files, and memory. Without tracking, human-authored rules become indistinguishable from agent-authored additions. This skill provides lightweight governance to maintain that distinction — provenance headers, authority levels, commit conventions, and review policies to ensure accountability and maintainability.

The Problem

Instruction files evolve over time. Without clear tracking, it's unclear who made changes and when, review responsibilities become ambiguous, agent-written goals can persist indefinitely without validation, security boundaries can be eroded gradually, and audit trails are lost.

Prerequisites

This skill requires git to be initialized in the workspace. The agent needs write access to instruction files and memory files (declared in the metadata above). Diff reports are posted to the conversation channel — no external channel credentials are needed unless the user configures an external destination.

All scheduled tasks (diff reports, heartbeat checks) use OpenClaw's built-in cron tool. They run as isolated agent sessions within the OpenClaw sandbox. No OS-level schedulers (crontab, systemd, launchd) are created or modified.

Architecture

Provenance Headers

All instruction files carry an HTML comment header:

<!--
  provenance: human-authored | agent-authored | mixed
  description: what this file is
  last-reviewed: YYYY-MM-DD
  reviewed-by: Human | Agent
-->

Provenance types:

  • human-authored — files created by the human user and not modified by the agent without explicit direction (SOUL.md, PRINCIPLES.md, USER.md)
  • agent-authored — files created and maintained by the agent (LEARNINGS.md, session files, daily notes, topic files, time-based archives)
  • mixed — files with both human policy and agent procedures (AGENTS.md, IDENTITY.md, TOOLS.md, HEARTBEAT.md, BOOT.md, contact files)
  • transient — one-shot scratch files with no provenance cadence (BOOTSTRAP.md). Not governed by this skill — OpenClaw creates them for a brand-new workspace and removes them after the bootstrap ritual finishes.

Only the user updates last-reviewed and reviewed-by on human-authored files.

Authority Levels

Files have different sensitivity levels that determine who can modify them and how changes are tracked.

Human-authored files (SOUL.md, PRINCIPLES.md, USER.md) define the agent's identity and core rules. The agent does not modify these without explicit direction from the user.

Mixed files (AGENTS.md, IDENTITY.md, TOOLS.md, HEARTBEAT.md, BOOT.md, contact files) have user-set policy with agent-maintained operational procedures. IDENTITY.md is created during the bootstrap ritual and may be updated by the agent, but the user owns the underlying identity assertions. TOOLS.md holds local tool notes and conventions — user-shaped guidance that blends with agent-observed usage patterns. BOOT.md is an optional startup checklist with the same mixed ownership. Contact files are mixed because the agent captures information from conversations but the user may correct details or add private context. All changes are logged in git.

Transient files (BOOTSTRAP.md) are first-run scratch files that OpenClaw creates for a brand-new workspace and deletes after the bootstrap ritual. They carry no provenance header and are not subject to review cadence. If BOOTSTRAP.md persists for more than a few sessions, flag it as an anomaly rather than treating it as a reviewable instruction file.

Agent-authored files (LEARNINGS.md, session files, daily notes, topic files) are written freely by the agent and reviewed periodically by the user. Topic files represent authoritative project state and should be treated with more care than transient session files.

Routing table (MEMORY.md) has mixed authority. The agent maintains pointers, but MEMORY.md is loaded into every session's system prompt, so changes have high impact. Keep it under 3KB with only pointers and active constraints. Log all changes via git with appropriate commit tags.

Commit Message Convention

Workspace commits use a tag prefix to identify who directed the change:

  • [human-directed] — the user explicitly asked for this change
  • [agent-autonomous] — the agent decided to make this change independently
  • [heartbeat] — change made during a heartbeat cycle
  • [cron] — change made by a scheduled job

This makes git log --oneline <file> a real audit trail.

Software project commits (any external project) use plain descriptive messages with NO provenance tags. Tags like [human-directed] are AI fingerprints — they leak that an agent is involved in the project.

TTL on Agent-Written Goals

Anything the agent writes to a goals, tasks, or backlog section gets a date stamp. If an agent-written goal is older than 14 days and the user hasn't touched it, the agent does not silently keep following it. Instead, ask the user whether it's still valid.

TTL on Topic Files

Topic files represent active projects and workstreams. If a topic file hasn't been modified in 30 or more days, flag it for the user during the next heartbeat: "The topic file for [project] hasn't been updated in a month. Is this still active, or should it be archived?" If the user confirms it's still active, update the file's timestamp. If the user says archive it, move it to memory/topics/archive/ and remove the pointer from MEMORY.md.

This prevents stale topic files from accumulating and cluttering search results, and keeps MEMORY.md's routing table current.

Instruction Diff Reports

Weekly (or on-demand via "diff report"): the agent diffs all instruction files against their state 7 days ago and posts a summary to the conversation. What changed, who changed it, why. The user reviews, confirms, or reverts.

Schedule the diff report at a fixed local time that works for the user (e.g., Sunday morning). There's nothing special about the exact time — pick one, set a cron using OpenClaw's built-in cron tool, be consistent.

Review Flagging with Graduated Urgency

Instruction files and key memory files should be reviewed periodically. Rather than a single flag, use graduated urgency:

30 days since last review — mention during heartbeat. Example: "AGENTS.md hasn't been reviewed in 30 days. Worth a quick look when you have time."

60 days since last review — warn explicitly. Example: "AGENTS.md is 60 days past its last review. I'm still following its instructions, but they may be outdated. Can you review it this week?"

90 days since last review — escalate. Example: "AGENTS.md hasn't been reviewed in 90 days. At this point it's either stable enough to not need review (in which case, update the review date to acknowledge that) or it's drifted without anyone noticing. Please review and confirm."

This applies to human-authored and mixed files. Agent-authored files don't need the same review cadence but benefit from periodic user spot-checks.

Setup

Initialize git in the workspace if it isn't already a repository, and configure a local git identity for agent commits. Use a name that makes agent-authored commits identifiable in the log. Create a .gitignore if needed to exclude temporary files, secrets, and local state.

Daily Provenance Checks

During heartbeat cycles:

  1. Check last-reviewed dates in provenance headers of all instruction files
  2. Apply graduated urgency: mention at 30 days, warn at 60, escalate at 90
  3. Check for agent-written goals/tasks older than 14 days without user interaction — flag for re-authorization
  4. Check for topic files untouched for 30 or more days — flag for archival or confirmation
  5. Generate weekly diff report if due

Security Implications

Provenance tracking provides defense in depth. It makes unauthorized changes visible in git history, enforces regular review of critical files, provides accountability for agent actions, and creates an audit trail for compliance.

Sensitive data: Provenance headers and commit messages should never contain secrets, API keys, or credentials. Commit messages describe what changed and why — they should reference file names and decisions, not secret values. The same redaction guidance from agent-session-state applies: log the existence of a credential and where it is stored, not the value itself.

Integration with Other Skills

hierarchical-agent-memory provides the memory structure this skill governs. MEMORY.md is a lean routing table with pointers to topic and contact files. Topic files are agent-authored and subject to the 30-day staleness check. Contact files are mixed authority. Daily notes and time-based archival layers are agent-authored and maintained freely. All memory file changes should use appropriate commit tags.

agent-session-state manages per-channel session files. Session state files are agent-authored and transient. They don't need provenance headers or review cadence, but commits that modify them should use the appropriate tag for audit trail purposes.

memory-wiki (bundled OpenClaw plugin, as of 2026.4.x) compiles durable knowledge into a separate vault at ~/.openclaw/wiki/main/ with its own lifecycle: structured claims, evidence linkage, freshness dashboards, wiki_lint, and the reports/ dashboard set. This skill does not govern the wiki vault. Do not retrofit provenance headers, last-reviewed dates, graduated urgency, or commit-tag discipline onto wiki pages — wiki has its own claim-level schema and lint tooling, and the two systems are deliberately orthogonal (file authorship and accountability vs. claim-level evidence lineage). Commits that touch wiki output should still use appropriate tags for audit trail purposes, but the pages themselves are out of scope.

Best Practices

For the agent: Always include provenance headers on new instruction files and new topic/contact files. Update last-reviewed after the user reviews a file. Use appropriate commit tags. Flag old content for review using graduated urgency. Ask the user about stale agent-written goals. Flag untouched topic files for archival.

For the user: Review flagged files promptly — graduated urgency means the agent will keep escalating until you respond. Update last-reviewed and reviewed-by after each review. Provide clear direction for changes explicitly requested. Periodically check git history for anomalies. When archiving a topic, confirm the MEMORY.md pointer is removed.

Related Skills

  • hierarchical-agent-memory — Hybrid topic-based working memory with optional time-based archival layers
  • agent-session-state — Per-channel isolation and WAL protocol

平台分布

OpenClaw

92.16%
按下载量换算1,947

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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