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Agent Skill · 效率

retrospective-agent(追溯 Agent 人)

retrospective-agent 用于记录任务执行中的错误、用户纠正、经验和能力缺口,适合在 OpenClaw 中希望让 Agent 持续沉淀问题、修正和最佳实践时使用。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。

retrospective-agent 是效率类 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,按安装量在效率类的 21,003 个 Skill 里排第 4,128。

总安装 14,296周安装 584GitHub Stars 1下载 4,579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
1.0.0

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:retrospective-agent(追溯 Agent 人)
来源仓库:https://github.com/sebclawops/retrospective-agent
安装命令:
openclaw skills install retrospective-agent
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 retrospective-agent

这个 Skill 是做什么的

效率类 Skill 把重复的整理、汇总、转换工作交给助手完成,减少手工复制粘贴。

OpenClaw代理的结构化回顾与执行内存管理工具。适用于经验沉淀、错误修正与最佳实践固化场景。自动记录任务失败、用户纠正与能力缺口,形成知识库更新。安装命令:openclaw skills install retrospective-agent,需启用持久化存储。

注意隐私与数据安全,避免在回顾中泄露敏感操作或内部凭证。

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 retrospective-agent;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

retrospective-agent 怎么安装?

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

retrospective-agent 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。

retrospective-agent 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。

retrospective-agent 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。

retrospective-agent 用的人多吗?

公开数据是累计安装 14,296 次,近一周安装 584 次,下载 4,579 次,GitHub 1 星。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。

retrospective-agent 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。
  • 需要处理效率类任务、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。

效率类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
github

GitHub 代码协作 · OpenClaw

7,632,918545需要联网MIT-0通过
nano-pdf

Nano PDF 文档 · OpenClaw

4,249,476231需要联网MIT-0通过
auto-updater

自动更新程序 · OpenClaw

2,964,063386操作浏览器MIT-0通过
video-frames

视频帧 · OpenClaw

2,621,304112需要联网MIT-0通过
gemini

Gemini 助手 · OpenClaw

2,547,39648需要联网MIT-0有提醒
retrospective-agent

追溯 Agent 人 · 本页

14,2961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
retrospective-agent
description
Structured retrospectives and execution-memory hygiene for OpenClaw agents. Use when the user wants a retrospective, lessons learned, self-improvement system, correction logging, weekly review, or a clean way to capture reusable execution lessons without creating hidden memory or autonomous behavior.

Retrospective Agent

Use this skill to capture execution lessons in a controlled, auditable way.

This skill exists to improve how the agent works over time. It does not create a second factual memory system, rewrite identity, or invent autonomy.

Core principles

  • Keep factual continuity in existing memory files
  • Keep execution lessons separate and scoped
  • Prefer reports and recommendations over automatic changes
  • Promote patterns only after repeated evidence
  • Never infer preferences from silence
  • Never rewrite persona, config, or outbound behavior on your own

Memory split

Use existing memory for

  • facts
  • events
  • decisions
  • dates
  • people
  • open tasks

Examples:

  • memory/YYYY-MM-DD.md
  • agent MEMORY.md
  • project README.md

Use retrospective-agent files for

  • repeated corrections
  • workflow improvements
  • tool failure patterns
  • success patterns worth repeating
  • project or domain execution lessons

Storage

Skill files live in:

  • workspace/skills/retrospective-agent/

Operational data lives in:

  • workspace/ops/retrospective-agent/

Expected first-pass files:

  • workspace/ops/retrospective-agent/corrections.md
  • workspace/ops/retrospective-agent/weekly/
  • workspace/ops/retrospective-agent/domains/
  • workspace/ops/retrospective-agent/projects/
  • workspace/ops/retrospective-agent/templates/

If the ops folder or expected files do not exist, create only the minimum needed for the current task. Do not create extra files "just in case".

Triggers

Use this skill when:

  • the user asks for a retrospective or lessons learned
  • a multi-step task ends and a short retro would be useful
  • the user gives a reusable correction
  • a process or tool fails in a reusable way
  • a project needs scoped lessons for future work
  • a weekly review is requested

Do not use this skill for:

  • one-off instructions with no reusable lesson
  • customer messaging drafts
  • sensitive personal profiling
  • fake automation or hidden monitoring claims

Operating modes

1. Post-task retrospective

Use after meaningful work.

Output:

  • what went well
  • what went wrong
  • what to repeat
  • what to change next time
  • whether anything deserves logging

Keep it short and operational.

2. Correction logging

Use when an explicit correction reveals a reusable lesson.

Workflow:

  1. capture the exact correction
  2. classify it
  3. choose scope: project, domain, or global execution lesson
  4. append a concise entry if warranted
  5. recommend promotion only after repeated evidence

3. Weekly retrospective

Use on demand or when a scheduled review is explicitly requested.

Output:

  • recurring wins
  • recurring misses
  • repeated patterns
  • candidate updates to memory, README files, or skills

Scope hierarchy

Most specific wins:

  1. project
  2. domain
  3. global execution lesson

If scope is unclear, prefer domain over global. If still unclear, say so.

Promotion model

Use conservative states:

  • observed
  • repeated
  • candidate rule
  • confirmed rule

Suggested threshold:

  • 1 occurrence: observed
  • 2 occurrences: repeated
  • 3 occurrences: candidate rule

Do not silently promote a candidate into durable agent behavior everywhere. Recommend the promotion and ask when confirmation matters.

Guardrails

Never:

  • rewrite SOUL.md
  • rewrite IDENTITY.md
  • rewrite USER.md
  • patch config
  • send messages
  • install companion skills without approval
  • infer preferences from silence
  • store credentials, secrets, or sensitive personal data
  • claim autonomous monitoring unless a real scheduler exists

Workflow references

Read these only when needed:

  • references/workflow.md
  • references/promotion-rules.md
  • references/boundaries.md

Use templates from:

  • assets/templates/post-task-retro.md
  • assets/templates/weekly-retro.md
  • assets/templates/lesson-entry.md

Style

Be honest, compact, and boring in a good way. Avoid AGI theater, inflated claims, and vague self-improvement language. Prefer operational wording like "lesson", "pattern", "correction", and "recommended update" over dramatic wording like "optimize myself" or "evolve".

Output rule

Lead with the useful retrospective or lesson. Do not narrate the framework unless the user asks.

平台分布

OpenClaw

90.08%
按下载量换算4,125

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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