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Agent Skill · 研究检索

self-improvement-agent(自我提升剂)

self-improvement-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。

self-improvement-agent 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为执行命令;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 9,270。

总安装 14,577周安装 584GitHub Stars 公开资料未说明下载 4,719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:self-improvement-agent(自我提升剂)
来源仓库:https://github.com/lucasye378/self-improvement-agent
安装命令:
openclaw skills install self-improvement-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 self-improvement-agent

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。

记录错误与用户纠正措施,推动Agent持续自我完善。适用于执行异常、知识盲区与用户需求变更等情形。支持多轮反馈整合与策略调整,提升长期任务表现。改进过程应保留证据链,确保可追溯性与责任界定。self-improvement-agent 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

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 self-improvement-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

    它需要执行命令,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

self-improvement-agent 怎么安装?

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

self-improvement-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。

self-improvement-agent 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 openclaw skills install self-improvement-agent 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

self-improvement-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。

self-improvement-agent 用的人多吗?

公开数据是累计安装 14,577 次,近一周安装 584 次,下载 4,719 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。

self-improvement-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。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 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

  • 不能接受 Skill 在你机器上执行命令的人。
  • 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
self-improvement-agent

自我提升剂 · 本页

14,577—执行命令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
self-improving-agent
description
Captures learnings, errors, and corrections for continuous improvement. Use when: (1) A command fails unexpectedly, (2) User corrects you ('No, that's wrong...', 'Actually...'), (3) User requests a missing capability, (4) An external API or tool fails, (5) You realize your knowledge is outdated, (6) A better approach is found for a recurring task. Also review .learnings/ before major tasks. Trigger words: 'actually', 'wrong', 'outdated', 'I wish you could', 'why can't you', non-zero exit code.

Self-Improvement Skill

Log learnings and errors to markdown files. Important patterns get promoted to project memory files.

Quick Reference

SituationAction
Command/operation failsLog to .learnings/ERRORS.md
User corrects youLog to .learnings/LEARNINGS.md (category: correction)
User wants missing featureLog to .learnings/FEATURE_REQUESTS.md
API/external tool failsLog to .learnings/ERRORS.md
Knowledge was outdatedLog to .learnings/LEARNINGS.md (category: knowledge_gap)
Found better approachLog to .learnings/LEARNINGS.md (category: best_practice)
Similar to existing entryLink with **See Also**, bump priority
Broadly applicable learningPromote to workspace files (see below)

Promotion Targets

When a learning proves broadly applicable, elevate it:

Learning TypePromote To
Behavioral patternsSOUL.md
Workflow patternsAGENTS.md
Tool gotchasTOOLS.md
Project factsCLAUDE.md or workspace prompt files

Logging Format

Learning Entry

## [LRN-YYYYMMDD-XXX] category

**Logged**: ISO-8601 timestamp
**Priority**: low | medium | high | critical
**Status**: pending | resolved | promoted | in_progress

### Summary
One-line description of what was learned

### Details
Full context: what happened, what was wrong, what's correct

### Suggested Action
Concrete fix or improvement

### Metadata
- Source: conversation | error | user_feedback
- Related Files: path/to/file.ext
- Tags: tag1, tag2
- See Also: LRN-YYYYMMDD-XXX (if related)

Error Entry

## [ERR-YYYYMMDD-XXX] command_or_tool

**Logged**: ISO-8601 timestamp
**Priority**: high
**Status**: pending

### Summary
Brief description of what failed

### Error

Paste actual error output here


### Context
- Command/operation attempted
- Input or parameters used
- Environment details

### Suggested Fix
If identifiable, how to resolve it

### Metadata
- Reproducible: yes | no | unknown
- Related Files: path/to/file.ext

Feature Request Entry

## [FEAT-YYYYMMDD-XXX] capability_name

**Logged**: ISO-8601 timestamp
**Priority**: medium
**Status**: pending

### Requested Capability
What the user wanted to do

### User Context
Why they needed it

### Complexity Estimate
simple | medium | complex

ID Generation

TYPE-YYYYMMDD-XXX — e.g. LRN-20250322-001, ERR-20250322-A3F

Resolving Entries

When fixed:

  1. Set Status: resolved or promoted
  2. Add resolution block:
### Resolution
- **Resolved**: 2025-01-16T09:00:00Z
- **Commit/PR**: abc123 or #42
- **Notes**: What was done

Promoting to Workspace Files

When: Learning applies across files, prevents recurring mistakes, or any contributor should know it.

How: Distill into a concise rule. Add to target file. Set original entry to promoted.

Example learning:

Project uses pnpm workspaces. npm install fails because lock file is pnpm-lock.yaml.

Promote to CLAUDE.md:

## Build & Dependencies
- Package manager: **pnpm** (not npm) — always use `pnpm install`

Recurring Pattern Detection

Before logging, search for related entries:

grep -r "keyword" .learnings/

If similar entry exists:

  • Link with **See Also**: LRN-...
  • Increment Recurrence-Count
  • Consider systemic fix (promote to AGENTS.md, create tech debt ticket)

Promote to permanent prompt guidance when a pattern:

  • Occurs 3+ times
  • Spans 2+ distinct tasks
  • Within a 30-day window

OpenClaw Inter-Session Tools

Share learnings across sessions:

ToolUse
sessions_listView active/recent sessions
sessions_history(sessionKey, limit)Read another session's transcript
sessions_send(sessionKey, message)Send a learning to another session
sessions_spawn(task, label, mode)Spawn a background sub-agent

Example: After a session ends, promote its key learnings to workspace files. Use sessions_history to review what another session discovered.

Periodic Review

Check .learnings/ at natural breakpoints:

  • Before starting a new major task
  • After completing a feature
  • Weekly during active development

Quick status:

grep -h "Status.*pending" .learnings/*.md | wc -l  # count pending
grep -B3 "Priority.*high" .learnings/*.md | grep "^##"  # high priority items

Detection Triggers

Log immediately when you notice:

Signal→ Entry
Non-zero exit code, exception, timeoutERRORS.md
User says "No, that's wrong...", "Actually..."LEARNINGS.md (correction)
User provides info you didn't knowLEARNINGS.md (knowledge_gap)
"Can you also...", "I wish you could..."FEATURE_REQUESTS.md
Found a better approach mid-taskLEARNINGS.md (best_practice)
Repeated mistake (2+ times)Promote to workspace file

Best Practices

  1. Log immediately — context is freshest right after the issue
  2. Be specific — future you needs to understand quickly
  3. Suggest concrete fixes — not just "investigate"
  4. Link related files — makes fixes easier
  5. Promote aggressively — broadly applicable learnings belong in workspace files, not hidden in .learnings/
  6. Use consistent IDs — enables See Also linking

Installation (OpenClaw)

clawhub install self-improving-agent

Manual:

git clone https://github.com/pskoett/self-improving-agent.git ~/.openclaw/skills/self-improving-agent

Create log directory:

mkdir -p ~/.openclaw/workspace/.learnings

Detailed Topics

For complete documentation, see:

  • OpenClaw integration: references/openclaw-integration.md
  • Hook setup: references/hooks-setup.md
  • Full entry examples: references/examples.md
  • Skill extraction workflow: references/skill-extraction.md
  • Other agents (Claude Code, Codex, Copilot): references/other-agents.md

平台分布

OpenClaw

70.96%
按下载量换算3,349

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 openclaw skills install self-improvement-agent 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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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