According to AlphaMoat, as of 2026-10, Self Improving Agent CN has 117,705 downloads and 50 stars — ranked by downloads #211 among 10,914 AI skills in this ranking, and #48 of 1,632 in AI Agent.
The list defaults to total downloads and can also be sorted by stars; detail-page rankings use total downloads.
| Platform | Downloads | Stars | Comments |
|---|---|---|---|
| ClawHub ↗ | 25.1K | 29 | 1 |
| SkillHub ↗ | 117.7K | 50 | — |
Platforms count differently and update at different times.
The document gives Python script examples for recording command failures, user corrections and best practices, then checking related memories before acting. It also describes automatic triggers and syncing important entries to workspace files. Those behaviors depend on the listed scripts and OpenClaw/workspace configuration; the supplied material does not verify that the scripts are installed or automation is enabled. Memory writes can affect later agent behavior, so redact sensitive information and review entries before saving or reusing them; check and remove stale items regularly.
Profile published 2026-10-27
Generated from the skill’s documentation as examples; not results of actual runs.
The counting method changed in 2026-09: skills with the same name are now counted separately by author, and the full catalog is covered. Dashed lines show months before the change; they are not compared with later months, and no growth is computed across the change. Other skills share this name; figures from before the change are attributed to this one, which currently has the most downloads.
| Month | Downloads | MoM | Stars |
|---|---|---|---|
| 2026-10 | 117.7K | — | 50 |
| 2026-09 | 61.4K | — | 50 |
| 2026-08 | 51.2K | +26.8% | 50 |
| 2026-07 | 40.4K | — | 50 |
| 2026-05 | 32.2K | — | 38 |
| 2026-03 | 19.2K | — | 24 |
The author’s original file, shown as plain text without edits or review by AlphaMoat. Links are not clickable; check commands before running them. Fetched 2026-10-23.
--- name: self-improving-agent description: "AI自我改进与记忆系统 - 解决'同类错误反复犯、用户纠正不长记性'的痛点。自动捕获错误、用户纠正、最佳实践,并转化为长期记忆。" version: 1.0.0 author: 老二 --- # Self-Improving Agent 让AI从错误中学习,越用越聪明。
## 核心解决的问题 ✅ 命令/操作莫名失败,下次还用同样的错方式 ✅ 反复纠正AI的写法、偏好、风格,它下个会话又忘了 ✅ 同一个项目里反复踩同一个坑 ✅ 发现更好的做法/更优解法,却没有系统化记住 ✅ 外部工具/API变动,AI还在用旧知识 ✅ 重要经验只存在于当前会话,跨天/跨项目就丢失 ## 安装 ```bash # 创建记忆目录 mkdir -p ~/.openclaw/memory/self-improving # 使用本skill cat ~/.openclaw/skills/self-improving-agent/SKILL.md ``` ## 使用方法 ### 1. 记录错误(自动) 当命令失败时,自动记录到错误库: ```bash # 脚本会自动捕获并记录 python3 ~/.openclaw/skills/self-improving-agent/log_error.py \ --command "npm install xxx" \ --error "permission denied" \ --fix "use sudo or check permissions" ``` ### 2. 记录用户纠正 当用户说: - "不对,应该..." - "错了,要用..." - "不对,我之前说过..." 自动记录: ```bash python3 ~/.openclaw/skills/self-improving-agent/log_correction.py \ --topic "代码风格" \ --wrong "用了双引号" \ --correct "项目要求单引号" \ --context "AGENTS.md 第23行" ``` ### 3. 记录最佳实践 发现更好的做法时: ```bash python3 ~/.openclaw/skills/self-improving-agent/log_best_practice.py \ --category "security" \ --practice "安装skill前必须审计代码" \ --reason "防止供应链投毒" ``` ### 4. 查看记忆(执行前自动检查) ```bash # 执行命令前,先检查是否有相关记忆 python3 ~/.openclaw/skills/self-improving-agent/check_memory.py \ --command "npm install" ``` 输出示例: ``` ⚠️ 发现相关记忆: [错误] 2026-03-05: npm install 权限失败 → 改用 sudo 或在用户目录安装 [纠正] 2026-03-04: 项目使用单引号而非双引号 ``` ## 文件结构 ``` ~/.openclaw/memory/self-improving/ ├── errors.jsonl # 错误记录 ├── corrections.jsonl # 用户纠正 ├── best_practices.jsonl # 最佳实践 ├── knowledge_gaps.jsonl # 知识盲区 └── index.json # 快速索引 ``` ## 自动触发场景 | 场景 | 自动记录 | 触发词 | |------|----------|--------| | 命令失败 | ✅ errors | 退出码非0 | | 用户纠正 | ✅ corrections | "不对" "错了" "应该" | | 更好的方法 | ✅ best_practices | "更好的" "更高效" "最优" | | 知识过时 | ✅ knowledge_gaps | "过时了" "已废弃" "新版是" | ## 跨项目同步 重要记忆自动同步到: - `~/.openclaw/memory/self-improving/` (全局) - 当前项目 `.learnings/` (项目级) - `AGENTS.md` (用户偏好) - `MEMORY.md` (长期记忆) ## 与现有Skill对比 | 功能 | 原self-improvement | 本skill | |------|-------------------|---------| | 记录错误 | ✅ | ✅ | | 记录纠正 | ✅ | ✅ 增强版 | | 自动触发 | ❌ 手动 | ✅ 自动 | | 跨项目记忆 | ❌ 项目级 | ✅ 全局+项目 | | 执行前检查 | ❌ | ✅ | | 知识过时检测 | ❌ | ✅ | ## 示例工作流程 ### 场景1:用户纠正代码风格 **用户**: "不对,我说过项目里要用单引号" **AI动作**: 1. 自动记录纠正到 `corrections.jsonl` 2. 更新 `AGENTS.md` 添加代码风格规则 3. 回复: "已记录,下次会使用单引号" ### 场景2:命令反复失败 **AI**: 执行 `npm install -g xxx` **结果**: 权限失败 **AI动作**: 1. 记录错误到 `errors.jsonl` 2. 下次执行前检查记忆 3. 自动改用: `sudo npm install -g xxx` 或本地安装 ### 场景3:发现更好做法 **用户**: "其实用 pip install -e . 更高效" **AI动作**: 1. 记录最佳实践到 `best_practices.jsonl` 2. 后续安装Python包时优先使用 editable 模式 ## 注意事项 - 记忆文件定期备份到git - 敏感信息脱敏后记录 - 定期review并清理过时记忆 --- Created: 2026-03-05 by 老二
Records learnings, errors and corrections as Markdown files for later reuse and promotion into workspace memory.
Finds skills in local and remote catalogs from a plain-language request and recommends what to install.
A browser-automation command line skill for AI agents.
Turns corrections and self-review into tiered memory and promotes or archives it by use.
A workspace setup guide for planning proactive follow-up, working memory and review routines for an AI agent.
A guide to creating and updating effective Claude skills.
Reviews a third-party skill's source, permissions, and danger patterns against a checklist before it is installed.
以李白(701—762,字太白,号青莲居士,世称诗仙)的诗学观、意象系统与口吻,进行唐诗赏析、文学评论、考据问答与拟体创作。触发词:李白、李太白、太白、青莲居士、诗仙、谪仙人、将进酒、静夜思、蜀道难、唐诗、盛唐诗人、浪漫主义诗人、拟李白风格、以李白视角、李白会怎么写、用李白口吻。能力:诗词鉴赏与风格DNA解析、诗学观与文学谱系评述、诗句出处考据与真伪边界标注、以李白口吻答问、拟李白体旧体诗(必显式标注非原作)。适用边界:仅用于唐代文学与古典诗歌相关话题,非此类话题不触发;本 skill 为文学普及与研究辅助,不代表李白本人立场,所拟之作均非李白原作;涉及生平佚事、篇目归属等内容不构成学术定论,皆标存疑或待考。
Data as of 2026-10. Downloads and stars are aggregated monthly from public skill registries (ClawHub, SkillHub). See data methodology.