Self Improving Agent

错误学习闭环：记录失败和纠正 → Pattern-Key 分类 → 定期复盘 → 整合长期记忆 → 防止再犯。 Use when: (1) 命令/操作意外失败且原因值得记录, (2) 用户纠正了错误（"不对"/"Actually..."/"你搞错了"）, (3) 用户要求的能力不存在（能力缺口信号）, (4) 外...

This skill appears to do what it says: remind the agent to log errors and convert repeated issues into persistent learnings. Before installing or enabling hooks globally, note: (1) the activator and error-detector are local scripts that will run with the same permissions as your agent and can write to your workspace (.learnings/, AGENTS.md, etc.); (2) enable the hooks only in the contexts you trust (project-level vs user-level); (3) review scripts (activator.sh, error-detector.sh, extract-skill.sh) and run extract-skill.sh with --dry-run to confirm behavior; (4) if you expect any cross-session operations (sessions_history/sessions_send), explicitly audit any runbooks that instruct the agent to use those APIs because they can access other sessions' data. Finally, be aware of minor metadata/version mismatches in the package (cosmetic) and verify origin if provenance is important.

Type: OpenClaw Skill Name: self-improving-learner Version: 1.0.1 The skill bundle implements a structured 'self-improvement' loop for AI agents, allowing them to log errors, user corrections, and new insights into local markdown files. It includes shell scripts (activator.sh, error-detector.sh) and OpenClaw hooks (handler.js/ts) that provide passive reminders to the agent without executing harmful commands or exfiltrating data. The skill-extraction script (extract-skill.sh) demonstrates security awareness by explicitly validating paths to prevent directory traversal.