SELF LEARNING SKILL V2

持续记录、分析并改正错误，实施预防措施，推动自我学习与迭代，确保不重复犯同类错误。

This skill is mostly documentation and templates for 'self-learning' behavior and is internally consistent, but it contains instructions that encourage the agent to search for authentication tokens, run GitHub/ClawHub auth flows, and perform autonomous daily/weekly tasks. Before installing: 1) Decide whether you are comfortable giving any agent the ability to search for tokens or credentials on your system — the skill suggests doing that even though it doesn't declare required env vars. 2) If you install, restrict the agent's runtime permissions or run it in a sandbox where it cannot access your home directory/credential stores. 3) Consider editing SKILL.md/EXECUTE.md to remove or require explicit user confirmation before any token-search or auth actions (e.g., require the user to provide a specific env var or confirm each GitHub/ClawHub operation). 4) Monitor logs/agent actions and avoid installing on accounts/machines that hold sensitive credentials. If you want a lower-risk alternative, keep this as a static template (read-only) and do token management manually.

Type: OpenClaw Skill Name: self-learning-skill-v2 Version: 1.0.0 The skill bundle implements a meta-learning framework for an AI agent to track errors, perform root cause analysis, and update its own capability matrix. It is classified as suspicious because SKILL.md and ERROR_LOG.md explicitly instruct the agent to "search for tokens in multiple locations" (建立 token 搜索机制，多位置查找) to resolve authentication failures. While this is plausibly intended to fix GitHub publishing issues, the broad instruction to hunt for credentials across the filesystem is a high-risk behavior. Additionally, EXECUTE.md defines scheduled automation tasks (e.g., daily checks at 22:00) that imply persistent background activity.