Self Improving Agent 3.0.5

Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Clau...

This skill appears to do what it says: it provides templates, a lightweight activator reminder, an error detector that watches tool output, and a helper to scaffold extracted skills. Before installing or enabling hooks: 1) Review the scripts (activator.sh, error-detector.sh, extract-skill.sh) to confirm you’re comfortable with their behavior; they do not exfiltrate data but do read runtime tool output and may encourage logging of command outputs to .learnings. 2) Prefer project-level (per-repo) hook configuration rather than user-global (~/.claude or ~/.openclaw) if you want to avoid injecting reminders across all sessions. 3) Check file permissions and ensure .learnings doesn't inadvertently store sensitive output (secrets, full stack traces) — treat it like a log. 4) If you enable the hook, test in a sandbox project first (or use the scripts' --dry-run where available). 5) If you have privacy or compliance concerns about storing tool outputs, do not enable PostToolUse hooks that automatically examine CLAUDE_TOOL_OUTPUT.

Type: OpenClaw Skill Name: self-improving-agent-3-0-5 Version: 1.0.0 The skill bundle implements a 'self-improvement' framework that allows an AI agent to log errors, user corrections, and new insights into a local `.learnings/` directory. It includes bash scripts (`activator.sh`, `error-detector.sh`) and OpenClaw hooks (`handler.js`) designed to inject reminders into the agent's context, encouraging it to document its performance. The `extract-skill.sh` utility provides a safe way to scaffold new skill templates with built-in protections against directory traversal. The logic is transparently aimed at improving agent reliability and project memory without any evidence of data exfiltration or unauthorized execution.