Meta Debugger

AI-powered self-debugging system that identifies, analyzes, and fixes errors automatically. Learns from past errors, builds error patterns, generates fix sug...

This skill appears to implement the advertised debugging and auto-fix features, but there are a few red flags to consider before installing or enabling autonomous fixes: - Do not enable auto_fix in production yet. Test in a controlled environment where file changes are reversible (use source control or a sandbox). The skill can generate and apply patches; you should confirm exactly which files it will touch. - The SKILL.md 'pip install json traceback ast' line is wrong — these are stdlib modules. Treat this as a sign the docs or packaging may be sloppy; request clarification from the author or inspect the code yourself. - Inspect the full meta_debugger.py implementation (especially apply_fix, generate_fixes, and any persistence code) to see whether it writes files, runs shell commands, or makes network calls. The provided file sets a default storage path (~/.meta_debugger) and records error/context history — ensure sensitive inputs are filtered or not stored if that matters to you. - If you plan to run with auto_fix=True or allow the agent to invoke the skill autonomously, restrict its permissions (run under a limited user) and ensure backups/CI checks are in place so accidental or incorrect patches can be detected and rolled back. - If you need higher assurance, ask the owner for: (1) the full source code and a description of how apply_fix modifies files, (2) whether any remote endpoints exist for logging/telemetry, and (3) explicit data-retention and filtering policies for recorded contexts. If those answers are not available, run only in development/sandbox.

Type: OpenClaw Skill Name: meta-debugger Version: 1.0.0 The 'meta-debugger' skill is a framework for error logging, root cause analysis, and automated retry logic. While the documentation in SKILL.md describes advanced 'self-healing' capabilities like autonomous code patching, the actual implementation in meta_debugger.py is a skeleton where the 'apply_fix' method is a stub that only records success without performing any system modifications. The tool primarily functions as an error tracker and decorator-based retry mechanism, with no evidence of malicious intent, data exfiltration, or unauthorized execution.