agent-introspection-debugging
Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.
- Kind
- Skill
- Works with
- Claude Code, Codex
- Source
- affaan-m/ECC @ d3b8a3e90890
- Path
- skills/agent-introspection-debugging/SKILL.md
- License
- MIT
- Jobs
- Debugging
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# Agent Introspection Debugging Use this skill when an agent run is failing repeatedly, consuming tokens without progress, looping on the same tools, or drifting away from the intended task. This is a workflow skill, not a hidden runtime. It teaches the agent to debug itself systematically before escalating to a human. ## When to Activate - Maximum tool call / loop-limit failures - Repeated retries with no forward progress - Context growth or prompt drift that starts degrading output quality - File-system or environment state mismatch between expectation and reality - Tool failures that are likely recoverable with diagnosis and a smaller corrective action ## Scope Boundaries Activate this skill for: - capturing failure state before retrying blindly - diagnosing common agent-specific failure patterns - applying contained recovery actions - producing a structured human-readable debug report Do not use this skill as the primary source for: - feature verification after code changes; use `verification-loop` - framework-specific debugging when a narrower ECC skill already exists - runtime promises the current harness cannot enforce automatically ## Four-Phase Loop …