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Structured self-debugging workflow for AI agent failures.
This skill provides a systematic approach for AI agents to debug themselves when they encounter failures. It captures the failure state, diagnoses the issue, applies contained recovery actions, and generates a structured report. Ideal for situations where an agent is stuck in a loop, consuming resources without progress, or drifting from its intended task. It helps ensure that agents can recover effectively without unnecessary retries, making the debugging process more efficient and reproducible.