agent-introspection-debugging

Agent self-debugging systematically logs error details and environment assumptions to capture failures, matches failure patterns to known causes like loops, and applies minimal safe fixes to resolve errors without extensive reprocessing.

Diagnose environment mismatches causing AI agent failures by using self-diagnosis to verify state assumptions, match failure patterns to known causes, and apply contained recovery actions to restore process stability.

Automate error recovery for AI agents using a structured self-debugging workflow that applies minimal actions to resolve errors, matches failure patterns to known causes, and generates introspection reports for human review or further automation.

No external dependencies are required to enable agent self-debugging. The skill operates independently using internal scripts and references to systematically log error details, diagnose root causes, and generate recovery reports.

Generate debug reports for recurring agent failures by triggering self-diagnosis to systematically log error details, match failure patterns to known causes, and output detailed introspection reports for human review.