| name | agent-introspection-debugging |
| description | Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. USE WHEN an agent run fails, loops, or behaves unexpectedly and you need a repeatable post-mortem and recovery process. |
| origin | ECC |
| cluster | ai-agents-meta |
| version | 1.0.0 |
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
