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Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when…
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.
$ npx -y skills add affaan-m/ECC --skill agent-introspection-debugging --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/agent-introspection-debuggingContext preview
The summary Claude sees to decide when to auto-load this skill.
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.
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 and you need a reproducible diagnosis instead of a retry. metadata: origin: ECC
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.
Activate this skill for:
Do not use this skill as the primary source for:
Before trying to recover, record the failure precisely.
Capture:
Minimum capture template:
## Failure Capture - Session / task: - Goal in progress: - Error: - Last successful step: - Last failed tool / command: - Repeated pattern seen: - Environment assumptions to verify:
Match the failure to a known pattern before changing anything.
| Pattern | Likely Cause | Check | | --- | --- | --- | | Maximum tool calls / repeated same command | loop or no-exit observer path | inspect the last N tool calls for repetition | | Context overflow / degraded reasoning | unbounded notes, repeated plans, oversized logs | inspect recent context for duplication and low-signal bulk | | `ECONNREFUSED` / timeout | service unavailable or wrong port | verify service health, URL, and port assumptions | | `429` / quota exhaustion | retry storm or missing backoff | count repeated calls and inspect retry spacing | | file missing after write / stale diff | race, wrong cwd, or branch drift | re-check path, cwd, git status, and actual file existence | | tests still failing after “fix” | wrong hypothesis | isolate the exact failing test and re-derive the bug |
Diagnosis questions:
Recover with the smallest action that changes the diagnosis surface.
Safe recovery actions:
Do not claim unsupported auto-healing actions like “reset agent state” or “update harness config” unless you are actually doing them through real tools in the current environment.
Contained recovery checklist:
## Recovery Action - Diagnosis chosen: - Smallest action taken: - Why this is safe: - What evidence would prove the fix worked:
End with a report that makes the recovery legible to the next agent or human.
## Agent Self-Debug Report - Session / task: - Failure: - Root cause: - Recovery action: - Result: success | partial | blocked - Token / time burn risk: - Follow-up needed: - Preventive change to encode later:
Prefer these interventions in order:
1. Restate the real objective in one sentence. 2. Verify the world state instead of trusting memory. 3. Shrink the failing scope. 4. Run one discriminating check. 5. Only then retry.
Bad pattern:
Good pattern:
When this skill is active, do not end with “I fixed it” alone.
Always provide:
Your agent can write code, but ECC gives it a coordinated engineering system and toolbox: it plans before it builds, verifies changes with tests, reviews its own work from a fresh context, remembers what matters, and turns repeated wins into reusable skills
Repo: affaan-m/ECC
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