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agent-introspection-debugging

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by Api.AirforcePrepends a system promptAI & Agent Building000 uses202,700

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports.

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What this skill does

When applied, it prepends a system prompt before your request is sent — no extra calls and no change to how you are billed beyond the added tokens.

---
name: agent-introspection-debugging
description: Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports.
origin: ECC
---

# 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

### Phase 1: Failure Capture

Before trying to recover, record the failure precisely.

Capture:
- error type, message, and stack trace when available
- last meaningful tool call sequence
- what the agent was trying to do
- current context pressure: repeated prompts, oversized pasted logs, duplicated plans, or runaway notes
- current environment assumptions: cwd, branch, relevant service state, expected files

Minimum capture template:

```markdown
## Failure Capture
- Session / task:
- Goal in progress:
- Error:
- Last successful step:
- Last failed tool / command:
- Repeated pattern seen:
- Environment ass

Use this skill

Per request

Add a "skill" field with the skill’s ID to your chat completion request. It is applied server-side before your prompt is sent — no extra calls.

{
  "model": "gpt-4o-mini",
  "skill": "imp-abacea57-9e62-47a8-aa45-26ae45813136",
  "messages": [{ "role": "user", "content": "…" }]
}
Always on — no field to send

Install the skill, enable it in your dashboard and (optionally) limit it to specific models. It then applies automatically to every matching request — with no "skill" field to send each time.

Set it up in your dashboard