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/structured-debug

AI DevKit · Guide structured debugging before code changes by clarifying expected behavior, reproducing issues, identifying likely root causes, and agreeing on a fix plan with validation steps. Use when users ask to debug bugs, investigate regressions, triage incidents, diagnose

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ai-devkit
1.6k24 skills
Install
$ npx -y skills add codeaholicguy/ai-devkit --skill structured-debug --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/structured-debug

Context preview

The summary Claude sees to decide when to auto-load this skill.

AI DevKit · Guide structured debugging before code changes by clarifying expected behavior, reproducing issues, identifying likely root causes, and agreeing on a fix plan with validation steps. Use when users ask to debug bugs, investigate regressions, triage incidents, diagnose

SKILL.md

structured-debug.SKILL.md
name: structured-debug
description: AI DevKit · Guide structured debugging before code changes by clarifying expected behavior, reproducing issues, identifying likely root causes, and agreeing on a fix plan with validation steps. Use when users ask to debug bugs, investigate regressions, triage incidents, diagnose failing behavior, handle failing tests, analyze production incidents, investigate error spikes, or run root cause analysis (RCA).

Local Debugging Assistant

Debug with an evidence-first workflow before changing code.

Hard Rule

  • Do not modify code until the user approves a selected fix plan.

Workflow

1. Clarify

  • Restate observed vs expected behavior in one concise diff.
  • Confirm scope and measurable success criteria.
  • Before investigating, search for similar past incidents: `npx ai-devkit@latest memory search --query "<observed behavior>" --tags "debug,root-cause"`

2. Reproduce

  • Capture minimal reproduction steps.
  • Capture environment fingerprint: runtime, versions, config flags, data sample, and platform.

3. Hypothesize and Test For each hypothesis, include:

  • Predicted evidence if true.
  • Disconfirming evidence if false.
  • Exact test command or check.
  • Prefer one-variable-at-a-time tests.

4. Plan

  • Present fix options with risks and verification steps.
  • Recommend one option and request approval.

Validation

  • Confirm a pre-fix failing signal exists.
  • Confirm post-fix success using the `verify` skill — including regression verification for bug fixes.
  • Summarize remaining risks and follow-ups.
  • Store root cause and fix for future sessions: `npx ai-devkit@latest memory store --title "<root cause>" --content "<diagnosis and fix>" --tags "debug,root-cause"`

Task Tracing

If task tracing is usable, choose a short kebab-case debug task name when no task name exists, then use `task` optionally: record repro/final results as `evidence`, the current hypothesis as `next`, and blockers only when they materially affect progress. Never block debugging because task tracing is unavailable.

Red Flags and Rationalizations

| Rationalization | Why It's Wrong | Do Instead | |---|---|---| | "I already know the cause" | Assumptions skip evidence | Reproduce and prove it first | | "This is urgent, just fix it" | A wrong fix wastes more time | 10 minutes of diagnosis saves hours | | "The fix is obvious from the stack trace" | Stack traces show symptoms, not causes | Trace backward to the root cause |

Output Template

Use this response structure:

  • Observed vs Expected
  • Repro and Environment
  • Hypotheses and Tests
  • Options and Recommendation
  • Validation Plan and Results
  • Open Questions
Read more
Ships withai-devkit

The control plane for AI coding agents. AI DevKit gives Claude Code, Codex CLI, Gemini CLI, opencode, Pi, Cursor, GitHub Copilot, Devin, and other coding agents one local-first operating layer: one config, one console, local memory retrieval, cross-agent

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Repo: codeaholicguy/ai-devkit

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