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Diagnosing Bugs

Skills#testing

A diagnosis loop for hard bugs and slowdowns.

From Matt Pocock's skills. When something is broken, throwing, failing or slow, your agent works through a structured diagnosis loop instead of guessing at fixes.

Install this skill

npx skills add https://github.com/mattpocock/skills --skill diagnosing-bugs

Runs the open-source skills CLI in your own terminal. It asks which agents to add the skill to. Read what it tells your agent to do before you install it.

Download skill (.zip)

Install for your agent

  • Claude Code

    Run this in your project

    npx skills add https://github.com/mattpocock/skills --skill diagnosing-bugs -a claude-code

    Add -g to install it for every project instead.

    Or ask Claude Code to do it

    Install the "diagnosing-bugs" skill from https://github.com/mattpocock/skills for Claude Code.
Copy the skill folder (the one containing SKILL.md, with any scripts or reference files next to it) into .claude/skills/ in this project.
Before copying, show me the SKILL.md and list any scripts it includes, and wait for me to confirm.

    Or copy the folder yourself

    Unzip the download into .claude/skills/ for this project, or ~/.claude/skills/ for all your projects.

    Picked up in the current session, no restart needed.

    Claude Code skills docs
  • Claude.ai

    Upload the ZIP

    1. In Settings > Capabilities, turn on Code execution and file creation.
    2. Go to Customize > Skills, press +, then Create skill.
    3. Choose Upload a skill and pick the ZIP you downloaded.

    Free, Pro and Max plans. On Team and Enterprise, an owner turns skills on in Organization settings first.

    Claude.ai skills docs
  • ChatGPT

    Upload the ZIP

    1. Open Skills in ChatGPT and select Create.
    2. Select Upload from your computer and pick the ZIP you downloaded.
    3. Wait for ChatGPT's safety scan. A skill marked Needs Review asks you to check it before use.

    Skills that rely on scripts or a terminal may not work unchanged in ChatGPT.

    ChatGPT skills docs
  • Codex

    Run this in your project

    npx skills add https://github.com/mattpocock/skills --skill diagnosing-bugs -a codex

    Add -g to install it for every project instead.

    Or ask Codex to do it

    Install the "diagnosing-bugs" skill from https://github.com/mattpocock/skills for Codex.
Copy the skill folder (the one containing SKILL.md, with any scripts or reference files next to it) into .agents/skills/ in this project.
Before copying, show me the SKILL.md and list any scripts it includes, and wait for me to confirm.

    Or copy the folder yourself

    Unzip the download into .agents/skills/ for this project, or ~/.agents/skills/ for all your projects.

    Restart Codex if the skill does not show up.

    Codex skills docs
  • Cursor

    Run this in your project

    npx skills add https://github.com/mattpocock/skills --skill diagnosing-bugs -a cursor

    Add -g to install it for every project instead.

    Or ask Cursor to do it

    Install the "diagnosing-bugs" skill from https://github.com/mattpocock/skills for Cursor.
Copy the skill folder (the one containing SKILL.md, with any scripts or reference files next to it) into .cursor/skills/ in this project.
Before copying, show me the SKILL.md and list any scripts it includes, and wait for me to confirm.

    Or copy the folder yourself

    Unzip the download into .cursor/skills/ for this project, or ~/.cursor/skills/ for all your projects.

    Run it by typing / and the skill name in chat.

    Cursor skills docs
  • GitHub Copilot

    Run this in your project

    npx skills add https://github.com/mattpocock/skills --skill diagnosing-bugs -a github-copilot

    Add -g to install it for every project instead.

    Or ask GitHub Copilot to do it

    Install the "diagnosing-bugs" skill from https://github.com/mattpocock/skills for GitHub Copilot.
Copy the skill folder (the one containing SKILL.md, with any scripts or reference files next to it) into .github/skills/ in this project.
Before copying, show me the SKILL.md and list any scripts it includes, and wait for me to confirm.

    Or copy the folder yourself

    Unzip the download into .github/skills/ for this project, or ~/.copilot/skills/ for all your projects.

    Works in Copilot CLI, the cloud agent and agent mode in VS Code and JetBrains.

    GitHub Copilot skills docs
  • Antigravity

    Run this in your project

    npx skills add https://github.com/mattpocock/skills --skill diagnosing-bugs -a antigravity

    Add -g to install it for every project instead.

    Or ask Antigravity to do it

    Install the "diagnosing-bugs" skill from https://github.com/mattpocock/skills for Antigravity.
Copy the skill folder (the one containing SKILL.md, with any scripts or reference files next to it) into .agents/skills/ in this project.
Before copying, show me the SKILL.md and list any scripts it includes, and wait for me to confirm.

    Or copy the folder yourself

    Unzip the download into .agents/skills/ for this project, or ~/.gemini/config/skills/ for all your projects.

    Antigravity skills docs
  • Gemini CLI

    Run this in your project

    npx skills add https://github.com/mattpocock/skills --skill diagnosing-bugs -a gemini-cli

    Add -g to install it for every project instead.

    Or ask Gemini CLI to do it

    Install the "diagnosing-bugs" skill from https://github.com/mattpocock/skills for Gemini CLI.
Copy the skill folder (the one containing SKILL.md, with any scripts or reference files next to it) into .gemini/skills/ in this project.
Before copying, show me the SKILL.md and list any scripts it includes, and wait for me to confirm.

    Or copy the folder yourself

    Unzip the download into .gemini/skills/ for this project, or ~/.gemini/skills/ for all your projects.

    Run /skills to check it was found.

    Gemini CLI skills docs
Installs
596.4K via skills.sh
GitHub
261.4K stars ↗
Last updated
4 Sept 2026
Licence
MIT

Security checks

Run by independent scanners and published on skills.sh. Their results, not a Viberation review.

  • Gen Agent Trust Hub Pass

    The skill provides a structured framework for diagnosing software bugs and regressions. It includes a strong focus on security best practices, such as explicit instructions for redacting secrets and credentials from logs and artifacts before processing. No malicious patterns, obfuscation, or unauthorized data exfiltration were detected.

    19 Aug 2026

  • Socket Pass

    No alerts

    19 Aug 2026

  • Snyk Pass

    Risk: LOW · No issues

    19 Aug 2026
What's inside (3 files)
  • agents/openai.yaml103 chars
  • scripts/hitl-loop.template.sh1.3K chars
  • SKILL.md8.5K chars

SKILL.md, first part. Shown as plain text.

---
name: diagnosing-bugs
description: Diagnosis loop for hard bugs and performance regressions. Use when the user says "diagnose"/"debug this", or reports something broken/throwing/failing/slow.
---

# Diagnosing Bugs

A discipline for hard bugs. Skip phases only when explicitly justified.

When exploring the codebase, read `CONTEXT.md` (if it exists) to get a clear mental model of the relevant modules, and check ADRs in the area you're touching.

## Redact

This skill has you show commands, outputs and captured artifacts. **Redact every secret first**: write `<REDACTED>` in its place. Build loops against env vars, so the credential stays in the environment rather than in what you show. Captured artifacts carry auth headers: quote only the lines that carry the signal.

If the redacted output is not enough to diagnose the bug, say so and ask the user.

## Phase 1: Build a feedback loop

**This is the skill.** Everything else is mechanical. If you have a **tight** pass/fail signal for the bug (one that goes red on _this_ bug), you will find the cause; bisection, hypothesis-testing, and instrumentation all just consume it. If you don't have one, no amount of staring at code will save you.

Spend disproportionate effort here. **Be aggressive. Be creative. Refuse to give up.**

### Ways to construct one, in roughly this order

1. **Failing test** at whatever seam reaches the bug: unit, integration, e2e.
2. **Curl / HTTP script** against a running dev server.
3. **CLI invocation** with a fixture input, diffing stdout against a known-good snapshot.
4. **Headless browser script** (Playwright / Puppeteer) that drives the UI and asserts on DOM/console/network.
5. **Replay a captured trace.** Save a real network request / payload / event log to disk; replay it through the code path in isolation.
6. **Throwaway harness.** Spin up a minimal subset of the system (one service, mocked deps) that exercises the bug code path with a single function call.
7. **Property / fuzz loop.** If the bug is "sometimes wrong output", run 1000 random inputs and look for the failure mode.
8. **Bisection harness.** If the bug appeared between two known states (commit, dataset, version), automate "boot at state X, check, repeat" so you can `git bisect run` it.
9. **Differential loop.** Run the same input through old-version vs new-version (or two configs) and diff outputs.
10. **HITL bash script.** Last resort. If a human must click, drive _them_ with `scripts/hitl-loop.template.sh` so the loop is still structured. Captured output feeds back to you.

Build the right feedback loop, and the bug is 90% fixed.

### Tighten the loop

Treat the loop as a product. Once you have _a_ loop, **tighten** it:

- Can I make it faster? (Cache setup, skip unrelated init, narrow the test scope.)
- Can I make the signal sharper? (Assert on the specific symptom, not "didn't crash".)
- Can I make it more deterministic? (Pin time, seed RNG, isolate filesystem, freeze network.)

A 30-second flaky loop is barely better than no loop; a 2-second deterministic one is tight, a debugging superpower.

### Non-deterministic bugs

The goal is not a clean repro but a **higher reproduction rate**. Loop the trigger 100×, parallelise, add stress, narrow timing windows, inject sleeps. A 50%-flake bug is debuggable; 1% is not, so keep raising the rate until it's debuggable.

### When you genuinely cannot build a loop

Stop and say so explicitly. List what you tried. Ask the user for: (a) access to whatever environment reproduces it, (b) a redacted captured artifact (HAR file, log dump, core dump, screen recording with timestamps), or (c) permission to add temporary production instrumentation. Do **not** proceed to hypothesise without a loop.

### Completion criterion: a tight loop that goes red

Phase 1 is done when the loop is **tight** and **red-capable**: you can name **one command** (a script path, a test invocation, a curl) that you have **already run at least once** (show the invocation and

Key info

Pricing
Open source
Category
Skills

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