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Autonomous Bug Fix

Community
andreaswasita
autonomous-bug-fix

Reproduces, diagnoses, fixes, and verifies bugs unaided.

Overview

Publisherandreaswasita
Repositorycopilot-agents-dojo
Skill nameautonomous-bug-fix
Stars
54
Forks
15
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by andreaswasita on GitHub. Read the source before you install it.

Installation

Install the Autonomous Bug Fix AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/andreaswasita/copilot-agents-dojo/tree/main/skills/autonomous-bug-fix
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/andreaswasita/copilot-agents-dojo.git /tmp/copilot-agents-dojo
mkdir -p .claude/skills
cp -r /tmp/copilot-agents-dojo/skills/autonomous-bug-fix .claude/skills/autonomous-bug-fix
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Autonomous Bug Fix in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Autonomous Bug Fix on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Autonomous Bug Fix is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Autonomous Bug Fix Skill

Walks the agent through the full reproduce → diagnose → fix → verify cycle on its own, without asking the user for navigation help, log-reading instructions, or test commands. Does NOT cover net-new feature work — for that use plan-before-code and executing-plans.

When to Use

  • User reports a bug, regression, or unexpected behavior.
  • CI is red on a branch you own.
  • An error or warning appears in logs.
  • A previously working feature stopped working.
  • The user says "this is broken," "it doesn't work," or similar.

Prerequisites

  • Read access to the failing component (use glob / grep to locate it).
  • The powershell tool to run tests, git, and reproduction commands.
  • A clean working tree on a feature branch (use using-git-worktrees if needed).
  • verify-before-done skill loaded — you'll invoke it at the end.

How to Run

text
1. Reproduce  → locate the code, run the failing path, confirm with evidence.
2. Diagnose   → trace from symptom to root cause; check recent changes.
3. Fix        → minimal change at the root cause + a regression test.
4. Verify     → re-run reproduction + full suite via `verify-before-done`.

Quick Reference

PhaseActionTool
Find codeSearch by symbol or file patterngrep, glob
Read codeInspect the failing pathview
ReproduceRun failing command/testpowershell
DiagnoseRecent changes / blamepowershell → git log -20 --oneline, git blame <path>
EditMinimal, root-cause fixedit
Add testRegression testcreate or edit under tests/
VerifyRe-run reproduction + full suitepowershell, then verify-before-done

Procedure

Step 1: Reproduce

Find the relevant code yourself — grep for the symbol, glob for the path. Do not ask the user "which file is this in?"

Run the failing path via the powershell tool. If no failing test exists, write a minimal one that captures the bug. Confirm reproduction with concrete evidence (stack trace, exit code, log line).

If you can't reproduce:

  • Check for environment-specific behavior (OS, Node/Python version).
  • Look for race conditions or state-dependent paths.
  • Ask the user for clarification only as a last resort, and only with specific questions.

Step 2: Diagnose Root Cause

Read the error message and stack trace before doing anything else — they exist for a reason. Trace from the user-visible symptom back to the root cause:

bash
# via the `powershell` tool
git log -20 --oneline
git blame path/to/suspect.ts
git diff HEAD~5 -- path/to/suspect.ts

Stop at the root cause, not the first thing that looks suspicious. "Why did this break?" — not "what broke?"

Step 3: Fix at the Root

Edit with precision via the edit tool:

  • Change only what needs to change. Bigger diffs hide bigger bugs.
  • Fix the root cause, never the symptom. Swallowing an exception is not a fix.
  • Add a regression test that fails without the fix and passes with it.
  • Check whether the same root cause exists elsewhere (grep for the pattern). If yes, fix those too or log them in tasks/lessons.md for follow-up.

Step 4: Verify

Hand off to the verify-before-done skill:

  • Re-run the reproduction. The error must be gone.
  • Run the full test suite. No regressions.
  • Record evidence in tasks/todo.md under the task.

Step 5: Rollback If Verification Fails

If verification fails after your fix:

  1. Reset the working tree (git checkout -- . or git stash via powershell).
  2. Log the failed attempt in tasks/lessons.md with the root-cause analysis you had.
  3. Re-plan with a different approach via plan-before-code.
  4. Never push broken code hoping someone catches it later.

Pitfalls

  • DO NOT ask the user "which file is it in?" or "how do I run the tests?" Use grep/glob/view/powershell to discover it.
  • DO NOT apply a band-aid (catch-and-swallow, ignore the warning). Fix the root cause.
  • DO NOT fix the symptom. A login button that fails because of a missing provider is a provider bug, not a button bug.
  • DO NOT skip the regression test. Without one, the bug comes back in 3 months.
  • DO NOT push without verification. An unverified fix is often worse than no fix.
  • DO NOT abandon failed attempts silently. Log them in tasks/lessons.md.

Verification

  • Reproduction was confirmed with concrete evidence before any fix.
  • Root cause is identified in writing (in commit message or tasks/todo.md).
  • Regression test added that fails on main and passes on the branch.
  • verify-before-done checklist passed.
  • If similar patterns exist elsewhere, they are fixed or logged.

Frequently asked questions

What does the Autonomous Bug Fix AI skill do?

Reproduces, diagnoses, fixes, and verifies bugs unaided.

Why use Autonomous Bug Fix on TypingMind?

Because you install it once and use it with any model. Autonomous Bug Fix is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Autonomous Bug Fix in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/andreaswasita/copilot-agents-dojo/tree/main/skills/autonomous-bug-fix. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Autonomous Bug Fix?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Autonomous Bug Fix?

As many as you like. As long as a model supports skills, you can use Autonomous Bug Fix with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Autonomous Bug Fix AI skill free?

Yes. It is published on GitHub by andreaswasita under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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