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Fix Tests

OrganizationPopular
NeoLabHQ
fix-tests

Systematically fix all failing tests after business logic changes or refactoring

Overview

PublisherNeoLabHQ
Repositorycontext-engineering-kit
Skill namefix-tests
Stars
1.7K
Forks
159
Bundled files
Instructions only
LicenseGPL-3.0
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 NeoLabHQ on GitHub. Read the source before you install it.

Installation

Install the Fix Tests 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.
  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/NeoLabHQ/context-engineering-kit.git /tmp/context-engineering-kit
mkdir -p .claude/skills
cp -r /tmp/context-engineering-kit/antigravity/skills/fix-tests .claude/skills/fix-tests
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Fix Tests 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 Fix Tests 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 Fix Tests 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.

Fix Tests

User Arguments

User can provide to focus on specific tests or modules:

$ARGUMENTS

If nothing is provided, focus on all tests.

Context

After business logic changes, refactoring, or dependency updates, tests may fail because they no longer match the current behavior or implementation. This command orchestrates automated fixing of all failing tests using specialized agents.

Goal

Fix all failing tests to match current business logic and implementation.

Important Constraints

  • Focus on fixing tests - avoid changing business logic unless absolutely necessary
  • Preserve test intent - ensure tests still validate the expected behavior
  • "Analyse complexity of changes" -
    • if there 2 or more changed files, or one file with complex logic, then Do not write tests yourself - only orchestrate agents!
    • if there is only one changed file, and it's a simple change, then you can write tests yourself.

Workflow Steps

Preparation

  1. Read sadd skill if available

    • If available, read the sadd skill to understand best practices for managing agents
  2. Discover test infrastructure

    • Read @README.md and package.json (or equivalent project config)
    • Identify commands to run tests and coverage reports
    • Understand project structure and testing conventions
  3. Run all tests

    • Execute full test suite to establish baseline
  4. Identify all failing test files

    • Parse test output to get list of failing test files
    • Group by file for parallel agent execution

Analysis

  1. Verify single test execution
    • Choose any test file
    • Launch haiku agent with instructions to find proper command to run this only test file
      • Ask him to iterate until you can reliably run individual tests
    • After he complete try running a specific test file if it exists
    • This ensures agents can run tests in isolation

Test Fixing

  1. Launch developer agents (parallel)

    • Launch one agent per failing test file
    • Provide each agent with clear instructions:
      • Context: Why this test needs fixing (business logic changed)
      • Target: Which specific file to fix
      • Guidance: Read TDD skill (if available) for best practices how to write tests.
      • Resources: Read README and relevant documentation
      • Command: How to run this specific test file
      • Goal: Iterate until test passes
      • Constraint: Fix test, not business logic (unless clearly broken)
  2. Verify all fixes

    • After all agents complete, run full test suite again
    • Verify all tests pass
  3. Iterate if needed

    • If any tests still fail: Return to step 5
    • Launch new agents only for remaining failures
    • Continue until 100% pass rate

Success Criteria

  • All tests pass ✅
  • Test coverage maintained
  • Test intent preserved
  • Business logic unchanged (unless bugs found)

Agent Instructions Template

When launching agents, use this template:

The business logic has changed and test file {FILE_PATH} is now failing.

Your task:
1. Read the test file and understand what it's testing
2. Read TDD skill (if available) for best practices on writing tests.
3. Read @README.md for project context
4. Run the test: {TEST_COMMAND}
5. Analyze the failure - is it:
   - Test expectations outdated? → Fix test assertions
   - Test setup broken? → Fix test setup/mocks
   - Business logic bug? → Fix logic (rare case)
6. Fix the test and verify it passes
7. Iterate until test passes

Frequently asked questions

What does the Fix Tests AI skill do?

Systematically fix all failing tests after business logic changes or refactoring

Why use Fix Tests on TypingMind?

Because you install it once and use it with any model. Fix Tests 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 Fix Tests in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/NeoLabHQ/context-engineering-kit/tree/master/antigravity/skills/fix-tests. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Fix Tests?

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 Fix Tests?

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

Is the Fix Tests AI skill free?

Yes. It is published on GitHub by NeoLabHQ under the GPL-3.0 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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