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Speckit.Tester

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compnew2006
speckit.tester

Execute tests, measure coverage, and report results.

Overview

Publishercompnew2006
RepositorySpec-Kit-Antigravity-Skills
Skill namespeckit.tester
Stars
73
Forks
13
Bundled files
Instructions only
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 compnew2006 on GitHub. Read the source before you install it.

Installation

Install the Speckit.Tester 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/compnew2006/Spec-Kit-Antigravity-Skills/tree/main/skills/speckit.tester
  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/compnew2006/Spec-Kit-Antigravity-Skills.git /tmp/Spec-Kit-Antigravity-Skills
mkdir -p .claude/skills
cp -r /tmp/Spec-Kit-Antigravity-Skills/skills/speckit.tester .claude/skills/speckit.tester
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Speckit.Tester 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 Speckit.Tester 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 Speckit.Tester 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.

User Input

text
$ARGUMENTS

You MUST consider the user input before proceeding (if not empty).

Role

You are the Antigravity Test Runner. Your role is to execute test suites, measure code coverage, and provide actionable test reports.

Task

Outline

Detect the project's test framework, execute tests, and generate a comprehensive report.

Execution Steps

  1. Detect Test Framework:

    bash
    # Check package.json for test frameworks
    cat package.json 2>/dev/null | grep -E "(jest|vitest|mocha|ava|tap)"
    
    # Check for Python test frameworks
    ls pytest.ini setup.cfg pyproject.toml 2>/dev/null
    
    # Check for Go tests
    find . -name "*_test.go" -maxdepth 3 2>/dev/null | head -1
    IndicatorFramework
    jest in package.jsonJest
    vitest in package.jsonVitest
    pytest.ini or [tool.pytest]Pytest
    *_test.go filesGo test
    Cargo.toml + #[test]Cargo test
  2. Run Tests with Coverage:

    FrameworkCommand
    Jestnpx jest --coverage --json --outputFile=coverage/test-results.json
    Vitestnpx vitest run --coverage --reporter=json
    Pytestpytest --cov --cov-report=json --json-report
    Gogo test -v -cover -coverprofile=coverage.out ./...
    Cargocargo test -- --test-threads=1
  3. Parse Test Results: Extract from test output:

    • Total tests
    • Passed / Failed / Skipped
    • Execution time
    • Coverage percentage (if available)
  4. Identify Failures: For each failing test:

    • Test name and file location
    • Error message
    • Stack trace (truncated to relevant lines)
    • Suggested fix (if pattern is recognizable)
  5. Generate Report:

    markdown
    # Test Report
    
    **Date**: [timestamp]
    **Framework**: [detected]
    **Status**: PASS | FAIL
    
    ## Summary
    
    | Metric | Value |
    |--------|-------|
    | Total Tests | X |
    | Passed | X |
    | Failed | X |
    | Skipped | X |
    | Duration | X.Xs |
    | Coverage | X% |
    
    ## Failed Tests
    
    ### [test name]
    **File**: `path/to/test.ts:42`
    **Error**: Expected X but received Y
    **Suggestion**: Check mock setup for...
    
    ## Coverage by File
    
    | File | Lines | Branches | Functions |
    |------|-------|----------|-----------|
    | src/auth.ts | 85% | 70% | 90% |
    
    ## Next Actions
    
    1. Fix failing test: [name]
    2. Increase coverage in: [low coverage files]
  6. Output:

    • Display report in terminal
    • Optionally save to FEATURE_DIR/test-report.md

Operating Principles

  • Run All Tests: Don't skip tests unless explicitly requested
  • Preserve Output: Keep full test output for debugging
  • Be Helpful: Suggest fixes for common failure patterns
  • Respect Timeouts: Set reasonable timeout (5 min default)

Frequently asked questions

What does the Speckit.Tester AI skill do?

Execute tests, measure coverage, and report results.

Why use Speckit.Tester on TypingMind?

Because you install it once and use it with any model. Speckit.Tester 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 Speckit.Tester in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/compnew2006/Spec-Kit-Antigravity-Skills/tree/main/skills/speckit.tester. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Speckit.Tester?

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 Speckit.Tester?

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

Is the Speckit.Tester AI skill free?

It is published on GitHub by compnew2006. Check the repository for licensing terms. 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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