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Bun Test Coverage

Community
secondsky
bun-test-coverage

Use for test coverage with Bun, --coverage flag, lcov reports, thresholds, and CI integration.

Overview

Publishersecondsky
Repositoryclaude-skills
Skill namebun-test-coverage
Stars
219
Forks
31
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 secondsky on GitHub. Read the source before you install it.

Installation

Install the Bun Test Coverage 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/secondsky/claude-skills.git /tmp/claude-skills
mkdir -p .claude/skills
cp -r /tmp/claude-skills/plugins/bun/skills/bun-test-coverage .claude/skills/bun-test-coverage
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Bun Test Coverage 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 Bun Test Coverage 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 Bun Test Coverage 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.

Bun Test Coverage

Bun has built-in code coverage reporting without additional dependencies.

Enabling Coverage

bash
# Enable coverage
bun test --coverage

# With threshold (fail if below)
bun test --coverage --coverage-threshold 80

Configuration in bunfig.toml

toml
[test]
coverage = true
coverageThreshold = 0.8  # 80% minimum
coverageDir = "./coverage"

# Patterns to ignore
coverageSkipTestFiles = true

Coverage Output

------------------|---------|---------|-------------------
File              | % Funcs | % Lines | Uncovered Line #s
------------------|---------|---------|-------------------
All files         |   85.71 |   89.23 |
 src/index.ts     |  100.00 |  100.00 |
 src/utils.ts     |   75.00 |   82.35 | 23-25, 41-43
 src/api.ts       |   80.00 |   85.00 | 67, 89-92
------------------|---------|---------|-------------------

Coverage Reporters

bash
# Default console output
bun test --coverage

# Generate lcov report
bun test --coverage --coverage-reporter=lcov

# Multiple reporters
bun test --coverage --coverage-reporter=text --coverage-reporter=lcov

Available Reporters

ReporterOutput
textConsole table (default)
lcovcoverage/lcov.info for CI tools
jsoncoverage/coverage.json

Coverage Thresholds

Set minimum coverage requirements:

bash
# Fail if coverage < 80%
bun test --coverage --coverage-threshold 80

# Per-metric thresholds in bunfig.toml
toml
[test]
coverage = true
coverageThreshold = {
  lines = 80,
  functions = 75,
  branches = 70
}

Excluding Files

toml
[test]
coverage = true

# Skip test files from coverage
coverageSkipTestFiles = true

# Patterns to exclude
coverageIgnore = [
  "**/*.test.ts",
  "**/fixtures/**",
  "**/mocks/**"
]

CI Integration

GitHub Actions

yaml
- name: Run tests with coverage
  run: bun test --coverage --coverage-reporter=lcov

- name: Upload coverage to Codecov
  uses: codecov/codecov-action@v5
  with:
    files: ./coverage/lcov.info

Output Directory

bash
# Custom output directory
bun test --coverage --coverage-dir=./reports/coverage

Programmatic Coverage

typescript
import { test, expect } from "bun:test";

// Get coverage data programmatically
const coverage = Bun.coverage;

// Access after tests complete
process.on("exit", () => {
  console.log(coverage.getCoverageData());
});

Common Errors

ErrorCauseFix
Coverage threshold not metCoverage below thresholdIncrease test coverage
No coverage dataFiles not executedCheck test includes file
lcov not foundMissing reporterAdd --coverage-reporter=lcov

Best Practices

  1. Set realistic thresholds - Start at 60%, increase gradually
  2. Exclude generated files - Mock files, type definitions
  3. Focus on critical paths - Business logic over boilerplate
  4. Run in CI - Prevent coverage regression

When to Load References

Load references/reporters.md when:

  • Custom reporter configuration
  • CI/CD integration details
  • Codecov/Coveralls setup

Frequently asked questions

What does the Bun Test Coverage AI skill do?

Use for test coverage with Bun, --coverage flag, lcov reports, thresholds, and CI integration.

Why use Bun Test Coverage on TypingMind?

Because you install it once and use it with any model. Bun Test Coverage 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 Bun Test Coverage in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/secondsky/claude-skills/tree/main/plugins/bun/skills/bun-test-coverage. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Bun Test Coverage?

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 Bun Test Coverage?

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

Is the Bun Test Coverage AI skill free?

Yes. It is published on GitHub by secondsky 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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