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Dart Test Coverage

Community
kevmoo
dart-test-coverage

Understand and improve test coverage in a Dart package. Helps agents run coverage, interpret results, and identify missed lines.

Overview

Publisherkevmoo
Repositorydash_skills
Skill namedart-test-coverage
Stars
148
Forks
16
Bundled files
7
LicenseApache-2.0
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.

  • 7 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Dart 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.
    https://github.com/kevmoo/dash_skills/tree/main/skills/dart-test-coverage
  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/kevmoo/dash_skills.git /tmp/dash_skills
mkdir -p .claude/skills
cp -r /tmp/dash_skills/skills/dart-test-coverage .claude/skills/dart-test-coverage
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Dart 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 Dart 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 Dart 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.

Dart Test Coverage

Guidelines for running and interpreting test coverage in Dart packages.

When to use this skill

  • When asked to "check test coverage" or "improve coverage".
  • When you need to identify which parts of a library are untested.

When NOT to use (Abstention Guardrails)

Do NOT collect or demand test coverage for:

  • Generated Code: Code generated by builders (*.g.dart, *.freezed.dart, protobufs).
  • Platform-Specific FFI / OS Entrypoints: Low-level platform bindings or entrypoints that require specific physical hardware or OS services not available in the execution environment.
  • Example Applications & Tool Scripts: Standalone sample code under example/ or developer maintenance scripts under tool/ unless the package explicitly mandates 100% repository-wide coverage.
  • Failing Test Suites: If existing tests are failing under dart test, fix the broken tests first before collecting or reporting coverage.

Discovery

To find areas lacking test coverage:

Run Coverage Analysis

Follow the workflow to generate and interpret coverage data:

  1. Run Tests with Coverage: dart test --coverage=.dart_tool/coverage
  2. Interpret Results: Use the script or format_coverage as described in the Interpreting Results section to identify specific files and missed lines.

How to use this skill (The Workflow)

  1. Ensure tests pass by running dart test.
  2. Collect coverage by running dart test --coverage=.dart_tool/coverage.
  3. Interpret the results using the provided script or standard tools.
  4. Add tests to cover missed lines.

Running Coverage

Run the following command to collect coverage in JSON format:

bash
dart test --coverage=.dart_tool/coverage

[!NOTE] We use .dart_tool/coverage as the output directory because .dart_tool is typically already ignored in .gitignore files.

[!TIP] For projects with complex conditional logic, you can pass the --branch-coverage flag to dart test to collect branch-level coverage.

Interpreting Results

Option 1: Use the custom interpreter script

This repository includes a zero-dependency script that parses the raw JSON output and provides a summary of covered percentage and missed lines.

Run it from the project root (adjust path to script as needed):

bash
dart run skills/dart-test-coverage/scripts/interpret_coverage.dart .dart_tool/coverage <package_name>

Replace <package_name> with the name from pubspec.yaml.

Example Output:

package:my_pkg/src/file.dart: 50.0% (2/4 lines)
  Missed lines: 3, 4

Option 2: Use package:coverage

If package:test is installed, package:coverage is likely available as a transitive dependency. You can use its format_coverage tool.

To get a human-readable "pretty print" of the coverage:

bash
dart run coverage:format_coverage --in=.dart_tool/coverage --out=stdout --pretty-print --report-on=lib

This will output the file content with hit counts on the left (e.g., 0| for missed lines).

Best Practices for Reporting Results

When presenting coverage results to the user, follow these guidelines:

  1. State the high-level percentage first to give immediate context.
  2. Identify specific files and missed lines clearly.
  3. Translate line numbers to code: Don't just say "lines 3-6 are missed". Look at the source file and tell the user which functions or blocks are untested (e.g., "The divide function is missing coverage").
  4. Propose concrete fixes: Provide example test code that the user can immediately apply to cover the missed lines.
  5. Use tables for multi-file summaries: When reporting on multiple files, use a markdown table with columns for File, Coverage %, and Missed Lines to make the summary easy to scan.

Constraints

  • ALWAYS verify that tests pass before collecting coverage.
  • DO NOT commit the .dart_tool/coverage directory.
  • Focus coverage improvements on lib/ files, not test/ or generated files.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Dart Test Coverage AI skill do?

Understand and improve test coverage in a Dart package. Helps agents run coverage, interpret results, and identify missed lines.

Why use Dart Test Coverage on TypingMind?

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

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

Which AI models can use Dart 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 Dart Test Coverage?

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

Is the Dart Test Coverage AI skill free?

Yes. It is published on GitHub by kevmoo under the Apache-2.0 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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