pytest-coverage

github/awesome-copilot · updated Apr 8, 2026

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$npx skills add https://github.com/github/awesome-copilot --skill pytest-coverage
0 commentsdiscussion
summary

Run pytest with coverage reporting to identify and eliminate untested code lines.

  • Generates annotated source files in cov_annotate/ directory, with ! markers indicating uncovered lines
  • Supports module-specific coverage checks via --cov=module_name and targeted test runs on specific test files
  • Workflow: run coverage, review annotated files for uncovered lines, write tests to cover gaps, repeat until 100% coverage achieved
skill.md

pytest-coverage

No content available.

how to use pytest-coverage

How to use pytest-coverage on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add pytest-coverage
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/github/awesome-copilot --skill pytest-coverage

The skills CLI fetches pytest-coverage from GitHub repository github/awesome-copilot and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/pytest-coverage

Reload or restart Cursor to activate pytest-coverage. Access the skill through slash commands (e.g., /pytest-coverage) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.531 reviews
  • Harper Ghosh· Dec 20, 2024

    pytest-coverage is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Pratham Ware· Dec 8, 2024

    I recommend pytest-coverage for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Sakshi Patil· Nov 27, 2024

    Useful defaults in pytest-coverage — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Xiao Nasser· Nov 23, 2024

    Registry listing for pytest-coverage matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Michael Mehta· Nov 11, 2024

    Solid pick for teams standardizing on skills: pytest-coverage is focused, and the summary matches what you get after install.

  • Chaitanya Patil· Oct 18, 2024

    pytest-coverage has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Xiao Okafor· Oct 14, 2024

    Keeps context tight: pytest-coverage is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Mateo Anderson· Oct 2, 2024

    We added pytest-coverage from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Min Agarwal· Sep 17, 2024

    pytest-coverage is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Aisha Abbas· Aug 24, 2024

    pytest-coverage reduced setup friction for our internal harness; good balance of opinion and flexibility.

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