cells-coverage

Analyzes coverage artifacts and test results to pinpoint gaps and failures.

Updated Aug 27, 2026
One-click install
npx skills add https://github.com/PixelDroid19/cells-agents --skill cells-coverage
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: cells-coverage
Source: https://github.com/PixelDroid19/cells-agents/tree/main/skills/cells-coverage
Command: npx skills add https://github.com/PixelDroid19/cells-agents --skill cells-coverage

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

Triage and prioritize test coverage issues by automatically analyzing coverage artifacts (lcov, HTML reports) and failing test outputs, reducing manual investigation time.

Core Features & Use Cases

  • Automated coverage triage: Prioritize uncovered branches and failing tests.
  • Evidence-driven rerun planning: Generate focused tests to close gaps.
  • Deterministic reports: Produce concise AI-friendly summaries from lcov and HTML reports.

Quick Start

Run a targeted coverage triage on the latest test run to surface the highest-impact uncovered branches.

Frequently Asked Questions about cells-coverage

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I triage test coverage gaps from lcov reports in a CI pipeline?

To triage test coverage gaps from lcov reports, this analysis process evaluates coverage artifacts and failing test outputs to pinpoint uncovered branches, generating AI-ready summaries that prioritize areas needing targeted tests.

What is the best way to prioritize failing tests and uncovered branches?

The best way to prioritize failing tests and uncovered branches is through automated coverage triage, which analyzes test results to surface the highest-impact gaps and suggests focused tests to close them.

Can I generate HTML coverage pages and AI-friendly summaries from local test runs?

Yes, you can generate HTML coverage pages and compact AI-friendly summaries from local test runs by processing lcov reports, which provide deterministic evidence for rerun planning and gap analysis.

Does this coverage triage approach work without external dependencies?

Yes, this coverage triage approach works without external dependencies, using internal scripts and references to analyze lcov and HTML reports directly from your CI pipelines or local environments.

How do I plan focused test reruns based on coverage artifacts?

You can plan focused test reruns by using the generated AI-ready summaries from your coverage artifacts, which identify specific uncovered branches and suggest targeted tests to efficiently close coverage gaps.