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qt-coverage-workflow

Collect and analyze Python and C++ test coverage for Qt projects.

6|1|Updated Feb 16, 2026
Search Tags:#code quality#testing#python#c++#coverage#ci#qt
One-click install
npx skills add https://github.com/L3DigitalNet/Claude-Code-Plugins --skill qt-coverage-workflow
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: qt-coverage-workflow
Source: https://github.com/L3DigitalNet/Claude-Code-Plugins/tree/main/plugins/qt-suite/skills/qt-coverage-workflow
Command: npx skills add https://github.com/L3DigitalNet/Claude-Code-Plugins --skill qt-coverage-workflow

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill automates the process of measuring and improving code test coverage for both Python and C++ Qt projects, ensuring critical code paths are tested and reducing the risk of regressions.

Core Features & Use Cases

  • Full Coverage Loop: Manages the entire test coverage feedback loop: running instrumented tests, generating reports, identifying gaps, and facilitating targeted test generation.
  • Cross-Language Support: Works seamlessly for Python (using coverage.py) and C++ (using gcov + lcov).
  • CI Integration: Provides templates and guidance for integrating coverage reporting into CI pipelines (e.g., GitHub Actions).
  • Gap Analysis: Helps prioritize which uncovered code sections are most valuable to test based on business logic and risk.
  • Use Case: After running your test suite, this skill will analyze the coverage report, identify specific lines or branches that were missed, and provide actionable insights on how to write new tests to cover them, ultimately helping you reach your target coverage threshold.

Quick Start

Run the qt-coverage skill to analyze test coverage for your project.

Frequently Asked Questions about qt-coverage-workflow

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

FAQPage Schema
How do I automate code test coverage analysis for Qt projects using Python and C++?▼

Automating Qt test coverage involves running instrumented tests and generating reports using coverage.py for Python and gcov with lcov for C++ to identify untested code paths.

How do I integrate coverage reporting into a CI pipeline for Qt applications?▼

CI integration for Qt coverage reporting uses pipeline templates, such as GitHub Actions, to automatically run tests, parse coverage data, and enforce configurable threshold checks.

What is the best way to identify and fix coverage gaps in a Qt codebase?▼

Identifying coverage gaps requires analyzing generated reports to find missed lines or branches, then prioritizing new test generation based on business logic and regression risk.

Can I use gcov and lcov to measure C++ test coverage within a Qt project?▼

Yes, gcov and lcov measure C++ test coverage within Qt projects by instrumenting compiled binaries, executing test suites, and extracting detailed line and branch coverage data.

How does coverage.py support Python test coverage in a mixed-language Qt application?▼

Coverage.py supports Python test coverage in Qt applications by executing Python test suites, tracing executed lines, and generating detailed reports to highlight untested logic.

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