Analyze pytest suites to reduce runtime and detect flaky tests.
npx skills add https://github.com/jorgealves/agent_skills --skill pytest-optimizer
Please help me install this Agent Skill. Skill: pytest-optimizer Source: https://github.com/jorgealves/agent_skills/tree/main/pytest-optimizer Command: npx skills add https://github.com/jorgealves/agent_skills --skill pytest-optimizer
Analyze and optimize pytest suites to improve speed, identify flaky tests, and increase coverage. Use to maintain high-quality, fast-running test pipelines.
Run: pytest-optimizer --project-path .
High-intent search queries and answers about installing and using this skill.
To optimize pytest suite performance, you need a valid Python environment to assess test structure and execution order. This identifies slow tests and detects flaky tests to reduce overall runtime and improve CI pipeline reliability.
Flaky test detection analyzes your pytest suite to pinpoint tests with inconsistent results. By identifying these unstable tests, you can apply recommendations to stabilize them, which directly improves test reliability and prevents false CI failures.
Yes, you can assess test coverage trends for legacy Python codebases. The analysis evaluates coverage metrics and suggests improvements for critical paths, helping you maintain high-quality test pipelines even in older projects.
Yes, you need a valid Python environment and a PyTest-based project to run the optimization analysis. The tool requires this setup to accurately assess your test structure, performance metrics, and coverage data.
To find the slowest tests in your pytest suite, run an analysis on your project path to identify performance bottlenecks. The optimization process then restructures the execution order to minimize overall test runtime.
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