Install any skill in seconds. Free to start, no credit card required.
Get Started Free →Expert pytest framework for Python unit, integration, and functional testing
.claude/skills/a5c-ai-pytest-testing/SKILL.md| Model | Eval pass | Runs |
|---|---|---|
| gemini-3.6-flash | 100% | 20 |
| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 47% | 0% |
| case-03 | ✗→✓ | ▲ Improved | -1% | 0% |
| case-13 | ✗→✓ | ▲ Improved | -44% | 0% |
| case-14 | ✗→✓ | ▲ Improved | -63% | 0% |
| case-15 | ✗→✓ | ▲ Improved | -60% | 0% |
This skill provides expert-level capabilities for pytest-based testing, enabling comprehensive Python testing with fixtures, parametrization, and plugin integration.
automation-framework.js - Test framework setupapi-testing.js - API test implementationcontinuous-testing.js - CI/CD integrationshift-left-testing.js - Early testing integrationpytest - Test frameworkpytest-cov - Coverage pluginpytest-xdist - Parallel executionpytest-html - HTML reportsjavascript{ kind: 'skill', skill: { name: 'pytest-testing', context: { action: 'execute-tests', testPath: 'tests/', markers: ['unit', 'integration'], coverage: true, parallel: 4 } } }
The skill respects pytest.ini, pyproject.toml, or setup.cfg configuration and can override settings as needed.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 6,693 | 7,895 | +18% | 1 | 1 | 0% | 1,193 | 1,758 | +47% | 0 | 0 | — |
case-02 | pass→pass | 11,562 | 11,176 | -3% | 1 | 1 | 0% | 1,982 | 2,488 | +26% | 0 | 0 | — |
case-03 | fail→pass | 6,434 | 3,870 | -40% | 1 | 1 | 0% | 1,156 | 1,145 | -1% | 0 | 0 | — |
case-04 | pass→pass | 8,426 | 5,837 | -31% | 1 | 1 | 0% | 1,265 | 1,461 | +15% | 0 | 0 | — |
case-05 | pass→pass | 14,948 | 14,878 | -0% | 1 | 1 | 0% | 2,202 | 3,193 | +45% | 0 | 0 | — |
case-06 | pass→pass | 9,929 | 9,066 | -9% | 1 | 1 | 0% | 2,170 | 1,917 | -12% | 0 | 0 | — |
case-07 | pass→pass | 2,193 | 3,268 | +49% | 1 | 1 | 0% | 365 | 983 | +169% | 0 | 0 | — |
case-08 | fail→fail | 11,987 | 11,613 | -3% | 1 | 1 | 0% | 2,386 | 2,625 | +10% | 0 | 0 | — |
case-09 | pass→pass | 9,555 | 8,001 | -16% | 1 | 1 | 0% | 1,570 | 1,893 | +21% | 0 | 0 | — |
case-10 | pass→pass | 9,425 | 9,390 | -0% | 1 | 1 | 0% | 1,757 | 2,017 | +15% | 0 | 0 | — |
case-11 | pass→pass | 7,893 | 4,420 | -44% | 1 | 1 | 0% | 1,427 | 1,195 | -16% | 0 | 0 | — |
case-12 | pass→pass | 5,142 | 4,331 | -16% | 1 | 1 | 0% | 881 | 1,222 | +39% | 0 | 0 | — |
case-13 | fail→pass | 6,905 | 1,725 | -75% | 1 | 1 | 0% | 1,157 | 650 | -44% | 0 | 0 | — |
case-14 | fail→pass | 10,574 | 1,583 | -85% | 1 | 1 | 0% | 1,713 | 626 | -63% | 0 | 0 | — |
case-15 | fail→pass | 9,843 | 1,889 | -81% | 1 | 1 | 0% | 1,612 | 652 | -60% | 0 | 0 | — |
case-16 | fail→pass | 13,706 | 1,588 | -88% | 1 | 1 | 0% | 1,924 | 659 | -66% | 0 | 0 | — |
case-17 | fail→pass | 9,118 | 3,147 | -65% | 1 | 1 | 0% | 1,434 | 809 | -44% | 0 | 0 | — |
case-18 | pass→pass | 6,548 | 4,081 | -38% | 1 | 1 | 0% | 965 | 901 | -7% | 0 | 0 | — |
case-19 | pass→pass | 9,655 | 8,649 | -10% | 1 | 1 | 0% | 1,595 | 2,022 | +27% | 0 | 0 | — |
case-20 | pass→pass | 11,390 | 9,216 | -19% | 1 | 1 | 0% | 2,125 | 2,122 | -0% | 0 | 0 | — |
case-21 | pass→pass | 7,155 | 9,523 | +33% | 1 | 1 | 0% | 1,430 | 1,988 | +39% | 0 | 0 | — |
case-22 | pass→pass | 12,268 | 9,576 | -22% | 1 | 1 | 0% | 1,919 | 2,455 | +28% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +32 percentage points is the difference between those two pass rates over the 22 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.