Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add HolobiomicsLab/asb-skill-collections --skill pytest-unit-test-execution-and-coverage-reportinggit clone --depth 1 https://github.com/HolobiomicsLab/asb-skill-collectionsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/holobiomicslab/asb-skill-collections/pytest-unit-test-execution-and-coverage-reporting)<a href="https://agentmods.dev/skills/holobiomicslab/asb-skill-collections/pytest-unit-test-execution-and-coverage-reporting"><img src="https://agentmods.dev/badge/skills/holobiomicslab/asb-skill-collections/pytest-unit-test-execution-and-coverage-reporting/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/holobiomicslab/asb-skill-collections/pytest-unit-test-execution-and-coverage-reporting"><img src="https://agentmods.dev/badge/skills/holobiomicslab/asb-skill-collections/pytest-unit-test-execution-and-coverage-reporting.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00048 | $0.01333 |
| Opus 5 | $0.00024 | $0.00666 |
| Sonnet 5 | $0.00010 | $0.00267 |
| Haiku 4.5 | $0.00005 | $0.00133 |
Grade A, and why
pytest-unit-test-execution-and-coverage-reporting scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
pytest-unit-test-execution-and-coverage-reporting
Summary
Execute unit tests on a Python package using pytest, measure code coverage with pytest-cov, and report both functional correctness and coverage metrics. This skill verifies that library functions behave as expected and identifies untested code paths.
When to use
Apply this skill after implementing or modifying Python library functions (such as utility functions in cooltools.lib subpackages) to verify correctness and identify gaps in test coverage before merging changes or releasing code.
When NOT to use
- Package contains no unit tests or test infrastructure—establish test files first before running pytest.
- Testing integration behavior or end-to-end workflows requiring external dependencies, data files, or services—use integration test frameworks or fixtures instead.
- Code coverage is not a project requirement or concern—pytest can still execute tests, but the -cov extension adds overhead unnecessary in purely pass/fail scenarios.
Inputs
- Python package source code with unit tests
- pytest configuration file (pytest.ini or setup.cfg with [tool:pytest] section, optional)
- Test files following pytest naming conventions (test_*.py or *_test.py)
Outputs
- Unit test execution report (PASSED/FAILED status per test)
- Code coverage percentage and per-file coverage metrics
- Coverage report showing line-by-line execution status
How to apply
Navigate to the root of the repository and run pytest with the pytest-cov extension to execute all unit tests and simultaneously measure code coverage. The framework will discover and execute all test files matching standard naming conventions (test_*.py or *_test.py), report pass/fail status for each test, and generate a coverage report showing which lines and branches were executed during testing. Examine the coverage output to identify functions or code paths not yet covered by tests, and use those results to guide additional test writing before considering the test suite complete.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 107 lines · 48 tokens per session scan A fbd3d882c440
pytest-unit-test-execution-and-coverage-reporting is a skill published in the GitHub repository HolobiomicsLab/asb-skill-collections (15 stars, last pushed 2d ago), licensed Apache-2.0. It adds 48 tokens to every session and 1,333 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-06.
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