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pytest-best-practices

Expert guidance for writing high-quality pytest tests. Use when writing tests, setting up fixtures, parametrizing, mocking, or reviewing test code.

69

Quality

85%

Does it follow best practices?

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SKILL.md
Quality
Evals
Security

Quality

Content

86%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A tight, well-structured skill body that progressively discloses detail into real reference files and gives mostly executable guidance. The main gap is the absence of an explicit run-test/fix-failures feedback loop and a few patterns lacking runnable examples.

Suggestions

Add a short run-test feedback loop in the body or quick reference, e.g. 'pytest -x -> read failure -> fix -> rerun', to strengthen workflow clarity.

Add minimal runnable snippets for the most common patterns (pytest.raises, @pytest.mark.parametrize, mocker.patch) instead of listing them only in the table.

Clarify when to prefer unit/ vs integration/ directories in the routing table so users pick the right location without guessing.

DimensionReasoningScore

Conciseness

The body is lean and well-organized into objective, principles, quick reference, routing, and dependencies; it assumes Claude's competence and contains no padding or explanations of basic concepts.

5 / 5

Actionability

Provides executable commands, a concrete directory structure, and a pattern/marker reference table, but several quick-reference patterns (e.g. pytest.raises, mocker.patch) are listed without runnable example snippets, leaving minor gaps.

4 / 5

Workflow Clarity

A clear routing table sequences the user to the right reference per task and a commands block covers common runs, but there are no explicit validation/feedback checkpoints for test runs (e.g. run tests -> read failures -> fix -> rerun), which keeps it just below 5.

4 / 5

Progressive Disclosure

Clear overview in SKILL.md with a well-signaled routing table pointing one level deep to real reference files (fixtures.md, parametrization.md, mocking.md, patterns.md), all of which exist, making navigation easy.

5 / 5

Total

18

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20

Passed

Description

83%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong, concrete description that answers both what and when with pytest-specific triggers and actions. It is mostly distinct and free of fluff, with only minor room to add synonyms or a few more action verbs.

DimensionReasoningScore

Specificity

Names the domain ('high-quality pytest tests') and lists several concrete actions ('setting up fixtures, parametrizing, mocking, or reviewing test code'), with minor gaps in coverage such as coverage/assertion patterns.

4 / 5

Completeness

Clearly states what it does ('Expert guidance for writing high-quality pytest tests') and explicitly when to use it ('Use when writing tests, setting up fixtures, parametrizing, mocking, or reviewing test code').

5 / 5

Trigger Term Quality

Includes natural terms users would say ('writing tests', 'setting up fixtures', 'parametrizing', 'mocking', 'reviewing test code'); a few common synonyms or variants like 'fixtures' alone are present but coverage is good rather than comprehensive.

4 / 5

Distinctiveness Conflict Risk

The pytest-specific niche and concrete trigger list make it mostly distinct from sibling skills, with only minor overlap risk against a generic testing/code-review skill.

4 / 5

Total

17

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
provectus/awos-recruitment
Reviewed

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