fastmcp-python-tests
Write and evaluate effective Python tests using pytest. Use when writing tests, reviewing test code, debugging test failures, or improving test coverage. Covers test design, fixtures, parameterization, mocking, and async testing.
68
82%
Does it follow best practices?
Impact
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No eval scenarios have been run
Passed
No known issues
Quality
Discovery
100%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a well-crafted skill description that clearly communicates what the skill does, when to use it, and covers specific pytest-related capabilities. It uses third person voice, includes natural trigger terms, and has an explicit 'Use when...' clause with multiple trigger scenarios. The description is concise yet comprehensive.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions and concepts: 'write and evaluate effective Python tests', 'test design, fixtures, parameterization, mocking, and async testing'. These are concrete, actionable capabilities. | 3 / 3 |
Completeness | Clearly answers both what ('Write and evaluate effective Python tests using pytest') and when ('Use when writing tests, reviewing test code, debugging test failures, or improving test coverage') with explicit trigger guidance. | 3 / 3 |
Trigger Term Quality | Includes strong natural keywords users would say: 'tests', 'pytest', 'test failures', 'test coverage', 'fixtures', 'mocking', 'parameterization', 'async testing'. These cover a wide range of natural user queries about Python testing. | 3 / 3 |
Distinctiveness Conflict Risk | Clearly scoped to Python testing with pytest specifically, which is a distinct niche. The mention of pytest, fixtures, parameterization, and mocking makes it unlikely to conflict with general coding or other language testing skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
64%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a solid, actionable skill with excellent concrete examples covering pytest patterns, project-specific conventions, and common testing scenarios. Its main weaknesses are moderate verbosity (some explanatory text Claude doesn't need) and a monolithic structure that could benefit from splitting project-specific details into referenced files. The project-specific constraints (no asyncio markers, result.data v3 API, in-memory transport) are the most valuable parts and are well-presented.
Suggestions
Trim explanatory prose that states things Claude already knows (e.g., 'A test that tests multiple things is harder to debug and maintain', 'Test your code with real implementations when possible') to improve conciseness.
Consider splitting project-specific rules (FastMCP transport, inline-snapshot usage) into a separate reference file to keep the main SKILL.md as a concise overview with pointers.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Generally efficient but includes some unnecessary guidance Claude already knows (e.g., 'A test that tests multiple things is harder to debug and maintain', 'Don't mock what you own' philosophy). The good/bad code comparisons add value but some explanatory prose could be trimmed. | 2 / 3 |
Actionability | Excellent executable examples throughout — parameterization, fixtures, mocking, error testing, async patterns, and inline snapshots all have copy-paste ready code. The API version constraint with specific accessor names is highly actionable. CLI commands for running tests are concrete and complete. | 3 / 3 |
Workflow Clarity | The checklist at the end provides a good validation checkpoint, and the inline-snapshot commands are clear. However, there's no explicit workflow sequence for writing tests (e.g., write → run → validate → fix cycle). The skill reads more as a reference than a guided workflow, though for a skill that's primarily about writing tests rather than a destructive multi-step process, this is acceptable. | 2 / 3 |
Progressive Disclosure | The content is well-organized with clear section headers, but it's a fairly long single file (~150 lines of content) with no references to external files. Some sections like the project-specific rules (FastMCP transport, inline snapshots) could be split into separate reference files to keep the main skill leaner. | 2 / 3 |
Total | 9 / 12 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.
Validation — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
- Repository
- Jamie-BitFlight/claude_skills
- Commit
4e61312
- Reviewed
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