package-management-python
Manage Python packages, virtual environments, and dependencies using uv. Use when installing packages, creating virtual environments, initializing Python projects, resolving dependencies, or running Python scripts.
95
93%
Does it follow best practices?
Impact
98%
1.84xAverage score across 3 eval scenarios
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 strong skill description that clearly communicates what the skill does and when to use it. It names the specific tool (uv), lists concrete actions, and provides an explicit 'Use when...' clause with natural trigger terms. Minor improvement could include mentioning file extensions like pyproject.toml or pip alternatives, but overall it is well-crafted.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: manage packages, virtual environments, dependencies, installing packages, creating virtual environments, initializing projects, resolving dependencies, running scripts. | 3 / 3 |
Completeness | Clearly answers both 'what' (manage Python packages, virtual environments, and dependencies using uv) and 'when' (explicit 'Use when...' clause listing five specific trigger scenarios). | 3 / 3 |
Trigger Term Quality | Includes strong natural trigger terms users would say: 'Python packages', 'virtual environments', 'dependencies', 'uv', 'installing packages', 'Python projects', 'running Python scripts'. These cover common user phrasings well. | 3 / 3 |
Distinctiveness Conflict Risk | The mention of 'uv' as the specific tool and the focus on Python package/environment management creates a clear niche. It is unlikely to conflict with general Python coding skills or other package manager skills due to the explicit 'uv' reference. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
87%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a well-crafted, concise skill that clearly communicates the constraint to use uv exclusively and provides a comprehensive command reference. Its main weakness is the lack of a sequenced workflow showing how commands chain together in typical scenarios (e.g., project setup from scratch, or cloning and running an existing project), which would help Claude execute multi-step tasks more reliably.
Suggestions
Add a sequenced workflow section (e.g., 'New Project Setup: 1. uv init → 2. uv add <deps> → 3. uv sync → 4. uv run main.py') to guide multi-step operations.
Include a brief validation/verification step such as 'uv pip list' or checking uv.lock after dependency changes to confirm the environment is correct.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is lean and efficient. It avoids explaining what uv is or how package managers work in general. Every section delivers actionable constraints or commands without padding. The 'Good/Bad' examples are minimal but effective for reinforcing the rules. | 3 / 3 |
Actionability | Provides a complete command reference table with exact commands for every common task, plus concrete bash examples that are copy-paste ready. The good/bad contrasts make the constraints unambiguous. | 3 / 3 |
Workflow Clarity | Individual commands are clear, but there's no sequenced multi-step workflow (e.g., 'init → add → sync → run') and no validation checkpoints. For a project initialization or dependency syncing flow, explicit sequencing with verification steps would improve clarity. | 2 / 3 |
Progressive Disclosure | For a simple, single-purpose skill under 80 lines with no need for external references, the content is well-organized into logical sections (Rules, Command Reference, Examples) with clear headers enabling quick navigation. | 3 / 3 |
Total | 11 / 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
- ucdavis/ai-skills-registry
- Commit
c0b2e4b
- Reviewed
Table of Contents
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