python-pro

Master Python 3.12+ with modern features, async programming, performance optimization, and production-ready practices. Expert in the latest Python ecosystem including uv, ruff, pydantic, and FastAPI.

Quality

23%

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Passed

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tessl review fix ./skills/python-pro/SKILL.md

Quality

Content

10%Scale 1-5

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

This skill is essentially a persona description or capability listing rather than an actionable skill. It contains no executable code, no concrete commands, no specific patterns, and no real workflow guidance. Nearly all content describes things Claude already knows (Python libraries, frameworks, design patterns) without adding any novel, actionable information that would help Claude perform better.

Suggestions

Replace the capability bullet lists with concrete, executable code examples for the most important patterns (e.g., a FastAPI app template, uv project setup commands, ruff configuration in pyproject.toml).

Add a clear workflow with validation steps, such as: 'Run `uv init`, configure pyproject.toml, run `ruff check .`, run `pytest --cov`, verify coverage > 90%' with explicit checkpoints.

Remove sections that only list things Claude already knows (Capabilities, Knowledge Base, Behavioral Traits) and replace with specific patterns, gotchas, or configurations unique to the 2024/2025 ecosystem that Claude might not know.

Split detailed content into bundle files (e.g., ASYNC_PATTERNS.md, FASTAPI_TEMPLATE.md, TOOLING_SETUP.md) and reference them from a concise overview in SKILL.md.

Dimension	Reasoning	Score
Conciseness	Extremely verbose and padded. The vast majority of content is listing capabilities, tools, and concepts Claude already knows (pytest, Django, NumPy, Docker, design patterns, etc.). The 'Capabilities' section is essentially a resume of Python knowledge areas with no actionable content. 'Behavioral Traits' and 'Knowledge Base' sections restate what Claude already knows. Almost no token earns its place.	1 / 5
Actionability	Contains zero executable code, zero concrete commands, and zero specific examples. The entire skill is abstract descriptions and bullet-point lists of topics. The 'Instructions' section has four vague steps ('Confirm runtime', 'Choose patterns', 'Implement and test', 'Profile and tune') with no concrete guidance on how to do any of them. 'Example Interactions' lists prompts but provides no actual responses or code.	1 / 5
Workflow Clarity	The 'Instructions' section provides a rough 4-step sequence but steps are extremely vague with no validation checkpoints, no concrete commands, and no feedback loops. The 'Response Approach' section lists 8 numbered items but these are abstract behavioral guidelines, not a workflow. No verification or error recovery steps exist.	2 / 5
Progressive Disclosure	No bundle files exist, yet the skill contains hundreds of lines of content that could benefit from being split into focused reference files (e.g., async patterns, FastAPI setup, tooling configuration). Everything is inlined in a monolithic structure. While there are section headers providing some organization, the content is a wall of bullet points with no references to external files or layered structure.	2 / 5
	Total	6 / 20 Passed

Description

36%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.

The description reads more like a resume bullet point or marketing tagline than a functional skill description. It uses first-person-adjacent self-aggrandizing language ('Master', 'Expert in') rather than describing concrete actions in third person, and completely lacks trigger guidance for when Claude should select this skill. The specific tool mentions (uv, ruff, pydantic, FastAPI) are a strength but are not tied to concrete actions.

Suggestions

Add an explicit 'Use when...' clause with natural trigger phrases like 'Use when the user asks to write Python code, create Python scripts, build APIs with FastAPI, configure Python projects, or work with .py files'.

Replace vague category labels with concrete actions in third person voice, e.g., 'Writes Python 3.12+ code with modern type hints, builds async services with FastAPI, configures projects with uv and ruff, validates data with pydantic models'.

Remove self-aggrandizing terms like 'Master' and 'Expert in' which add no selection value and replace with actionable capability descriptions.

Dimension	Reasoning	Score
Specificity	Names the domain (Python 3.12+) and mentions broad areas like 'async programming' and 'performance optimization', but these are high-level categories rather than concrete actions. No specific verbs describing what the skill actually does (e.g., 'writes async handlers', 'configures uv projects', 'sets up FastAPI endpoints').	2 / 5
Completeness	Has a vague 'what' (master Python with modern features) but completely lacks any 'when' clause or trigger guidance. There is no 'Use when...' or equivalent, which per the rubric should cap completeness at 3, and the 'what' itself is more of a self-description than actionable capability listing, pushing it to 2.	2 / 5
Trigger Term Quality	Includes some relevant keywords like 'Python 3.12+', 'async programming', 'uv', 'ruff', 'pydantic', 'FastAPI', but misses natural user phrases like 'write Python code', 'Python script', '.py files', 'type hints', 'virtual environment', or 'API endpoint'. The tool names are good triggers but user-facing language is lacking.	3 / 5
Distinctiveness Conflict Risk	Specifying Python 3.12+ and specific tools (uv, ruff, pydantic, FastAPI) provides some distinctiveness, but the broad framing ('production-ready practices', 'performance optimization') could overlap with general coding skills or other Python-related skills. The mention of specific ecosystem tools helps but doesn't fully carve out a clear niche.	3 / 5
	Total	10 / 20 Passed

Validation

90%

Warnings & errors only

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

Validation — 10 / 11 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	10 / 11 Passed

Repository: administrakt0r/AI-Agents-Safe-Coding-Skills
Path: skills/python-pro/SKILL.md
Commit: 57c135b

Reviewed: 2 days ago

Table of Contents

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