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python-patterns

Python development principles and decision-making. Framework selection, async patterns, type hints, project structure. Teaches thinking, not copying.

41

Quality

41%

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tessl review fix ./plugins/antigravity-bundle-python-pro/skills/python-patterns/SKILL.md

The canonical home for this skill is python-patterns in administrakt0r/AI-Agents-Safe-Coding-Skills

SKILL.md
Quality
Evals
Security

Quality

Content

42%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 provides a reasonable high-level decision framework for Python development but suffers from being too abstract and principle-heavy without enough executable examples. The content is repetitive across sections (async/sync appears multiple times) and would benefit from consolidation and more concrete code. It reads more like a reference card of opinions than an actionable skill that teaches Claude how to implement specific patterns.

Suggestions

Add concrete, executable code examples for key patterns—especially error handling (custom exception classes, handlers), dependency injection, and project scaffolding commands—rather than just listing principles in ASCII trees.

Consolidate overlapping async/sync guidance from sections 2, 5, and 6 into a single authoritative section to reduce redundancy and improve conciseness.

Split framework-specific content (Django best practices, FastAPI patterns) into separate referenced files to improve progressive disclosure and reduce the monolithic nature of the skill.

Add at least one complete mini-workflow with validation steps, e.g., 'Setting up a new FastAPI project: 1. Create structure → 2. Add health endpoint → 3. Verify with curl → 4. Add tests → 5. Verify tests pass' to improve workflow clarity.

DimensionReasoningScore

Conciseness

The skill is moderately efficient but contains significant redundancy—async vs sync decision logic appears in sections 2, 5, and 6 with overlapping content. Many decision trees use ASCII art that could be more compact. Some content like 'Learn to THINK, not memorize patterns' is motivational padding. However, it avoids explaining basic Python concepts Claude already knows.

3 / 5

Actionability

The skill is predominantly abstract decision trees and principle lists rather than executable guidance. There are very few concrete code examples—only a few type hint snippets, one async test example, and a brief FastAPI route. Most sections describe when to use things rather than showing how, e.g., the error handling section has no actual code for exception handlers or error responses.

2 / 5

Workflow Clarity

The decision checklist in section 10 provides a reasonable sequence for project setup decisions. However, there are no validation checkpoints or feedback loops—for example, no guidance on verifying framework choice works (e.g., running a hello-world endpoint), no steps for validating project structure, and no error recovery paths when decisions prove wrong.

3 / 5

Progressive Disclosure

The content is well-sectioned with numbered headers and clear topics, but at ~300+ lines it's a monolithic file with no references to supporting documents. Framework-specific details (Django best practices, FastAPI patterns) could be split into separate files. There are no bundle files to reference, and the skill doesn't link to any external resources or sub-documents.

3 / 5

Total

11

/

20

Passed

Description

41%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 identifies a clear domain (Python development) and lists relevant topic areas, but relies on abstract concepts ('principles', 'decision-making', 'teaches thinking') rather than concrete actions. It lacks a 'Use when...' clause entirely, making it difficult for Claude to know when to select this skill over other Python-related skills. The philosophical framing ('teaches thinking, not copying') is distinctive but not actionable for skill selection.

Suggestions

Add an explicit 'Use when...' clause with trigger phrases like 'Use when the user asks about choosing between Python frameworks (e.g., Django vs FastAPI), structuring a Python project, implementing async patterns, or adding type hints.'

Replace abstract language like 'teaches thinking, not copying' with concrete actions such as 'Guides framework selection decisions, recommends async vs sync patterns, suggests type annotation strategies, and advises on project layout.'

Include common synonyms and natural user phrases like 'Django vs Flask', 'asyncio', 'type annotations', 'Python project layout', 'which Python library' to improve trigger term coverage.

DimensionReasoningScore

Specificity

Names the domain (Python development) and lists several topic areas (framework selection, async patterns, type hints, project structure), but these are categories rather than concrete actions. 'Teaches thinking, not copying' is abstract philosophy rather than a specific capability.

3 / 5

Completeness

Has a partial 'what' (Python development principles and decision-making across several topics) but no 'when' clause at all. There is no 'Use when...' or equivalent trigger guidance, which per the rubric should cap completeness at 3, and the 'what' itself is more thematic than concrete, placing this at a 2.

2 / 5

Trigger Term Quality

Includes relevant keywords like 'Python', 'framework selection', 'async patterns', 'type hints', 'project structure', but misses common user phrases like 'which framework should I use', 'how to structure my Python project', 'FastAPI vs Django', or 'typing' as a synonym. No file extensions or tool names mentioned.

3 / 5

Distinctiveness Conflict Risk

The focus on 'principles and decision-making' and 'teaches thinking, not copying' provides some philosophical distinction, but 'Python development' is extremely broad and could overlap with any Python coding skill. The topic areas (async, type hints, project structure) help somewhat but are still common Python skill territory.

3 / 5

Total

11

/

20

Passed

Validation

90%

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

Validation10 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

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
Reviewed

Table of Contents

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