docstring

Document a Python module and its classes using Google style

1.43x

Quality

—

Does it follow best practices?

Impact

95%

1.43x

Average score across 3 eval scenarios

Securityby

Passed

No known issues

Quality

Content

62%

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

The skill is highly actionable with concrete docstring templates and examples, and is well-organized, but it is a monolithic single-file body with no validation checkpoint in its workflow and some prose padding, keeping conciseness, workflow clarity, and progressive disclosure at 2.

Suggestions

Add an explicit validation step (e.g., run a docstring linter or confirm the module still imports/parses) before the final checklist to lift workflow clarity to 3.

Move the larger template/example blocks (e.g., deprecation, enum, dataclass formats) into a references file and keep SKILL.md as a concise overview with one-level-deep links to improve progressive disclosure.

Trim interpretive prose like "Understand the purpose of each component" and de-duplicate formatting guidance to tighten conciseness toward 3.

Dimension	Reasoning	Score
Conciseness	The body is mostly efficient with concrete template and example blocks, but several prose passages (e.g., "Understand the purpose of each component") and repeated formatting guidance pad the skill with content Claude largely already knows, fitting the score-2 anchor of mostly efficient but could be tightened.	2 / 3
Actionability	It provides concrete, copy-paste-ready docstring templates plus worked examples for modules, classes, constructors, methods, dataclasses, and enums with explicit Args/Returns/Raises sections, matching the score-3 anchor of fully executable, specific examples.	3 / 3
Workflow Clarity	The numbered instructions sequence the documentation order and a final checklist exists, but the workflow skips a number (jumps 2 to 4) and offers no validation/verification step to confirm generated docstrings parse or conform before finishing, which caps workflow clarity at 2.	2 / 3
Progressive Disclosure	Content is well-organized into sections but the entire template library is inline in a single ~250-line SKILL.md with no bundle references, so it is a single self-contained file rather than an overview pointing to one-level-deep materials, fitting the score-2 anchor of some structure with content that could be split.	2 / 3
	Total	9 / 12 Passed

Description

57%

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 clearly conveys a focused niche (Google-style Python docstrings) and is distinctive, but it is terse and omits an explicit use-when trigger and broader action coverage, which cap specificity and completeness at 2.

Suggestions

Add an explicit "Use when..." clause (e.g., "Use when the user asks to document Python code, add docstrings, or write Google-style docstrings") to reach completeness 3.

Expand the action list to name multiple concrete tasks (e.g., "Add module, class, method, and dataclass docstrings following Google style") to move specificity from 2 to 3.

Include more natural trigger variations users would say ("add docstrings", "document Python code", "write Args/Returns sections") to improve trigger term coverage.

Dimension	Reasoning	Score
Specificity	"Document a Python module and its classes using Google style" names the domain and one concrete action (document) but does not list multiple specific actions, so it matches the score-2 anchor that names domain and some actions but is not comprehensive.	2 / 3
Completeness	It clearly states what the skill does but lacks an explicit "Use when..." trigger, so per the guidelines a missing trigger clause caps completeness at 2 (has what, but when is only implied).	2 / 3
Trigger Term Quality	It surfaces relevant terms users would say ("Python module", "classes", "Google style", "docstrings"), but omits common variations like "document code", "add docstrings", or "add type hints", fitting the score-2 anchor of some relevant keywords missing common variations.	2 / 3
Distinctiveness Conflict Risk	"Google style" docstrings for Python modules and classes carves out a clear niche with distinct triggers unlikely to conflict with other skills, matching the score-3 anchor of a clear niche with distinct triggers.	3 / 3
	Total	9 / 12 Passed

Validation

100%

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 — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: pipecat-ai/pipecat
Commit: 037ee5d

Reviewed: 4 days ago

Table of Contents

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