code-comment-generator

Generates meaningful comments and documentation for code to improve maintenance and readability. Use when adding documentation to Python or Java code, including function/method docstrings, class documentation, inline explanations for complex logic, and code annotations (TODO, FIXME). Analyzes existing comment style in the codebase to match conventions. Produces clear, concise comments that explain the "why" not just the "what", following best practices for each language.

1.23x

Quality

92%

Does it follow best practices?

Impact

89%

1.23x

Average score across 3 eval scenarios

Securityby

Passed

No known issues

Quality

Content

85%

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-structured, highly actionable skill with excellent workflow clarity and good progressive disclosure. The main weakness is verbosity - the content explains concepts Claude already understands (like 'explain why not what') and provides parallel Python/Java examples throughout that significantly inflate token count. The skill would be more efficient at roughly half its current length.

Suggestions

Consolidate Python and Java examples - show one language inline and reference the other in a separate file (e.g., 'See references/java_examples.md for Java equivalents')

Remove the 'Comment Quality Guidelines' section - Claude already knows these principles; a brief reminder list would suffice

Trim the 'Best Practices Summary' to 3-4 key points that are specific to this skill rather than general commenting wisdom

Dimension	Reasoning	Score
Conciseness	The skill is comprehensive but verbose, with extensive examples that could be condensed. Many concepts (like what makes a good comment) are things Claude already knows, and the dual Python/Java examples throughout nearly double the content length.	2 / 3
Actionability	Provides fully executable, copy-paste ready code examples in both Python and Java. Each section includes concrete before/after examples showing exactly how to transform uncommented code into well-documented code.	3 / 3
Workflow Clarity	Clear 6-step workflow with explicit sequence: analyze existing style → understand code → write documentation → add inline comments → document classes → add annotations. Each step has clear criteria and examples.	3 / 3
Progressive Disclosure	Well-structured with clear sections and references to external files (references/comment_examples.md, references/style_guides.md) for detailed content. Main document serves as actionable overview without requiring deep nesting.	3 / 3
	Total	11 / 12 Passed

Description

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 excels across all dimensions. It clearly specifies what the skill does (generates comments and documentation), when to use it (with explicit 'Use when...' clause covering specific scenarios), and includes natural trigger terms developers would use. The description is appropriately scoped to Python and Java code documentation, making it distinctive and unlikely to conflict with other skills.

Dimension	Reasoning	Score
Specificity	Lists multiple specific concrete actions: 'function/method docstrings, class documentation, inline explanations for complex logic, and code annotations (TODO, FIXME)'. Also specifies analyzing existing comment style and producing comments that explain the 'why'.	3 / 3
Completeness	Clearly answers both what ('Generates meaningful comments and documentation for code') AND when ('Use when adding documentation to Python or Java code, including function/method docstrings, class documentation, inline explanations for complex logic, and code annotations'). Has explicit 'Use when...' clause with specific triggers.	3 / 3
Trigger Term Quality	Includes natural keywords users would say: 'documentation', 'Python', 'Java', 'docstrings', 'comments', 'TODO', 'FIXME', 'inline explanations'. Good coverage of terms developers naturally use when requesting code documentation help.	3 / 3
Distinctiveness Conflict Risk	Clear niche focused specifically on code comments and documentation with distinct triggers like 'docstrings', 'TODO', 'FIXME', 'inline explanations'. Unlikely to conflict with general coding skills or other documentation skills due to specific focus on comment generation.	3 / 3
	Total	12 / 12 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
skill_md_line_count	SKILL.md is long (664 lines); consider splitting into references/ and linking	Warning

	Total	10 / 11 Passed

Repository: ArabelaTso/Skills-4-SE
Commit: 0f00a4f

Reviewed: 4 months ago

Table of Contents

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