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euxxeuxx/claude-skills-for-copilot/skills/comment-analyzer/SKILL.md

comment-analyzer

Skill4 starsChanged 7 months agoMITView on GitHub

Analyzes code comments for accuracy, completeness, and long-term maintainability. Detects comment rot and misleading documentation. Use after adding or modifying code comments.

4 other projects use a version of this, 2 of them edited.

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The file

We split this skill into the rules it gives an agent

4 rules. 0 are common, 4 are distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 3 edited versions we read keep these.

  • 4

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    After adding or modifying documentation comments or docstrings

    line 14
  2. Distinctive:

    When reviewing existing comments for potential technical debt

    line 15
  3. Distinctive:

    When verifying comments accurately reflect the code they describe

    line 16
  4. Distinctive:

    Avoid comments referencing temporary states or transitional implementations

    line 37

“Common” is measured: kept by at least 6 in 10 of the 3 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Comment Analyzer

Analyze code comments for accuracy, completeness, and long-term maintainability. Protect codebases from comment rot by ensuring every comment adds genuine value.

When to Use

  • After adding or modifying documentation comments or docstrings
  • When reviewing existing comments for potential technical debt
  • When verifying comments accurately reflect the code they describe

Analysis Steps

  1. Verify Factual Accuracy: Cross-reference every claim against the actual code.
    • Function signatures match documented parameters and return types
    • Described behavior aligns with actual code logic
    • Referenced types, functions, and variables exist and are used correctly
    • Edge cases mentioned are actually handled
    • Performance or complexity claims are accurate
  2. Assess Completeness:
    • Critical assumptions or preconditions are documented
    • Non-obvious side effects are mentioned
    • Complex algorithms have their approach explained
    • Business logic rationale is captured when not self-evident
  3. Evaluate Long-term Value:
    • Comments that merely restate obvious code should be flagged for removal
    • Comments explaining why are more valuable than those explaining what
    • Comments that will become outdated with likely future changes should be reconsidered
    • Avoid comments referencing temporary states or transitional implementations
  4. Identify Misleading Elements:
    • Ambiguous language with multiple possible meanings
    • Outdated references to refactored code
    • Assumptions that may no longer hold
    • TODOs or FIXMEs that may already be addressed

Output Format

## Summary
Brief overview of the analysis scope and findings.

## Critical Issues
Comments that are factually incorrect or highly misleading.
- Location: [file:line]
- Issue: [specific problem]
- Suggestion: [recommended fix]

## Improvement Opportunities
- Location: [file:line]
- Current state: [what's lacking]
- Suggestion: [how to improve]

## Recommended Removals
- Location: [file:line]
- Rationale: [why it should be removed]

## Positive Findings
Well-written comments that serve as good examples (if any).

Analysis and feedback only — do not modify code or comments directly.

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