Best use case
comment-quality is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Review and fix temporal references in code comments.
Teams using comment-quality should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/comment-quality/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How comment-quality Compares
| Feature / Agent | comment-quality | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Review and fix temporal references in code comments.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# Comment Quality Skill
Review code comments for temporal references, development-activity language, and relative comparisons. Produces structured reports with actionable rewrites that explain WHAT the code does and WHY, only WHAT the code does and WHY. Supports `.go`, `.py`, `.js`, `.ts`, `.md`, and `.txt` files.
## Instructions
### Phase 1: SCAN
**Goal**: Identify all comments containing temporal, activity, or relative language.
**Step 1: Determine scope**
Read the repository CLAUDE.md first to pick up any project-specific comment conventions.
Scan only what was requested. If user specifies files, scan those files. If user specifies a directory, scan that directory. Honor the explicit scope -- even if you suspect other files have issues, honor the explicit scope and suggest expansion separately at the end.
If user explicitly requests auto-fix, enable it. Otherwise present findings for review. For large codebases, group findings by directory when reporting.
**Step 2: Search for temporal patterns**
Flag every instance of the following categories. No temporal word is "harmless" -- all temporal language ages poorly and must be rewritten regardless of how innocuous it seems:
- **Temporal words**: "new", "old", "previous", "current", "now", "recently", "latest", "modern"
- **Development activity**: "added", "removed", "deleted", "updated", "changed", "modified", "fixed", "improved", "enhanced", "refactored", "optimized"
- **State transitions**: "replaced", "migrated", "upgraded", "deprecated", "became", "turned into", "evolved"
- **Date references**: "as of", "since", "from", "after", "before"
- **Relative comparisons**: "better than", "faster than", "instead of", "unlike the previous"
**Step 3: Filter false positives**
Exclude from findings -- these are not developer comments and must remain untouched:
- Copyright and license headers (legal requirements, not code comments)
- `@generated` markers (tooling markers)
- `@deprecated` annotations (keep the tag, flag only temporal explanation text after it)
- Variable names or string literals that happen to contain temporal words
- TODO/FIXME items that describe future work without temporal references
When a finding appears, inspect nearby comments in the same function or block -- temporal language tends to cluster.
**Gate**: All files in scope scanned. Findings list populated with file path, line number, and matched text. Every finding listed, not just the first few. Proceed only when gate passes.
### Phase 2: ANALYZE
**Goal**: Understand context for each finding to produce meaningful rewrites.
**Step 1: Read surrounding code**
For each finding, read the function, block, or section the comment describes. Understand what the code actually does. A rewrite without code context produces vague replacements that strip temporal words without adding substance.
**Step 2: Classify the comment**
```markdown
| Finding | Type | Severity |
|---------|------|----------|
| "now uses JWT" | Temporal + Activity | High |
| "improved perf" | Activity | Medium |
| "Copyright 2024" | Legal (skip) | N/A |
```
**Step 3: Determine replacement content**
For each comment, identify:
1. What does the code do right now?
2. Why does it do it this way?
3. What value does the comment add for a future reader?
**Gate**: Every finding classified with context understood. Proceed only when gate passes.
### Phase 3: REWRITE
**Goal**: Generate specific, valuable replacement comments.
**Step 1: Draft rewrites**
For each finding, produce a structured entry with file path, line number, current text, suggested replacement, and reasoning:
```markdown
**File: `path/to/file.ext`**
Line X - [Comment type]:
Current: // Authentication now uses JWT tokens
Suggested: // Authenticates requests using signed JWT tokens
Reason: "now uses" is temporal - describe current behavior only
```
**Step 2: Validate rewrite quality**
Each rewrite MUST pass these checks:
- [ ] Would this comment make sense in 10 years?
- [ ] Does it explain WHAT or WHY, not WHEN?
- [ ] Is it more specific than what it replaces (not just temporal word removed)?
- [ ] Does it add value for a future maintainer?
If a rewrite just removes the temporal word without adding substance, it fails validation. Simply deleting a word produces a useless comment -- `// Updated error handling` becoming `// Error handling` adds nothing. Rewrite with specific, descriptive content: `// Handles database connection errors with exponential backoff retry`.
**Gate**: All rewrites pass quality checks. No vague or empty replacements. Proceed only when gate passes.
### Phase 4: REPORT
**Goal**: Deliver structured, actionable report.
**Step 1: Generate report**
Report facts concisely with file paths and line numbers. Every finding must include the current text, suggested replacement, and reasoning -- a diagnostic-only count without rewrites creates work without providing solutions.
```markdown
## Comment Quality Review
### Summary
- Files scanned: N
- Issues found: M
- Most common pattern: [temporal word]
### Findings
[All findings with file, line, current text, suggested text, reason]
### Recommendations
1. Apply suggested changes
2. Consider adding linter rules for temporal language prevention
```
**Step 2: Apply fixes (if auto-fix enabled)**
If user requested auto-fix, apply all rewrites using Edit tool. Verify each edit succeeded. Wait for explicit user permission before auto-fixing without explicit user authorization.
**Step 3: Cleanup**
Remove any scan results, intermediate reports, or helper files created during execution.
**Gate**: Report delivered. All findings accounted for. Task complete.
## Error Handling
### Error: "No Temporal Language Found"
Cause: Files are clean or scope was too narrow
Solution:
1. Verify common files were scanned (README, main source files)
2. Report clean results -- this is a valid positive outcome
3. Suggest expanding scope if user suspects issues exist elsewhere
### Error: "Too Many Results to Display"
Cause: Large codebase with widespread temporal language
Solution:
1. Prioritize by file importance (README first, then core modules)
2. Group findings by pattern type
3. Process files by directory with grouped reports
### Error: "Comment Meaning Unclear Without History"
Cause: Comment only makes sense with development context that no longer exists
Solution:
1. Read surrounding code to infer current purpose
2. If purpose is clear from code, suggest removing the comment entirely
3. If purpose is unclear, ask user for clarification before rewriting
## References
### Reference Files
- `${CLAUDE_SKILL_DIR}/references/temporal-keywords.txt`: Complete list of temporal words to flag
- `${CLAUDE_SKILL_DIR}/references/examples.md`: Before/after examples of comment rewrites
- `${CLAUDE_SKILL_DIR}/references/quality-issues.md`: Common problematic patterns with explanationsRelated Skills
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