hunt-comments
Use when hunting down verbose, narrative, or dead comments in the codebase to reduce comment noise and character counts.
Source facts
- Repository
- dealfluence/adeu
- Last source activity
- August 22, 2026 at 16:40
- Detected SKILL.md language
- English
- Stars
- 168
- Forks
- 25
Install options
The review-first prompt is selected by default. You can switch to a direct command or download a local copy.
Review the source files
Read SKILL.md and any companion files shown by SkillsMP before deciding whether to install.
Showing SKILL.md
SKILL.md
Source instructions · Read-only preview- name
- hunt-comments
- description
- Use when hunting down verbose, narrative, or dead comments in the codebase to reduce comment noise and character counts.
# Hunt Comments Skill
This skill provides a systematic approach to finding and reducing comment density and character bloat across source code files.
## Workflow
1. **Run the Comment Density Spotter**:
Execute `python scripts/count_comment_chars.py` to rank files by comment character count:
```bash
uv run python scripts/count_comment_chars.py -n 25
```
2. **Target High-Density Files**:
Focus on top-ranked files with high comment ratios (>20% comment characters).
3. **Identify & Remove Non-Essential Commentary**:
- Delete narrative historical explanations ("Why we added this in 2024...", "Fix for issue #123 where...").
- Strip redundant docstrings that simply restate function signatures, types, or obvious operations.
- Collapse multi-paragraph block comments into brief 1-line "why" notes or remove them entirely if code is self-explanatory.
- Retain only essential architectural invariants (e.g., OPC part boundaries, Word signed int32 overflow rules, security guards).
4. **Verify Behavior**:
Always run test suites to verify zero functional or formatting regressions:
- Python: `uv run pytest` & `uv run mypy src`
- Node: `npm run build && npm test`
- LangChain: `uv run pytest` in `langchain`
View on GitHub