dealfluence Hunt Comments Skill
This skill provides a systematic approach to finding and reducing comment density and character bloat across source code files.
Workflow
Run the Comment Density Spotter: Execute
python scripts/count_comment_chars.pyto rank files by comment character count:uv run python scripts/count_comment_chars.py -n 25Target High-Density Files: Focus on top-ranked files with high comment ratios (>20% comment characters).
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).
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 pytestinlangchain
- Python: