Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/dealfluence/adeu/hunt-commentsnpx skills add dealfluence/adeu --skill hunt-commentsgit clone --depth 1 https://github.com/dealfluence/adeuWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00026 | $0.00316 |
| Opus 5 | $0.00013 | $0.00158 |
| Sonnet 5 | $0.00005 | $0.00063 |
| Haiku 4.5 | $0.00003 | $0.00032 |
Grade A, and why
hunt-comments scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
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 25 -
Target 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:
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday First seen · 33 lines · 26 tokens per session scan A 2d6f74bfaa4c
hunt-comments is a skill published in the GitHub repository dealfluence/adeu (149 stars, last pushed 2d ago), licensed MIT. It adds 26 tokens to every session and 316 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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