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 skills add felipelobomotta-blip/book-genesis-v4 --skill mechanical-preprocessgit clone --depth 1 https://github.com/felipelobomotta-blip/book-genesis-v4Wrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/felipelobomotta-blip/book-genesis-v4/mechanical-preprocess)<a href="https://agentmods.dev/skills/felipelobomotta-blip/book-genesis-v4/mechanical-preprocess"><img src="https://agentmods.dev/badge/skills/felipelobomotta-blip/book-genesis-v4/mechanical-preprocess/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/felipelobomotta-blip/book-genesis-v4/mechanical-preprocess"><img src="https://agentmods.dev/badge/skills/felipelobomotta-blip/book-genesis-v4/mechanical-preprocess.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What 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 5.1 | $0.00041 | $0.03211 |
| Opus 5 | $0.00020 | $0.01605 |
| Sonnet 5 | $0.00008 | $0.00642 |
| Haiku 4.5 | $0.00004 | $0.00321 |
Grade A, and why
mechanical-preprocess 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 11d ago.
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.
How it starts
The opening of the file, as written. The whole thing — 307 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Mechanical Preprocess
PURPOSE
AI agents are bad at processing entire manuscripts for mechanical fixes. Context windows overflow, attention drifts, and the agent "forgets" the rules by chapter 15. This skill solves that by splitting the work:
- Bash handles the 80% — pattern matching, counting, safe replacements
- AI handles the 20% — judgment calls on ambiguous cases, reviewing diffs
This is the ONLY skill in the pipeline that uses bash scripting as its primary tool. It exists because some problems are engineering problems, not language problems.
WHEN TO RUN
- After: All chapters have been through prose-craft (complete draft exists)
- Before: dialogue-polish, chaos-engine, or any AI-based editing pass
- Trigger: Orchestrator calls this once when the full manuscript draft is ready
- Re-run: After any major rewrite pass that may reintroduce mechanical patterns
REQUIRED INPUTS
- Chapter files — all chapter drafts in
chapters/directory (e.g.,chapters/chapter-01.mdthroughchapters/chapter-[N].md) - voice-dna.md — for:
- Forbidden word list
- Em-dash policy (max per chapter, allowed contexts)
- Any other mechanical rules (e.g., max semicolons per chapter, banned constructions)
- foundation.md — for genre context (affects which patterns are acceptable)
PROCESS
PHASE 1: SCAN (Pure bash -- no AI)
Run these scans against every chapter file. All commands use standard Unix tools (grep, wc, awk, sed).
1.1 Em-Dash Census
# Count em-dashes per chapter (both spaced and unspaced variants)
for f in chapters/chapter-*.md; do
echo "$(basename $f): $(grep -oP '(\x{2014}| — )' "$f" | wc -l) em-dashes"
done
Categorize each em-dash by context:
- Independent clause separator —
[complete sentence] — [complete sentence](TARGET FOR REMOVAL) - Parenthetical aside —
word — aside — continuation(TARGET: convert to commas or restructure) - Dialogue interruption —
"I was going to—"(KEEP — this is correct usage) - List/appositive —
three things — money, power, fame — were gone(EVALUATE case by case)
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.
- 11d ago First seen · 307 lines · 41 tokens per session scan A 8efc08efb5c1
mechanical-preprocess is a skill published in the GitHub repository felipelobomotta-blip/book-genesis-v4 (114 stars, last pushed 5d ago), licensed MIT. It adds 41 tokens to every session and 3,211 once invoked, about $0.0002 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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