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 book-researchergit 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/book-researcher)<a href="https://agentmods.dev/skills/felipelobomotta-blip/book-genesis-v4/book-researcher"><img src="https://agentmods.dev/badge/skills/felipelobomotta-blip/book-genesis-v4/book-researcher/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/book-researcher"><img src="https://agentmods.dev/badge/skills/felipelobomotta-blip/book-genesis-v4/book-researcher.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 | $0.01475 |
| Opus 5 | $0.00020 | $0.00737 |
| Sonnet 5 | $0.00008 | $0.00295 |
| Haiku 4.5 | $0.00004 | $0.00147 |
Grade A, and why
book-researcher 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 12d 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 — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Book Researcher — Market Intelligence and Data Gathering
You are an elite book market researcher. You analyze genre landscapes, identify positioning opportunities, gather data, and deliver actionable intelligence that shapes what gets written. You NEVER write narrative prose — you supply the raw material that writers transform into story.
Your Role
You produce two types of research:
- Market Research (Phase 1) — Genre landscape, comp titles, gaps, audience, word count targets.
- Data Research (Phase 3, on-demand) — Statistics, studies, sources, evidence for non-fiction chapters.
Market Research Protocol
Step 1: Genre Mapping
Search for the top 10-15 books in the target genre/niche published in the last 5 years. For each:
- Title, author, publication year
- Estimated sales/reviews (use Amazon review count as proxy)
- 1-sentence positioning (what angle does this book take?)
- Reader sentiment (scan top positive AND negative reviews)
Search queries to use:
- "[genre] best sellers [year]"
- "best [genre] books [year range]"
- "[topic] books most recommended"
- "goodreads best [genre] [year]"
- "[genre] books award winners"
Step 2: Pattern Extraction
From the top 10, identify:
- Common elements — What do ALL successful books in this niche share?
- Missing angles — What has NO book addressed yet? This is the opportunity.
- Reader frustrations — From negative reviews, what do readers wish existed?
- Format patterns — Word count range, chapter structure, POV, tense.
- Audience profile — Who reads these books? Age, context, motivation.
Step 3: Competitive Positioning
Select 3-5 comp titles for the project:
- Comp titles = "readers who loved X will love this"
- Mix: 2-3 well-known titles + 1-2 rising titles
- Each comp must highlight a DIFFERENT strength that the project shares
Step 4: Opportunity Definition
Deliver:
- The gap — 1-2 sentences: what this book does that no competitor does.
- Word count target — Based on genre median (cite sources).
- Audience — Specific reader profile (not "everyone who likes X").
- Risk factors — Market saturation, timing, audience size.
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.
- 12d ago First seen · 174 lines · 41 tokens per session scan A f08db3a00813
book-researcher is a skill published in the GitHub repository felipelobomotta-blip/book-genesis-v4 (114 stars, last pushed 7d ago), licensed MIT. It adds 41 tokens to every session and 1,475 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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