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 reader-personagit 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/reader-persona)<a href="https://agentmods.dev/skills/felipelobomotta-blip/book-genesis-v4/reader-persona"><img src="https://agentmods.dev/badge/skills/felipelobomotta-blip/book-genesis-v4/reader-persona/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/reader-persona"><img src="https://agentmods.dev/badge/skills/felipelobomotta-blip/book-genesis-v4/reader-persona.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 | $0.00061 | $0.03945 |
| Opus 5.5 | $0.00024 | $0.01578 |
| Sonnet 5.5 | $0.00012 | $0.00789 |
| Haiku 4.5 | $0.00006 | $0.00394 |
Grade A, and why
reader-persona 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 1mo 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 — 402 lines — stays where its author put it; the contents beside it link to each section on GitHub.
READER PERSONA — Audience Architecture V3.7
Writers who write "for everyone" write for no one. This skill creates concrete, detailed reader profiles so every agent in the pipeline knows exactly WHO they are writing for. The personas inform:
- Architect: Pacing decisions, what the reader's patience threshold is
- Writer: Vocabulary level, what to explain vs. assume, emotional calibration
- Evaluator: Whether the manuscript serves its actual audience (4-reader simulation)
- Packager: Marketing angle, comp titles, pitch framing, discovery channel targeting
- Chaos Engine: Which persona to CHALLENGE (the comfortable one) and which to PROTECT (the one on the edge of abandoning)
WHEN TO RUN
- After: Research phase is complete (
bestseller-dna.md, market analysis exist) - After: Foundation document exists (genre, theme, engagement type defined)
- Before: Any writing begins
- Trigger: Orchestrator calls this once during project setup
- Re-run: Only if the book's genre, thesis, or target audience fundamentally changes
REQUIRED INPUTS
foundation.md— for:- Genre classification
- Engagement type ranking (primary/secondary/tertiary)
- Premise and theme
- Protagonist archetype and tone
- Emotional residue target
research/bestseller-dna.md(if available) — for:- Comparable titles and their audiences
- Market positioning
- Genre conventions and reader expectations
STATE.yaml— for project metadata, genre declaration- Any market research in
research/directory
OUTPUT
A single file: reader-personas.md in the book's root directory.
BUILDING THE PERSONAS
Step 1: Audience Landscape Analysis
Before creating individual personas, establish the audience landscape.
1.1 Genre Audience Mapping
Based on the genre declared in foundation.md, identify:
- Core demographic (age range, gender skew if applicable, education level)
- Reading frequency (books per year)
- Discovery channels (BookTok, Goodreads, book clubs, literary reviews, podcast recommendations, airport bookstores)
- Purchase triggers (cover, blurb, recommendation, author loyalty, topic interest)
- Deal-breakers (content they will not tolerate, pacing they will abandon)
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.
- 1mo ago First seen · 402 lines · 61 tokens per session scan A ef3664883c7e
reader-persona is a skill published in the GitHub repository felipelobomotta-blip/book-genesis-v4 (114 stars, last pushed 1mo ago), licensed MIT. It adds 61 tokens to every session and 3,945 once invoked, about $0.0002 per session on Opus 5.5. 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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