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Brutally honest book builder

Skill vybzai/spitfire-storybook/skills/brutally-honest-book-builder

Turn your own data into a brutally honest, deeply personal development book — then have it read aloud to you. Local, private, open-source.

Install
npx -y skills add vybzai/spitfire-storybook --skill brutally-honest-book-builder

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Turn a user's own connected data and assistant memory into a book-length, deeply personalized, brutally honest self-development guide. Use this when the user says things like "build me a personalized book", "write a brutally honest self-development book from my data", "turn my data into a book", "make me a development guide based on how I actually work", or asks for an evidence-based personal-growth book grounded in their real email, chat, tasks, calendar, meeting notes, and memory. Runs a consent-gated, read-only pipeline: Collect -> Diagnose -> Generate (~30-40 chapters, ~120k+ words) -> Build (PDF + EPUB). The private diagnostic profile never ships in the compiled book.

SKILL.md

5.8 KB, ~1.2k tokens by cl100k_base, as published. Nobody here has run it

Brutally Honest Book Builder

This skill helps you turn a user's OWN data into a long-form, deeply personalized self-development book. The book is written in the voice of a no-bullshit mentor: harsh and direct on the surface, genuinely on the user's side underneath. The specificity comes from evidence in the user's real working life, not generic advice.

The pipeline has four steps. Follow them in order:

  1. Collect — read across the user's connected sources to understand how they actually operate.
  2. Diagnose — synthesize a private, evidence-based profile of strengths and shortcomings.
  3. Generate — run a multi-agent workflow to write ~30-40 chapters from a strict shared template seeded with the profile.
  4. Build — compile the Markdown into PDF and EPUB with pandoc.

Detailed instructions for each step live in the reference/ files. Load each one when you reach that step — do not read them all up front.

  • Step 1: reference/01-collect-data.md
  • Step 2: reference/02-build-profile.md
  • Step 3: reference/03-generate-book.md
  • Step 4: reference/04-build-pdf-epub.md

Build assets live in assets/: metadata.yml (title/author/PDF + EPUB settings), Makefile (compile targets), and epub.css (EPUB styling).

Consent & Privacy (read this first — non-negotiable)

This skill reads the user's private life. Treat that as a responsibility, not a convenience.

  • Get explicit consent before reading anything. Before touching any connected source, tell the user exactly which sources you intend to read (e.g. email, team chat, task/issue tracker, calendar, meeting transcripts, notes/wiki, long-term memory) and wait for a clear yes. If a source is not approved, do not read it.
  • Read-only. Never send, post, modify, delete, or create anything in the user's connected sources. You are observing, not acting.
  • Summarize, never exfiltrate. Capture patterns and paraphrased evidence. Do NOT copy raw private content (full emails, message logs, names of third parties, financial figures, client identities) into any file, and never into the book.
  • The profile is private and stays private. Step 2 produces a working profile file. It is git-ignored, lives outside the book sources, and is NEVER included in the compiled PDF/EPUB. Verify this during the build (Step 4).
  • The user opts into harshness. The book is blunt by design. Confirm the user wants that tone before generating. Harsh means honest and constructive, never cruel or contemptuous.
  • Let the user stop or redact at any point. If they want a source dropped or a pattern removed, comply immediately.

Before starting, create a .gitignore in the book working directory (if not already present) that excludes the private profile and any intermediate notes, for example:

profile.md
profile/
notes/
*.private.md

Step 1 — Collect

Read reference/01-collect-data.md.

With consent secured, survey the approved sources to understand how the user really works: how they communicate, where they follow through and where they drop things, how they spend time, recurring frictions, and recurring strengths. Produce concise, paraphrased pattern notes — not raw dumps.

Step 2 — Diagnose

Read reference/02-build-profile.md.

Synthesize the collected patterns into a single private profile.md: top strengths, top critical shortcomings, recurring behavioral patterns, each backed by concrete but paraphrased evidence. This profile is the engine of the whole book — its specificity is what makes the book feel written for this one person. Keep it git-ignored and out of the build.

Step 3 — Generate

Read reference/03-generate-book.md.

Plan ~30-40 chapters that map directly onto the profile's findings. Then use a multi-agent workflow — one writer agent per chapter, all working from a single strict chapter template seeded with the relevant profile excerpts — to write each chapter at ~3,000-4,500 words (~120k+ words total). Every chapter follows the same structure: cold open, hard truth, teaching (with Mermaid diagrams and tables), worked example, real case study, a "Harsh Mirror" self-assessment with a 1-5 scorecard, drills, common mistakes, key takeaways, and a weekly commitment.

Step 4 — Build

Read reference/04-build-pdf-epub.md.

Compile the Markdown chapters into PDF (via pandoc + xelatex) and EPUB, using the files in assets/ (metadata.yml, Makefile, epub.css). Optionally render Mermaid diagrams to images with a mermaid filter. Then verify: total word count and page count are in range, all diagrams render, the chapter structure is intact, and — critically — the private profile file is NOT present in the compiled artifact.

Definition of done

  • The user gave explicit, source-by-source consent and chose the tone.
  • A private, git-ignored profile.md exists and drives the chapters.
  • ~30-40 chapters exist, each following the full template, totaling ~120k+ words.
  • PDF and EPUB build cleanly with diagrams rendered.
  • The compiled book contains zero raw private content and excludes the profile.

Gives 0 of the 12 instructions most debug triage skills give in ~1.2k tokens

Counted across 839 of the 1,149 authors here whose files we hold, read 2026-08-06

  • investigate root cause before proposing any fixin 102 of 839, across 65 files
  • read error messages completelyin 90 of 839, across 48 files
  • create a failing test case before fixingin 84 of 839, across 44 files
  • reproduce the issue consistentlyin 82 of 839, across 40 files
  • change one variable at a timein 82 of 839, across 42 files
  • check recent changesin 74 of 839, across 35 files
  • write the regression test before fixingin 74 of 839, across 36 files
  • fix the root cause not the symptomin 60 of 839, across 43 files
  • implement a single fix at a timein 59 of 839, across 20 files
  • trace data flow backward to the sourcein 50 of 839, across 20 files
  • remove all debug instrumentationin 49 of 839, across 13 files
  • form a single hypothesisin 48 of 839, across 18 files

Said here and by no other author read

  • execute the pipeline steps in order
  • load each reference file only when reaching that step
  • obtain explicit source-by-source consent before reading data
  • keep connected sources strictly read-only
  • paraphrase private evidence never copy raw content
  • exclude the private profile from the compiled book

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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