# virgiliojr94/book-to-skill

> Converts technical books and other structured documents into agent skills: extracts chapters, glossary, patterns, and cheatsheets that the agent loads on demand. Useful for making a book or docs part of your workflow without hallucination or PDF digging.

- Magnitude: 3.0 out of 10 — Steady
- Stars: 36,443 total · +19 stars measured 2026-10-29, 00:05–04:19 UTC, ≈ 103 by evening
- Star trust: star growth looks organic
- Category: AI agents · Language: Python · License: MIT · Created: 2026-05-01 · Last push: 2026-10-28
- GitHub: https://github.com/virgiliojr94/book-to-skill · Page: https://gitnova.dev/en/r/virgiliojr94/book-to-skill

## Useful for

- Build a skill from internal docs and query the agent while coding
- Turn a PDF book into chapter files and a glossary for quick answers
- Merge several papers and notes into one updatable skill

## Why it’s here

- Star-counter measurements on 2026-10-29 (UTC), 00:05–04:19: 36424 → 36443 stars (+19). This is the change over that interval.
- Estimated end-of-day forecast: about +103 stars, using observed gains and the previous day.
- About 12 forks a day — people are taking the code.

## Star trust

Star growth looks organic.

Star-trust labels are heuristics based on the repository’s behavior, not a check of every stargazer.

## Numbers

- Forks: 3,863
- Issues and pull requests: 310
- Watchers: 149
- Average over the last week: 111 per day
- Usual pace: 124 per day
- Stars in the last hour (measured): 5
- Latest release: v1.4.0 (2026-08-10)

## Stars per day, last 30 days (oldest → newest, today is partial)

2026-09-30 … 2026-10-29: 129, 85, 86, 190, 226, 128, 129, 122, 122, 123, 107, 133, 109, 114, 116, 110, 89, 88, 118, 107, 117, 146, 137, 128, 102, 113, 109, 120, 104, 19

## Magnitude by day, last 14 days

09-26 3.3, 09-27 3.4, 09-28 3.5, 09-29 3.1, 09-30 3.0, 10-01 2.9, 10-02 2.6, 10-23 3.1, 10-24 3.3, 10-25 3.0, 10-26 3.7, 10-27 3.5, 10-28 3.3, 10-29 3.0

## More in this category

1. **HKUDS/DeepTutor** — 8.8 · Breakout · AI agents · Python · +415 stars measured 2026-10-29, 00:02–04:17 UTC, ≈ 1,933 by evening
   A lifelong personalized AI tutor with long-term memory: builds learning paths, reads documents and books, and runs practice and assessments via a multi-agent system and RAG.
   Full card: https://gitnova.dev/en/r/HKUDS/DeepTutor.md
2. **elayadesign/ai-design-skills** — 7.9 · Breakout · AI agents · +228 stars measured 2026-10-29, 00:02–04:17 UTC, ≈ 1,299 by evening
   A collection of markdown-based design skills for AI coding tools like Claude Code, Cursor, Codex and Windsurf, covering landing page design and turning static designs into animated showcases.
   Full card: https://gitnova.dev/en/r/elayadesign/ai-design-skills.md
3. **anonnerdfrenzy/survival-llm** — 7.7 · Early signal · AI agents · Python · +47 stars measured 2026-10-29, 00:02–04:17 UTC, ≈ 358 by evening
   A local offline LLM assistant with a library of ~1.5M survival, medical and how-to articles; every answer cites the exact source passage.
   Full card: https://gitnova.dev/en/r/anonnerdfrenzy/survival-llm.md
4. **unclebob/ub-mode** — 7.6 · Breakout · AI agents · +191 stars measured 2026-10-29, 00:02–04:17 UTC, ≈ 1,098 by evening
   An agent skill that enforces disciplined software engineering practices when writing or changing code: TDD, root-cause fixes, behavior testing, and quality gates via mutation testing. Installed as SKILL.md into the agent's skills directory.
   Full card: https://gitnova.dev/en/r/unclebob/ub-mode.md
5. **pbakaus/impeccable** — 7.6 · Breakout · AI agents · Rust · +551 stars measured 2026-10-29, 00:02–04:17 UTC, ≈ 2,466 by evening
   A set of commands and detector rules for AI coding agents that helps them produce better frontend design instead of generic templates. Installs as a skill into Claude Code, Cursor, Codex and other harnesses.
   Full card: https://gitnova.dev/en/r/pbakaus/impeccable.md

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Magnitude (0–10) measures how fast and how unusually interest in a repository is growing right now. It is not a quality score.
Days are UTC. “So far today” is a fact; “expected by the end of the day” is a forecast.
Summaries and use cases are written by an LLM (DeepSeek V4.1 Flash) from the README and may be inaccurate: verify specific claims (benchmarks, speed, hardware) in the repository itself.
Data as of 2026-10-29 04:27 UTC, updated every 30 minutes.