book-to-skill vs llama_index
The two are close in size: 35.4k stars for book-to-skill, 52.6k for llama_index. Over the days we have tracked them book-to-skill moved +14.8% and llama_index +3%, so book-to-skill is growing faster right now.
llama_index leads on customization. book-to-skill does not take any axis by a clear margin.
Stars and commit dates come from our own daily tracking. The six axes are read off each project's documentation by our review pipeline, so they describe what a project says about itself, not what we measured in its code.
Where they stand today
Converts books and document collections into cross-agent, on-demand 'skills' with per-chapter files so agents answer from real content without dumping entire books into context.
- Stars
- 35.4k
- Tracked growth
- +14.8%
- Maturity
- ●●●●●
- Last commit
- 1d ago
- Language
- Python
- License
- MIT
- Cost to run
- Free, local processing; external model API costs apply
A data-first RAG framework focused on document agents and agentic OCR with extensive indexing, retrieval, and 300+ integrations.
- Stars
- 52.6k
- Tracked growth
- +3%
- Maturity
- ●●●●●
- Last commit
- 4h ago
- Language
- Python
- License
- MIT
- Cost to run
- Your API key (or optional LlamaParse cloud)
Six axes, head to head
Each axis runs 0 to 5. The label under a score is what that project's own docs claim, not a category average.
| Axis | book-to-skill | llama_index |
|---|---|---|
Context depth How much of your codebase it sees before it answers: the open diff, the diff plus related files, or the whole repository. | ●●●●● Whole-skill access | ●●●●● Whole-data ingestion |
Noise control How it keeps output volume down — severity thresholds, deduplication, incremental runs over new commits only. | ●●●●● Validation & rules | ●●●●● Rerankers + filters |
Customization How far it bends to your team: custom rules, prompts, style guides, per-path config. | ●●●●● Config file + options | ●●●●● Highly extensible |
Privacy Whether your code stays on your own infrastructure: fully local, self-hostable, or cloud API only. | ●●●●● Local processing | ●●●●● Local model support |
Model freedom Whether you can point it at any provider, or it is wired to one. | ●●●●● BYO model | ●●●●● BYO models & keys |
Setup ease What it takes to get a first useful run out of it. | ●●●●● One-command install | ●●●●● Config + API key |
Which one to pick
Pick book-to-skill if…
Privacy-first — processes documents locally into compact, on-demand agent skills to avoid hallucination and reduce token/token-costs when querying.
Pick llama_index if…
Document-agent focused — pick LlamaIndex when you need a flexible, extensible RAG/document-agent/OCR framework with strong local model and integration support.
- Customization: Highly extensible (5/5 against 3/5)
What people want from each one
virgiliojr94/book-to-skill
- PDF: `pdftotext -layout` interleaves columns on multi-column documents, and the word-based token estimate hides the 26x size blowup 👍 0
- [bug] Interrupted-run reuse accepts missing or corrupted extracted text 👍 0
- [bug] BeautifulSoup HTML/EPUB extraction inserts newlines inside inline headings and code tokens 👍 0
run-llama/llama_index
Questions people ask
Is book-to-skill better than llama_index?
llama_index leads on customization. book-to-skill does not take any axis by a clear margin. book-to-skill is worth picking when privacy-first — processes documents locally into compact, on-demand agent skills to avoid hallucination and reduce token/token-costs when querying.
Which of book-to-skill and llama_index keeps my code private?
book-to-skill: Local processing (5/5). llama_index: Local model support (5/5).
What does each one cost to run?
book-to-skill: Free, local processing; external model API costs apply. llama_index: Your API key (or optional LlamaParse cloud).
Full profiles: virgiliojr94/book-to-skill and run-llama/llama_index. Everything else in RAG & retrieval.