book-sft-pipeline
This skill should be used when the user asks to "fine-tune on books", "create SFT dataset", "train style model", "extract ePub text", or mentions style transfer, LoRA training, book segmentation, or author voice replication.
npx skills add majiayu000/claude-skill-registry --skill book-sft-pipeline-kalyanikhandare29-agent-skills-for-con-3 --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Book SFT Pipeline A complete system for converting books into SFT datasets and training style-transfer models. This skill teaches the pipeline from raw ePub to a model that writes in any author's voice. ## When to Activate Activate this skill when: - Building fine-tuning datasets from literary works - Creating author-voice or style-transfer models - Preparing training data for Tinker or similar SFT platforms - Designing text segmentation pipelines for long-form content - Training small models (8B or less) on limited data ## Core Concepts ### The Three Pillars of Book SFT **1. Intelligent Segmentation** Text chunks must be semantically coherent. Breaking mid-sentence teaches the model to produce fragmented output. Target: 150-400 words per chunk, always at natural boundaries. **2. Diverse Instruction Generation** Use multiple prompt templates and system prompts to prevent overfitting. A single prompt style leads to memorization. Use 15+ prompt templates with 5+ system prompts. **3. Style Over Content** The goal is learning the author's rhythm and vocabulary patterns, not memorizing plots. Synthetic instructions describe what happens without quoting the text. ## Pipeline Architectu
- When to Activate
- Core Concepts
- The Three Pillars of Book SFT
- Pipeline Architecture
- Phase 1: Text Extraction
- Critical Rules
- Phase 2: Intelligent Segmentation
- Smaller Chunks + Overlap
- Expected Results
- Phase 3: Diverse Instruction Generation
- The Key Insight
- Instruction Generation
- Phase 4: Dataset Construction
- Message Format
Search training data for output phrases grep "specific phrase from output" dataset.jsonl Should return: No matches
What does the book-sft-pipeline skill do?
This skill should be used when the user asks to "fine-tune on books", "create SFT dataset", "train style model", "extract ePub text", or mentions style transfer, LoRA training, book segmentation, or author voice replication.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill book-sft-pipeline-kalyanikhandare29-agent-skills-for-con-3 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.
