book-sft-pipeline

book-sft-pipeline is a skill for Claude Code, Codex from muratcankoylan/Agent-Skills-for-Context-Engineering. It costs 46 tokens per session (3,125 once invoked), scanned A, original, MIT.

A workflow for turning books in ePub format into supervised fine-tuning datasets and training models to reproduce an author's writing style. Supervised fine-tuning means training a model with examples of desired input and output.

In plain words
What is it for?
Use it to build author-voice or style-transfer datasets, train models of 8B parameters or less with LoRA, and evaluate the results.
Why use it?
It provides a structured way to split long books into useful text sections and prepare varied training examples without focusing only on story content.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions subagents; positional $N argument.

Good fit Use it to build author-voice or style-transfer datasets, train models of 8B parameters or less with LoRA, and evaluate the results.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/muratcankoylan/agent-skills-for-context-engineering/book-sft-pipeline
About the project

Agent Skills for Context Engineering is a collection of reusable instructions that teach AI agents how to manage their context, coordinate multi-agent systems, and evaluate behavior. Developers use it when building or debugging production agent systems, and the catalogue entries are skills, agents, instructions, and a plugin from this collection.

muratcankoylan/Agent-Skills-for-Context-Engineering · 17,960 stars · on GitHub

Install

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.

Any agent
npx skills add muratcankoylan/Agent-Skills-for-Context-Engineering --skill book-sft-pipeline
Clone the repo
git clone --depth 1 https://github.com/muratcankoylan/Agent-Skills-for-Context-Engineering

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for book-sft-pipeline

README.md
[![agentmods](https://agentmods.dev/badge/skills/muratcankoylan/agent-skills-for-context-engineering/book-sft-pipeline/github.svg)](https://agentmods.dev/skills/muratcankoylan/agent-skills-for-context-engineering/book-sft-pipeline)
Your own site
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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.

agentmods 80×15 button for book-sft-pipeline

Your own site · 80×15
<a href="https://agentmods.dev/skills/muratcankoylan/agent-skills-for-context-engineering/book-sft-pipeline"><img src="https://agentmods.dev/badge/skills/muratcankoylan/agent-skills-for-context-engineering/book-sft-pipeline.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 46 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,125 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00046 $0.03125
Opus 5 $0.00023 $0.01563
Sonnet 5 $0.00009 $0.00625
Haiku 4.5 $0.00005 $0.00313

Measured 12d ago against content hash 4079f17b32dd, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

book-sft-pipeline 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 12d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/pipeline_example.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

examples/book-sft-pipeline/SKILL.md · 381 lines

How it starts

The opening of the file, as written. The whole thing — 381 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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 Architecture

┌─────────────────────────────────────────────────────────────────┐
│                    ORCHESTRATOR AGENT                           │
│  Coordinates pipeline phases, manages state, handles failures   │
└──────────────────────┬──────────────────────────────────────────┘
                       │
       ┌───────────────┼───────────────┬───────────────┐
       ▼               ▼               ▼               ▼
┌──────────────┐ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐
│  EXTRACTION  │ │ SEGMENTATION │ │  INSTRUCTION │ │   DATASET    │
│    AGENT     │ │    AGENT     │ │    AGENT     │ │   BUILDER    │
│ ePub → Text  │ │ Text → Chunks│ │ Chunks →     │ │ Pairs →      │
│              │ │ 150-400 words│ │ Prompts      │ │ JSONL        │
└──────────────┘ └──────────────┘ └──────────────┘ └──────────────┘
                       │
       ┌───────────────┴───────────────┐
       ▼                               ▼
┌──────────────┐               ┌──────────────┐
│   TRAINING   │               │  VALIDATION  │
│    AGENT     │               │    AGENT     │
│ LoRA on      │               │ AI detector  │
│ Tinker       │               │ Originality  │
└──────────────┘               └──────────────┘

Read the full file on GitHub · 381 lines

Changes

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.

  1. 12d ago First seen · 381 lines · 46 tokens per session scan A 4079f17b32dd

Subscribe to this mod's changes

book-sft-pipeline is a skill published in the GitHub repository muratcankoylan/Agent-Skills-for-Context-Engineering (17,960 stars, last pushed yesterday), licensed MIT. It adds 46 tokens to every session and 3,125 once invoked, about $0.0002 per session on Opus 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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