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.
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.
npx skills add muratcankoylan/Agent-Skills-for-Context-Engineering --skill book-sft-pipelinegit clone --depth 1 https://github.com/muratcankoylan/Agent-Skills-for-Context-EngineeringWrote 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.
[](https://agentmods.dev/skills/muratcankoylan/agent-skills-for-context-engineering/book-sft-pipeline)<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/github.svg" alt="Measured on agentmods" height="20"></a>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.
<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>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once 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 |
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.
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.
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 │
└──────────────┘ └──────────────┘
What ships with it
12 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- examples/gertrude-stein/dataset_sample.jsonl 3.9 KB
- examples/gertrude-stein/pangram/Screenshot 2025-12-27 at 3.05.04 AM.png 202 KB
- examples/gertrude-stein/pangram/Screenshot 2025-12-27 at 3.05.36 AM.png 134 KB
- examples/gertrude-stein/pangram/Screenshot 2025-12-27 at 3.07.18 AM.png 129 KB
- examples/gertrude-stein/README.md 5.3 KB
- examples/gertrude-stein/sample_outputs.md 3.5 KB
- examples/gertrude-stein/training_config.json 2.7 KB
- README.md 2.7 KB
- references/segmentation-strategies.md 11 KB
- references/tinker-format.md 5.9 KB
- references/tinker.txt 143 KB
- scripts/pipeline_example.py 6.5 KB runs code
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.
- 12d ago First seen · 381 lines · 46 tokens per session scan A 4079f17b32dd
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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