knowledge-compiler

A Chinese-language workflow for turning collected web research and references into a structured teaching textbook. It organises the material into chapters with goals, concepts, explanations, examples, summaries, and further questions.

In plain words
What is it for?
Use it after gathering enough webpages and references to plan and write a multi-chapter educational guide, one chapter at a time.
Why use it?
It gives research material a consistent lesson structure and keeps the sources visible, making the result easier to teach from and review.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/ghostricke9/studyagent/knowledge-compiler
Any agent
npx skills add Ghostricke9/StudyAgent --skill knowledge-compiler
Clone the repo
git clone --depth 1 https://github.com/Ghostricke9/StudyAgent

Made for: Claude Code, Codex.

Per session 20 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 486 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00020 $0.00486
Opus 5 $0.00010 $0.00243
Sonnet 5 $0.00004 $0.00097
Haiku 4.5 $0.00002 $0.00049

Measured yesterday against content hash dd7463d2fbdb, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

knowledge-compiler 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 yesterday.

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.

skills/knowledge-compiler/SKILL.md · 59 lines

What it actually says

技能:编撰教学教材

何时使用

当你已经收集到足够的网页资料和参考文献,需要将它们整理成一份结构化的教学教材时,调用此技能。

编撰要求

请严格按照以下 Markdown 格式逐章输出教材内容。每次编撰一个章节,不要一次输出全部:

# [主题名称]

## [本章标题]

### 本章目标
- [列出3-5个本章学习目标]

### 关键概念
| 概念 | 解释 |
|------|------|
| 概念1 | 简明解释 |
| 概念2 | 简明解释 |

### 详细讲解
[分小节详细讲解本章知识点,每个小节包含:
- 概念引入(为什么需要这个知识)
- 核心内容讲解
- 代码示例或公式推导(如适用)
- 常见误区或注意事项]

### 示例
[提供1-2个完整的代码/公式/案例示例]

### 本章小结
[3-5句话总结本章关键知识点]

### 进阶思考
[1-2个引导读者深入思考的问题]

编撰原则

  1. 循序渐进:从基础概念到深层原理
  2. 理论与实践结合:每个概念配合实际示例
  3. 语言清晰:避免过于学术化,用通俗语言解释复杂概念
  4. 保留原出处:引用参考资料中的重要数据或观点时标注来源
  5. 控制篇幅:每章内容控制在2000-3000字
  6. 分章编撰:一次只写一章,完成后再写下一章

使用方式

  1. 根据参考资料规划出3-5个章节标题
  2. 逐章编撰,每章单独输出
  3. 所有章节完成后,使用 save_document 保存完整教材
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. yesterday First seen · 59 lines · 20 tokens per session scan A dd7463d2fbdb

Subscribe to this mod's changes

knowledge-compiler is a skill published in the GitHub repository Ghostricke9/StudyAgent (5 stars, last pushed 3mo ago), licensed MIT. It adds 20 tokens to every session and 486 once invoked, about $0.0001 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 2026-08-31.

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