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把书、长视频、播客等高价值内容蒸馏成可执行的 Agent Skills(Distill high-value content from books, long-form videos, podcasts, and more into executable Agent Skills)
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内容来自 GitHub 原始文件,由原作者维护。在 GitHub 查看
Finish reading, watching, or listening—and leave with a methodology you can invoke.
🌐 Visit the Cangjie Skill official website
The website provides visual Skill Pack browsing, a beginner-friendly usage guide, Skill detail pages, and a contribution submission entry. This GitHub repository remains the sole source for cangjie-skill code, methodology, and templates; the website provides presentation, navigation, and usage guidance.
single) or a compact pack with a router plus promoted standalone Skills (pack).scripts/cangjie.py now covers diagnostics, compilation, output replanning, incremental updates, repair, rollback, evaluation, and benchmarking.See the v2.5.0 release notes and changelog for the complete scope and migration notes.
2026-09-13 refresh (still v2.5.0): task-first validation now retains complete procedures and formulas explained in a single source location. Output scoring counts missing runs and checks numeric values/units; compiled Skills can carry declared scripts and text templates. Download the refreshed generic Skill ZIP · SHA256. Extract it and install the complete cangjie-skill/ directory. Existing users must download the refreshed package; check BUILD_INFO.json for the source commit and refresh date. The original tag is unchanged, so GitHub's automatic source archives do not contain this refresh.
cangjie-skill also provides a standalone installation package for DeepSeek Harness. The adapter layer is bundled in the Release package, so no platform-specific wrapper files are added to this repository.
After installing DeepSeek Harness, download the v2.5.0 package and checksum, verify it, then install from the local tarball:
mkdir -p ~/.dsh/packages
curl -fL "https://github.com/kangarooking/cangjie-skill/releases/download/v2.5.0/dsh-cangjie-skill-2.5.0.tgz" \
-o ~/.dsh/packages/dsh-cangjie-skill-2.5.0.tgz
curl -fL "https://github.com/kangarooking/cangjie-skill/releases/download/v2.5.0/dsh-cangjie-skill-2.5.0.tgz.sha256" \
-o ~/.dsh/packages/dsh-cangjie-skill-2.5.0.tgz.sha256
(cd ~/.dsh/packages && shasum -a 256 -c dsh-cangjie-skill-2.5.0.tgz.sha256)
dsh plugin --profile web add ~/.dsh/packages/dsh-cangjie-skill-2.5.0.tgz
dsh web
Download the DeepSeek Harness plugin (for Cangjie Skill v2.5.0) · SHA256 checksum
After starting a new task, you can say:
Use cangjie-skill to distill this book into a set of executable Agent Skills: <file path>
There's a recent viral idea: distilling colleagues into AI skills. Even after someone leaves, their experience, tone, and work style can be partially replicated by AI. nuwa-skill does exactly this — creating "human skills" like an Elon Musk skill or a Warren Buffett skill. The companion darwin-skill handles automatic skill evolution.
Distilling people is valuable — nuwa-skill has already proven this. Distilling the content people have expressed systematically is a complementary dimension: a book, a long-form interview, a podcast episode, or a long Bilibili or YouTube video can contain methodologies that took the creator years to refine. Rather than imitating someone's expression style, extracting those methodologies and turning them into tools that solve real problems is equally valuable.
There's also a real pain point: you may read many books, save many videos, and listen to many podcasts, yet still struggle to apply what you learned. Content-rich long videos are published every day, are often time-sensitive, and can be difficult to absorb in one viewing; they may not be represented in an AI model's training data at all. Once this content is distilled into skills, an AI agent can invoke the knowledge in real scenarios instead of letting it gather dust in notes, bookmarks, or watch-later lists.
So cangjie-skill has one clear goal: distill every piece of high-value content worth distilling. It works not only with books, but also with videos that have subtitles or transcripts, podcasts, interviews, talks, courses, long-form articles, and document collections. Whenever content contains extractable, verifiable, and transferable methodologies, cangjie-skill can turn them into independently callable, composable, and pressure-testable AI skill packs.
For video content, we recommend using the video-downloader skill alongside cangjie-skill. Use it first to download the video, extract subtitles or audio transcripts, and collect key materials; then pass the resulting text to cangjie-skill for methodology extraction, skill construction, and pressure testing.
cangjie-skill uses the RIA-TV++ pipeline to transform source texts—including books, video transcripts, podcast transcripts, and interview notes—into a reusable Capability Bundle, then compiles that source into installable skills. The process has seven stages:
Script dependencies: the deterministic scripts under
scripts/require Python 3.10+ and PyYAML (python3 -m pip install pyyaml).python3 scripts/cangjie.py doctorruns a self-check and works even when PyYAML is missing. Optional:tiktoken,jsonschema.
BOOK_OVERVIEW.md.cangjie/capabilities/single or compact pack, alongside a reader-facing DIGEST.md, validation results, and installable artifactsThe name RIA-TV++ breaks down as:
User Need
"I want to turn the core methodologies from a book or a long Bilibili/YouTube video into reusable AI skills, not just a summary."
How cangjie-skill reasons
Example Output
The result will not be one summary document. It will be a multi-skill repository with
BOOK_OVERVIEW.md,INDEX.md, a reader-facingDIGEST.md, aGLOSSARY.md, multiple*/SKILL.mdfiles, andtest-prompts.jsonfor trigger testing.
User Need
"I don't want a long explanatory article. I want a skill pack my agent can reuse."
How cangjie-skill reasons
Example Output
The system produces multiple skill modules with trigger conditions, boundaries, execution patterns, and related-skill links — rather than flattening the source into one generalized note.
| Repository | Source | Skills |
|---|---|---|
| buffett-letters-skill | Buffett's shareholder letters (1957-2023) | 20 |
| cognitive-dividend-skill | Cognitive Dividend | 15 |
| duan-yongping-skill | Duan Yongping's Q&A (business + investment logic) | 15 |
| viral-copywriting-skill | Bao Kuan Wen An | 14 |
| copywriters-handbook-skill | The Copywriter's Handbook | 12 |
| contagious-skill | Contagious | 15 |
| influence-skill | Influence | 12 |
| 1000-true-fans-skill | 1000 True Fans | 13 |
| system-prompt-skills | 165 AI product system prompts | 15 |
| X-growth-skills | Practical X (Twitter) account launch, content growth, algorithm, engagement, and monetization resources | 15 |
| sunyuchen-skill | A single narrative writing sample labeled “sunyuchen” | 1 (7 capabilities) |
| poor-charlies-almanack-skill | Poor Charlie's Almanack | 12 |
| no-rules-rules-skill |
These repositories are built from subtitles or transcripts of long-form videos, courses, or video collections. They demonstrate cangjie-skill's ability to distill methodologies from non-book content.
| Repository | Source | Skills |
|---|---|---|
| ai-for-everyone-skill | Andrew Ng's AI for Everyone video course | 25 |
| loop-engineering-skill | Loop Engineering long-form video collection | 8 |
More high-value books are planned for distillation. Future candidates include, but are not limited to, The Prince.
Additional external source (included with the author's permission):
cangjie-skill/
├── README.md ← You are here (default)
├── README.zh-CN.md ← Simplified Chinese version
├── README.ja.md ← Japanese version
├── LICENSE ← MIT License
├── SKILL.md ← Meta-skill definition (full execution spec for cangjie-skill)
├── methodology/ ← RIA-TV++ stage-by-stage methodology docs
├── extractors/ ← Prompt definitions for the 5 parallel extractors
└── templates/ ← SKILL.md / INDEX.md / BOOK_OVERVIEW.md templates
cangjie-skill is part of a larger skill ecosystem:
They interlock: nuwa distills people, cangjie distills books, darwin keeps them evolving.
External Source (included with the author's permission):
Thank you to the following contributors for expanding the cangjie-skill ecosystem:
袋鼠帝 kangarooking — AI blogger and indie developer. Creator of the AI Top WeChat Official Account “袋鼠帝 AI 客栈”
Volcengine Navigation KOL, Baidu Qianfan Developer Ambassador, GLM Evangelist, Trae Kunming's First Fellow
| Platform | Link |
|---|---|
| 𝕏 Twitter | https://x.com/aikangarooking |
| Xiaohongshu | https://xhslink.com/m/5YejKvIDBbL |
| Douyin | https://v.douyin.com/hYpsjphuuKc |
| WeChat Official Account | 袋鼠帝 AI 客栈 |
| WeChat Video Channel | AI 袋鼠帝 |
WeChat Official Account「袋鼠帝 AI 客栈」QR code:

If you also want to distill methodologies from books, long-form videos, podcasts, and courses into callable Agent Skills, join the cangjie-skill WeCom community group:
If this project has helped you, please star it.
MIT License. See LICENSE.
| No Rules Rules |
| 10 |
| huangdi-neijing-skill | Huangdi Neijing (Suwen + Lingshu) | 22 |
| first-principles-skill | First Principles | 10 |
| mao-selected-works-skill | Selected Works of Mao Zedong, Vol. 1-5 | 25 |
| qbdx-hub/buffett-letters-skill | Buffett Shareholder Letters (1957-2023) | 20 |
| qbdx-hub/wo-yu-di-tan-skill | Wo Yu Di Tan | 6 |
| qbdx-hub/mingchao-those-things-skill | Mingchao Those Things | 7 |
| qbdx-hub/sunzi-bingfa-skill | Sunzi Bingfa | 8 |
| qbdx-hub/zhouyi-skill | Zhouyi | 8 |
| qbdx-hub/high-math-vol1-ch1-skill | High Math Vol. 1 Chapter 1 | 8 |