🌐 English ｜ 中文
A cold-start onboarding solution for AI agents: it interviews you, learns the right real tools, passes an independent proctor, and ships a real result back to your machine.
Motto: Nothing is learned without proof.
The problem with tutorials: people read them and never actually do them. So flip it: don't just school your AI — onboard it like a new hire.
Hand this repo to your own Claude Code. Two paths:
- 🚀 Quick onboard (recommended, ~30 min) →
agent-school/onboard.en.md: it interviews you, speed-runs the 2–3 most relevant courses, and immediately gets one real task done for you. - 🎓 Full study (132 courses) →
agent-school/enroll.en.md: systematic training across seven faculties.
Either way: real execution → real graduation test → independent proctor → skill cards deployed to your machine. "Doing" is welded into "learning." An agent that graduates here has ability that is verified, not claimed.
A generic skill card may not run on your machine — wrong OS, missing dependency, version drift. Here the agent installs, executes, and verifies on your actual computer first, then distills a skill card calibrated against that real run. What comes back isn't a manual — it's a working capability that's been road-tested on your machine.
| Task | 🤖 Bare agent | 🎓 After onboarding |
|---|---|---|
| Trim a long video into highlights | Guesses at ffmpeg flags, may corrupt timing |
Pulls its ffmpeg skill card (T17), trims on keyframes, verifies output |
| Clean a messy spreadsheet | Improvises pandas, assumes column names | Pulls its data-wrangling card, inspects structure first, handles encoding |
| Batch-rename / tidy files | Runs a risky one-liner blind | Explores first (J01), dry-runs, shows the plan before touching anything |
Examples map to real courses in this repo (T17 ffmpeg, Tools/pandas, J01) — no invented abilities.
This repo is built for you. You can act on your own:
- To onboard fast (recommended) → read
agent-school/onboard.en.md: interview → speed-run 2–3 courses → ship one real task in ~30 min. - To study the full curriculum → read
agent-school/enroll.en.md. The full 132-course index is in the Course Map. - To grasp the whole repo in 30s → read
llms.txt(an index written for LLMs). - To find ready-made gear → read the Skill Arsenal.
- Want AI onboarded fast (recommended) → send
agent-school/onboard.en.mdto your Claude Code; ~30 min to your first real result. - Want full systematic training → send
agent-school/enroll.en.mdto your Claude Code; it studies and reports back the results. - Want to learn yourself → the companion Claude Code Field Course is below.
| 🔬 Strict in, strict out — graduate by proof | "I learned it" counts for nothing. Only real commands you ran and real outputs count. |
| 🧑⚖️ Independent proctor, no free passes | Each course's pass/fail is judged by a fresh-context independent proctor that re-runs the commands itself — it won't take the student's word. |
| 🚫 Zero tolerance for faking | Fabricated evidence or pretend-execution = expelled on the spot. That's exactly why the diploma is worth something. |
| 🎒 Brings back real skills + real tools | Not just good habits — your agent learns to wield real tools (Scrapling, pandas, ffmpeg…) it can deploy on your machine. |
| 🧲 Integration-first — built on real OSS | We don't reinvent wheels. New courses are each anchored to a battle-tested GitHub project (screenshot-to-code, n8n, ComfyUI, Dify…); install commands are verified from the project's README, not made up. |
| 🌐 Global & bilingual | Built for the whole world. Localizes per audience: Chinese editions use WeChat/Xiaohongshu/Douyin; English editions use X/LinkedIn/Substack/YouTube. |
What a graduate brings back: a diploma + a graduation report with a before/after capability chart + a drawer of skill cards + a fully-traceable report card.
Full catalog and progress in the Course Map; course bodies live in agent-school/courses/. Every course follows one iron rule: it's not an explainer article — it's a real task with evidence and a distilled skill card.
| Faculty | Count | What it teaches |
|---|---|---|
| 🏗 Foundations | 15 (J) | Make the agent a reliable employee: explore before acting, manage memory, deliver with evidence, respect the user's machine, review & regression… |
| 🔧 Tools | 35 (T) | Master real tools: gh · git · pandas · DuckDB · Playwright · Scrapling · ffmpeg · yt-dlp · Whisper · OCR · pandoc · docker… |
| 💼 Professions | 50 (Z) | Serve real industries: content & social · e‑commerce/livestream/cross-border · data/growth/finance · sales/support/HR · legal/education/F&B/real-estate… |
| 🎨 Design | 11 (D) | Make output look good, anchored to real OSS: screenshot-to-code · shadcn/ui · ComfyUI · Figma MCP · social-card & slides skills |
| 🎬 Media | 8 (M) | Video/audio production: auto-editor · faster-whisper · edge-tts · GPT-SoVITS · MoneyPrinterTurbo · videocut-skills |
| 🔌 Automation | 6 (A) | Wire tools into pipelines: n8n (+ n8n-MCP) · Dify · Activepieces · Node-RED · Windmill |
| 🧱 Build & Product | 7 (B) | Build & ship: bolt.diy · Dyad · ToolJet · NocoDB · Plane · PM-Skills · PRD generators |
Two graduation tracks: by default take the core (01–07) for a basic graduation; for "full training," continue with the electives.
🌐 Bilingual: all 132 courses are available in both Chinese (
courses/) and English (courses/en/) — Professions localized per platform, legal courses jurisdiction-neutralized (GDPR/CCPA), integration courses (Design/Media/Automation/Build) localized per platform/region.
🚀 Try it now: send agent-school/enroll.en.md to your Claude Code.
A graduate is great — but agents have no memory between conversations. Open a new chat and it forgets it ever studied. AgentForge ships the missing piece: weld the learned skills into your agent's persistent memory, so every new conversation auto-carries them.
- One-shot equip —
agent-school/配置向导.en.md: paste one line to your agent; it installs a graduate memory + on-task reflex + ready-to-use skill cards into~/.agentforge/and grafts it into the global memory file of every agent tool (Claude Code / opencode / OpenClaw / Hermes / Codex / Gemini). Idempotent · backed up ·--uninstall-able. Script:deploy/setup.sh. - Memory grafter —
deploy/agentforge-memory/: the engine that writes the reflex block into each tool's global memory. Three-pronged: known tools + auto-discovery + manual--target. - Remote MCP server —
deploy/agentforge-mcp/: a read-only service so any MCP client can pull the 132 courses on demand (get_rules/list_courses/get_course/get_doc), served live from GitHub.
Honest ceiling: we guarantee the reminder + real skill cards are present in every new session; whether the agent acts on them still depends on the model's strength.
11 lessons that translate official best practices into plain language (for humans to read, and for agents to draw from). The whole thing rests on one sentence:
🧠 Claude's "context window" is its working memory — the fuller it gets, the worse it performs.
See the index in content/posts/ (claude-code-*.md). (Currently in Chinese; English edition on the roadmap.)
agent-school/ # 🎓 The school for agents (written directly for AI to read)
├── enroll.md / enroll.en.md # Enrollment instructions (zh / en) — paste to your agent
├── 课程地图.md # Course Map: all 132 courses + progress
├── 出课标准.md # Course quality gate (integration-first / real task / verifiable / bilingual)
├── 校规.md # Academic-integrity constitution + isolation + safety
├── 体检报告.md # Independent-proctor audit report
├── courses/ # 132 course bodies (J/T/Z + D Design / M Media / A Automation / B Build)
├── templates/ # Blank masters (report card / graduation report / diploma)
├── students/ # One "dorm" per agent (= one training run)
├── skills/ · 毕业印迹.md · 未来规划.md
content/posts/ # 📚 Claude Code Field Course (11) + AI tool map
deploy/ # 🧬 Make skills stick: agentforge-mcp (MCP server) · agentforge-memory (grafter) · setup.sh
llms.txt # 🤖 Repo index written for LLMs
src/ # 🌐 Companion site source (Next.js, optional)
📦 Run / deploy the companion site (for developers, optional)
The site is built with Next.js 16 + Tailwind v4, Claude-design style, dark mode supported.
npm install
npm run dev # http://localhost:3000
./deploy.sh # build → standalone bundle → rsync to server → PM2 restartAdd an article: create content/posts/xxx.md with frontmatter (title/description/date/tag); the filename is the URL slug. Course ordering lives in src/lib/course.ts. New claude-code-* course articles must also be registered in courseEntries (see AGENTS.md).
Stack: Next.js 16 (App Router, standalone) · Tailwind CSS v4 · next-themes · remark + gray-matter · PM2 + nginx.
—— Headmaster Basion Wang ⚒️ · Motto: Nothing is learned without proof.