by WenyuChiou
A trilingual (繁中 / English / 简中) learning roadmap for agentic AI: from LLM basics to multi-agent systems, with 240+ curated resources and hands-on examples. 中文 AI agent 學習地圖。
# Add to your Claude Code skills
git clone https://github.com/WenyuChiou/awesome-agentic-ai-zhGuides for using ai agents skills like awesome-agentic-ai-zh.
Last scanned: 5/11/2026
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awesome-agentic-ai-zh is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by WenyuChiou. A trilingual (繁中 / English / 简中) learning roadmap for agentic AI: from LLM basics to multi-agent systems, with 240+ curated resources and hands-on examples. 中文 AI agent 學習地圖。. It has 8,493 GitHub stars.
Yes. awesome-agentic-ai-zh passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/WenyuChiou/awesome-agentic-ai-zh" and add it to your Claude Code skills directory (see the Installation section above).
awesome-agentic-ai-zh is primarily written in Python. It is open-source under WenyuChiou on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh awesome-agentic-ai-zh against similar tools.
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Automated security scan — not a certification.
🤖 一張從「AI Agent 是什麼」走到「能做出可靠系統」的學習地圖
先選一條路,再一步一步走。重要概念、動手練習與精選資源都幫你排好順序。
📱 手機閱讀請使用線上文件站。
AI Agent(AI 代理人)是「能為了人的目標,自己判斷下一步並採取行動的 AI 系統」。人給它目標後,它會看目前情況、選擇下一步,必要時使用工具,再依結果繼續、修正、停止,或把控制權交還給人。它可以自動替人完成工作,但只能在人給的規則與權限內行動。只回答一次的聊天機器人,或每一步都固定寫好的腳本,不一定是 Agent。這個 repo 不要求你一開始就懂所有名詞,而是帶你依序完成三件事:
這裡的角色是學習路線圖 + 精選資源 + 可直接執行的小練習。需要完整章節時,我們會帶你去官方文件、Datawhale Hello-Agents 或對應的 Cookbook,不重寫另一套百科全書。需要連模型時,每個練習會再說明雲端或本機路徑。
章節中的重要技術詞第一次出現時會先用白話說明,再保留正式英文。忘記某個詞時,直接查名詞表。
走 Track A 或 Track B 前,先確認 Stage 0–2;只走日常使用者路線的人可以直接打開角色指南。
git clone https://github.com/WenyuChiou/awesome-agentic-ai-zh.git
cd awesome-agentic-ai-zh
下載後先開啟 stages/00-foundations.md,或依上表直接前往適合你的第一站。

這張地圖共有 8 個主題 Stage + Stage 0 準備關 + Stage 7.5 進階閱讀站,也就是 10 個學習站。Track A/B 讀者先確認 Stage 0–2 共用基礎;已經會 Python、Git 與 API 的人可以跳過 Stage 0。日常使用者可以直接走角色指南。
正式順序是 A1 → A2 → Stage 5 → A3 → Stage 8。 Stage 8 建議接著學,不擋 Track A Capstone。
Stage 4 先看懂 Workflow Graph,再用 framework 把它做出來;Stage 7 加入 Eval、觀測、批准與復原,讓流程穩定運作。
🔭 學習順序:Stage 2 Prompt → Stage 3 Agent Loop → Stage 4 Workflow Graph/Framework → Stage 5 工具與規則 → Stage 6 Context Engineering → Stage 7 production。Prompt、Context、Harness、Loop、Graph 會一起工作;它們不是五層,也不是互相取代的產品世代。
Track A 完成 A3 後,可開始 Capstone 專案。Track B 則先完成 Stage 8(含 Stage 7.5)。用 PROGRESS.md 記錄進度。
時程只是安排參考。先完成眼前的一步,不需要一次讀完整張地圖。
這裡只放最常用入口;完整清單在 RESOURCES.md。星號表示學習優先順序,不是專案排行榜。