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PromptsMay 12, 2026·2 min de lecture

Awesome Agentic AI (ZH) — 7-Stage Learning Map

awesome-agentic-ai-zh is a bilingual 7-stage roadmap for AI agents, with 145+ curated projects, hands-on exercises, and CLI/MCP ecosystem guidance.

Prêt pour agents

Cet actif peut être lu et installé directement par les agents

TokRepo expose une commande CLI universelle, un contrat d'installation, le metadata JSON, un plan selon l'adaptateur et le contenu raw pour aider les agents à juger l'adaptation, le risque et les prochaines actions.

Native · 96/100Policy : autoriser
Surface agent
Tout agent MCP/CLI
Type
Prompt
Installation
Single
Confiance
Confiance : Community
Point d'entrée
stages/
Commande CLI universelle
npx tokrepo install 9687e825-75cf-57b7-86ab-6304f16c119e
Introduction

awesome-agentic-ai-zh is a bilingual 7-stage roadmap for AI agents, with 145+ curated projects, hands-on exercises, and CLI/MCP ecosystem guidance.

  • Best for: learners who want a structured path from LLM basics to multi-agent systems and MCP
  • Works with: Markdown-first content; ZH (Traditional/Simplified) + English; includes exercises and project picks
  • Setup time: 30–45 minutes to start

Practical Notes

  • Quant: the roadmap is organized into 7 stages with two tracks (CLI Power User vs Agent Builder).
  • Quant: it highlights 145+ projects and estimates 14–19 weeks minimum (realistically 5–6 months at 5–8 hr/week).

Main

A practical way to use this repo at work:

  1. Follow Stage 0–2 as shared foundation, then choose Track A (use CLI agents) or Track B (build agents).
  2. Treat each stage’s “hands-on” items as acceptance tests: finish them before moving on.
  3. Keep a weekly log of what you built and what failed—agent work improves fastest when failures are explicit.

If your goal is productivity with Claude Code/Codex, Track A is the faster path; Track B is the deeper path for system builders.

FAQ

Q: Is it only in Chinese? A: No—README shows Traditional Chinese, Simplified Chinese, and English docs.

Q: Which track should I start with? A: Most people start with Track A for CLI productivity, then switch to Track B for deeper agent building.

Q: How long does it take? A: The repo estimates 14–19 weeks minimum; realistic pace is 5–6 months at 5–8 hours/week.

🙏

Source et remerciements

Source: https://github.com/WenyuChiou/awesome-agentic-ai-zh > License: MIT > GitHub stars: 1,043 · forks: 102

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