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hyyhf / agent-book-code

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《从0开始构建 AI 智能体》 一本带你亲手打造类 “Claw” AI Agent 的实战书

ai ai-agents claw harness-engineering skills
16
2
100% credibility
Found Apr 30, 2026 at 16 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

A tutorial repository with runnable code examples guiding users to build FunHarness, a minimal terminal-based AI programming assistant from basic LLM calls through advanced features like tools, memory, permissions, and multi-agent collaboration.

How It Works

1
📚 Discover the guide

You find a friendly book that teaches building your own smart coding helper from simple chats to a full assistant.

2
🔗 Connect your AI

You link a smart thinking service so your helper can understand and respond like a brain.

3
💬 Try your first chat

You ask simple questions and see the AI reply right away, feeling the magic start.

4
🛠️ Build step by step

You follow easy chapters to add powers like reading files, remembering things, and planning tasks, watching your helper grow stronger.

5
🚀 Launch your assistant

With one command, your full helper appears in the terminal, ready to code with you.

6
💻 Code together

You give tasks like 'fix this bug' or 'plan a project', and it reads, writes, tests, and explains everything.

🎉 Your coding buddy

Now you have a personal AI sidekick that remembers your projects, plans work, and helps you build faster every day.

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Star Growth

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AI-Generated Review

What is agent-book-code?

This Python repo is the code companion to a hands-on book that walks you through building a Claw-like AI agent from raw LLM API calls. Starting with basic chat and tool calling, it evolves into FunHarness—a runnable mini agent with TUI chat, 30+ tools for file ops/shell/search, persistent memory, agent teams, task scheduling, and Feishu bot integration. You get chapter-by-chapter scripts plus a full open Claw agent product to tweak into your own claw agentic AI assistant.

Why is it gaining traction?

Unlike black-box frameworks, it forces you to implement every layer—loops, context compaction, permissions, multi-agent handoffs—revealing how real claw agent AI like Claude Code or OpenDevin actually work under the hood. Devs dig the iterative evolution from toy demos to a production-ish mini claw agent with TUI, backend runtime, and open claw agent teams talking to each other. Zero dependencies beyond OpenAI-compatible APIs and uv make it dead simple to run and fork for github claw bot experiments.

Who should use this?

Backend engineers prototyping custom coding agents, AI researchers dissecting agentic flows without vendor lock-in, or indie devs building github claw code empires like mini claw agent task managers. Perfect for teams exploring iron claw agent or zero claw github setups before scaling to nemo claw github.

Verdict

Grab it if you want to grok agent engineering hands-on—low 1.0% credibility score reflects 16 stars and early docs, but code runs flawlessly out-of-box with solid MIT license. Not production-ready, but unbeatable for learning claw agent 256 patterns. (198 words)

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