learn_claude_code_langchain: Rebuild Claude Code's agent harness step by step with LangChain and LangGraph

by wangyuxun6699 · Agent Tool · ★ 55

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Security audit verdict: CAUTION · quality 58/100

Flagged: spawns subprocesses. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

Quick Facts

Stars55
Forks2
LanguagePython
CategoryAgent Tool
LicenseMIT
Quality Score58/100
Last Updated2026-09-30
Created2026-07-28
Platformsclaude-code, python
Est. Tokens~18k

About learn_claude_code_langchain

Learn Claude Code — LangChain Agent Harness 版 命名说明:仓库目录名与 里的 是历史遗留( 是 Java 库,与本项目无关)。 本项目是纯 Python 实现(LangChain 1.x + LangGraph + OpenAI-compatible ChatModel),仓库内没有任何 Java 文件。 框架选对了,代码量最多可以少一半。这个仓库基于 LangChain 和 LangGraph,深入拆解 Claude Code 这类 coding agent 的 Harness。 本项目已对齐 shareAI-lab/learn-claude-code 的 17 章源码结构(功能同步基线:;本次结构核对:main )。章节中的 Agent Loop、工具协议、Hook、Context、Task、Team、Workflow 与 Goal...

Compatible Skills

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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