Ross ROSS = Recommend OSS · open-source software intelligence for agents

Windy3f3f3f3f/claude-code-from-scratch resource

Build your own Claude Code from scratch. 🔍 Claude Code 开源了 50 万行代码,读不动?用 ~5000 行 TypeScript / Python 从零复现核心架构,11 章分步教程带你理解 coding agent 精髓 observed · 2026-08-28

github.com/Windy3f3f3f3f/claude-code-from-scratch · homepage · Python · MIT (permissive) observed · 2026-08-28

Health v2 · maintenance only

59/100

  • Activity 91
  • Release rhythm 45
  • Longevity 11

Flags: young

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 155
  • days_rel: 155
  • days_push: 55
  • n_releases_24m: 1

Full methodology

Adoption not part of the score

2607 stars · 534 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A step-by-step tutorial project that rebuilds the core architecture of Claude Code in about 5000 lines of TypeScript and Python across 13 chapters. It covers the agent loop, tool system, context compression, memory recall, skills, multi-agent orchestration, and MCP integration, with runnable code for every chapter.

Use cases

  • understand how claude code works internally
  • learn to build a coding agent from scratch
  • study agent loop and tool execution patterns
  • learn context compression for llm agents
  • build a terminal ai coding assistant
  • understand mcp integration in agents
  • learn multi-agent orchestration patterns

When to choose

  • you want to understand coding agent architecture without reading hundreds of thousands of lines
  • you prefer learning by writing code step by step
  • you want runnable examples that work without an API key
  • you want both TypeScript and Python reference implementations

When to avoid

  • you need a production-ready coding agent for daily use
  • you expect an exact replica of Claude Code's internal implementation
  • you need guaranteed compatibility or support from Anthropic

Facets

learning-resource · maturity active

agent-framework llm-inference developer-tools cli mcp prompt-engineering large-language-models tutorials developer-tools education python cli cross-platform claude-code coding-agent build-from-scratch step-by-step-tutorial agent-loop context-compression multi-agent hands-on ai-agents nodejs

2 sources

Member repositories

RepositoryRoleHealth v2
Windy3f3f3f3f/claude-code-from-scratchmain59

For agents

markdown · JSON · MCP: product_card(name="Windy3f3f3f3f/claude-code-from-scratch")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem