Master Claude Code with 6 GitHub Projects: From Multi‑Agent Collaboration to Source‑Code Deep Dive

Part 1: Multi‑Agent Projects for Claude Code

Everything Claude Code

Repository: https://github.com/affaan-m/ECC/tree/main Provides a configuration system that splits a single Claude Code agent into specialized sub‑agents (Planning, Architecture, Code Review, Security, etc.) to reduce hallucinations and capability degradation. The project defines four modules: Skills: domain‑specific knowledge bases that enforce best practices for different frameworks. Commands: shortcut prompts such as /plan, /code-review, /tdd for TDD‑style development. Rules: mandatory rule files (e.g., forbid hard‑coded API keys, enforce Git commit format) that set constraints for the AI. Hooks: automatically triggered workflows based on defined conditions.

The methodology is model‑agnostic and can be applied to Claude Code, Codex, Cursor, OpenCode, and other AI programming assistants.

gstack

Repository: https://github.com/garrytan/gstack Implements a role‑play skill pack for Claude Code. Each role is a distinct sub‑agent with its own slash command: /ceo: product idea review from a business perspective. /eng-manager: technical architecture assessment. /engineer: code implementation. /review: code review for bugs and performance. /qa: test case generation and edge‑case testing. /release: deployment and release configuration.

All skills are defined in Markdown files and integrated via Claude Code’s native slash‑command feature; no external dependencies are required.

Part 2: Understanding Claude Code Internals

learn-claude-code

Repository: https://github.com/shareAI-lab/learn-claude-code A 20‑lesson curriculum where each lesson is a runnable Python file. The series starts with a minimal 01_agent_loop.py (~50 lines) implementing a basic agent loop and incrementally adds explicit planning, context compression, multi‑agent coordination, and other production‑grade mechanisms. Lesson 5 demonstrates the need for explicit task planning; lesson 8 emphasizes context management and compression.

deepagents‑cli (dcode)

Repository: https://github.com/langchain-ai/deepagents Provides a CLI that mimics Claude Code using the DeepAgents framework (LangChain + LangGraph). The architecture includes:

integration of built‑in tools,

sub‑agent scheduling,

code sandboxing,

production‑grade infrastructure such as checkpoint recovery, time‑travel debugging, parallel sub‑agents, and MCP protocol support.

The project is MIT‑licensed, 99.4 % Python, and can be used directly in production.

OpenCode

Repository: https://github.com/anomalyco/opencode Open‑source alternative to Claude Code with a client‑server architecture. The core service (TypeScript + Bun) handles agent scheduling, task management, and tool execution; the terminal UI (Go) provides high‑performance interaction. Six specialized agents (build, plan, general, explore, etc.) have distinct permissions to avoid role confusion. The model‑adapter layer supports 75+ LLM providers, including Claude, GPT, Gemini, and local models.

instructkr/claude-code

Repository: https://github.com/instructkr/claude-code Community‑maintained archive of the official Claude Code source accidentally published by Anthropic (≈1906 TypeScript files, 510 k lines). The archive preserves the original design: agent loop, task orchestration, MCP protocol, multi‑layer security isolation, and Swarm parallelism. A Rust re‑implementation provides legal safety while retaining the same design patterns.