shareAI-lab/learn-claude-code

Implements a minimal Claude-powered coding agent through direct model integration rather than prompt orchestration, emphasizing tool access (shell, file I/O, API calls) and dynamic knowledge retrieval as the core "harness" architecture. The project deliberately rejects framework-heavy approaches, instead teaching how to build lightweight execution environments that let LLMs autonomously reason and act—applicable across any domain requiring perception, reasoning, and action loops. Core technical patterns cover tool composition, context management, and subagent isolation to keep the model's decision-making clean and scalable.

25,759 stars. Actively maintained with 58 commits in the last 30 days.