Claude Code Guide for China Users: Get Started from ¥7.9 Without a Credit Card

What the Claude Code Source Leak Revealed About Its True Capabilities

A few days ago, Claude Code accidentally leaked approximately 510,000 lines of source code due to a packaging error. This incident gave many developers their first real look at Claude Code's underlying architecture — it's not a simple AI coding assistant, but a complete streaming programming and multi-Agent collaboration system.

The leak itself was quite dramatic. When Anthropic published a version of Claude Code's npm package, a misconfigured packaging script caused the source directory — which should have been excluded — to be bundled and uploaded to the public repository. The 510,000 lines of code were downloaded and publicly analyzed by multiple developers before being removed. This type of incident isn't uncommon in the software industry — the openness of the npm ecosystem means that once a package is published, retraction is often too late. The leaked code revealed that Claude Code internally uses an event-driven streaming architecture, Tool Use Chains, and a multi-Agent task distribution mechanism. These design philosophies show clear architectural differences from similar products like OpenAI's Codex and GitHub Copilot.

But for most developers in China, the real concerns are much more practical: What can it actually do for me? What if I don't have an overseas credit card? Are there cheaper alternatives?

What Is Claude Code? Core Features at a Glance

Claude Code is a terminal-level AI programming tool launched by Anthropic. Unlike conversational AI tools such as ChatGPT, it runs directly in your terminal environment with the following core capabilities:

• Full-stack code generation: Describe your requirements in one sentence, and it generates a complete project structure from frontend to backend
• Streaming programming experience: Code outputs in real-time, generating and executing simultaneously, multiplying development efficiency
• Multi-Agent collaboration: Multiple AI Agents process different tasks in parallel, essentially giving you an AI development team
• Project-level context understanding: Can comprehend an entire codebase, not just individual files

Multi-Agent collaboration is key to understanding Claude Code's capability boundaries. Traditional AI coding assistants use single-turn or multi-turn dialogue modes, with only one model instance processing requests at a time. In a multi-Agent system, an "Orchestrator Agent" breaks down tasks and distributes subtasks to multiple "Execution Agents" for parallel processing — for example, one Agent generates frontend components, another simultaneously handles backend API logic, and a third writes test cases. Based on the leaked code, Claude Code's multi-Agent implementation relies on message queues and tool-calling protocols, with each Agent sharing project state through standardized context windows. This is the technical foundation that enables it to understand entire codebases rather than single files.

Streaming programming experience also deserves deeper understanding. Its underlying layer relies on the Server-Sent Events (SSE) protocol, allowing the model to push tokens to the client in real-time as they're generated. For programming scenarios, this means users can instantly detect directional errors during code generation and interrupt, rather than waiting for hundreds of lines of code to be fully generated before reworking. Claude Code deeply integrates streaming output with the terminal execution environment, forming a "generate-execute-feedback" loop.