Claude Code Source Study Skill by ara.so — Daily 2026 Skills collection. A 25-article deep-dive into Claude Code's ~1900-file source code, covering System Prompt engineering, multi-agent orchestration, tool systems, permission security, and terminal UI. Learn production-grade AI agent patterns from Anthropic's real CLI product. What This Project Is This is a Chinese-language source code analysis series that dissects Claude Code (Anthropic's AI CLI coding assistant) module by module — with exact file references, line numbers, and code snippets. Each article extracts reusable design patterns for building your own AI agent applications. Tech stack covered: Bun + TypeScript + Ink (React for terminals) + Anthropic API Repository Structure claude-code-source-study/ ├── docs/ │ ├── 00-目录与阅读指引.md # Index and reading guide │ ├── 01-项目全景.md # Project overview │ ├── 02-启动优化.md # Startup optimization │ ├── 03-状态管理.md # State management │ ├── 04-System-Prompt-工程.md # System prompt engineering │ ├── 05-对话循环.md # Conversation loop │ ├── 06-上下文管理.md # Context management │ ├── 07-Prompt-Cache.md # Prompt caching │ ├── 08-Thinking-与推理控制.md # Thinking & reasoning │ ├── 09-工具系统设计.md # Tool system design │ ├── 10-BashTool-深度剖析.md # BashTool deep dive │ ├── 11-命令系统.md # Command system │ ├── 12-Agent-系统.md # Agent system │ ├── 13-内置Agent设计模式.md # Built-in agent patterns │ ├── 14-任务系统.md # Task system │ ├── 15-MCP-协议实现.md # MCP protocol │ ├── 16-权限系统.md # Permission system │ ├── 17-Settings-系统.md # Settings system │ ├── 18-Hooks系统.md # Hooks system │ ├── 19-Feature-Flag与编译期优化.md │ ├── 20-API调用与错误恢复.md # API retry/recovery │ ├── 21-Ink框架深度定制.md # Ink UI customization │ ├── 22-设计系统.md # Design system │ ├── 23-Memory系统.md # Memory system │ ├── 24-Skill-Plugin开发实战.md # Plugin development │ └── 25-架构模式总结.md # Architecture patterns summary └── README.md Reading Routes ⚡ Quick Route (7 articles) — Global understanding 01 → 02 → 03 → 05 → 09 → 12 → 25 🤖 AI Engineering Route (9 articles) — Deep AI core 01 → 03 → 04 → 05 → 06 → 08 → 09 → 12 → 13 📚 Complete Route (25 articles) Read docs/01 through docs/25 in order. Key Patterns Extracted from Claude Code 1. Tool Builder Pattern ( buildTool() ) Claude Code registers tools using a builder with three-layer conditional registration: // Pattern extracted from docs/09-工具系统设计.md const buildTool = < TInput , TOutput

( config : { name : string description : string inputSchema : ZodSchema < TInput

handler : ( input : TInput , context : ToolContext ) => Promise < TOutput

isEnabled ? : ( context : AppContext ) => boolean requiresPermission ? : PermissionLevel } ) => config // Registration with conditions const tools = [ buildTool ( { name : 'bash' , ... } ) , buildTool ( { name : 'read_file' , ... } ) , buildTool ( { name : 'write_file' , ... } ) , ] . filter ( tool => tool . isEnabled ?. ( ctx ) ?? true ) 2. AsyncGenerator Conversation Loop ( docs/05 ) // Pattern: state-machine conversation loop using AsyncGenerator async function * conversationLoop ( messages : Message [ ] , tools : Tool [ ] ) : AsyncGenerator < StreamEvent

{ while ( true ) { const stream = await anthropic . messages . stream ( { model : 'claude-opus-4-5' , messages , tools , system : buildSystemPrompt ( ) , } ) for await ( const event of stream ) { yield event } const response = await stream . finalMessage ( ) if ( response . stop_reason === 'end_turn' ) break if ( response . stop_reason === 'tool_use' ) { const toolResults = await executeTools ( response . content ) messages . push ( { role : 'assistant' , content : response . content } ) messages . push ( { role : 'user' , content : toolResults } ) // loop continues } } } 3. 35-Line Minimal Store (React ↔ Non-React Bridge) ( docs/03 ) // Pattern: tiny reactive store bridging React and imperative code type Listener < T

= ( state : T ) => void function createStore < T

( initialState : T ) { let state = initialState const listeners = new Set < Listener < T

( ) return { getState : ( ) => state , setState : ( updater : Partial < T

| ( ( s : T ) => T ) ) => { state = typeof updater === 'function' ? updater ( state ) : { ... state , ... updater } listeners . forEach ( l => l ( state ) ) } , subscribe : ( listener : Listener < T

) => { listeners . add ( listener ) return ( ) => listeners . delete ( listener ) } , // React hook integration useStore : ( ) => { const [ s , setS ] = React . useState ( state ) React . useEffect ( ( ) => subscribe ( setS ) , [ ] ) return s } } } 4. System Prompt Segmented Construction ( docs/04 ) // Pattern: build system prompt in segments with cache boundaries function buildSystemPrompt ( context : AppContext ) : SystemPrompt { return [ // Static segment — cache this (never changes) { type : 'text' , text : CORE_INSTRUCTIONS , cache_control : { type : 'ephemeral' } } , // Semi-static segment — cache per project { type : 'text' , text : buildProjectContext ( context . project ) , cache_control : { type : 'ephemeral' } } , // Dynamic segment — never cache (changes each turn) { type : 'text' , text : buildDynamicContext ( context . session ) } , ] } 5. Context Auto-Compact with Token Budget ( docs/06 ) // Pattern: token budget management with auto-compact const TOKEN_BUDGET = { MAX_CONTEXT : 200_000 , COMPACT_THRESHOLD : 0.85 , // compact at 85% full SUMMARY_RESERVE : 2_000 , } async function maybeCompact ( messages : Message [ ] ) : Promise < Message [ ]

{ const tokenCount = await countTokens ( messages ) if ( tokenCount < TOKEN_BUDGET . MAX_CONTEXT * TOKEN_BUDGET . COMPACT_THRESHOLD ) { return messages } // Summarize older messages, keep recent ones verbatim const keepRecent = messages . slice ( - 20 ) const toSummarize = messages . slice ( 0 , - 20 ) const summary = await summarize ( toSummarize ) return [ { role : 'user' , content : Previous conversation summary:\n ${ summary } } , { role : 'assistant' , content : 'Understood.' } , ... keepRecent , ] } 6. Permission 7-Step Decision Pipeline ( docs/16 ) // Pattern: layered permission evaluation type PermissionMode = 'default' | 'acceptEdits' | 'bypassPermissions' | 'plan' | 'auto' | 'strict' | 'custom' async function evaluatePermission ( action : ToolAction , context : PermissionContext ) : Promise < PermissionResult

{ // Step 1: Check bypass mode if ( context . mode === 'bypassPermissions' ) return { allowed : true } // Step 2: Check if action is always-safe if ( isAlwaysSafe ( action ) ) return { allowed : true } // Step 3: Check allowlist if ( isAllowlisted ( action , context . allowlist ) ) return { allowed : true } // Step 4: Check blocklist if ( isBlocklisted ( action , context . blocklist ) ) return { allowed : false , reason : 'blocklisted' } // Step 5: Check auto-approve rules if ( matchesAutoApprove ( action , context . rules ) ) return { allowed : true } // Step 6: Check session memory if ( context . sessionMemory . has ( actionKey ( action ) ) ) return { allowed : true } // Step 7: Ask user const decision = await promptUser ( action ) if ( decision . remember ) context . sessionMemory . add ( actionKey ( action ) ) return { allowed : decision . approved } } 7. Multi-Agent Context Isolation ( docs/12 ) // Pattern: sub-agent with isolated context async function spawnSubAgent ( task : AgentTask , parentContext : AgentContext ) { const subContext : AgentContext = { // Isolated: sub-agent gets its own conversation messages : [ ] , sessionId : generateId ( ) , // Inherited: shares tools and permissions from parent tools : parentContext . tools , permissionMode : parentContext . permissionMode , // Scoped: limited working directory cwd : task . workingDir ?? parentContext . cwd , // Budget: prevent runaway sub-agents maxTurns : task . maxTurns ?? 10 , tokenBudget : task . tokenBudget ?? 50_000 , } return conversationLoop ( [ { role : 'user' , content : task . prompt } ] , subContext . tools , subContext ) } 8. withRetry for API Overload ( docs/20 ) // Pattern: exponential backoff with overload handling async function withRetry < T

( fn : ( ) => Promise < T

, options = { maxAttempts : 3 , baseDelay : 1000 } ) : Promise < T

{ for ( let attempt = 1 ; attempt <= options . maxAttempts ; attempt ++ ) { try { return await fn ( ) } catch ( err ) { if ( attempt === options . maxAttempts ) throw err // Handle Anthropic 529 overloaded if ( isOverloadError ( err ) ) { const delay = options . baseDelay * Math . pow ( 2 , attempt - 1 ) await sleep ( delay + Math . random ( ) * 1000 ) // jitter continue } // Don't retry non-retriable errors if ( isAuthError ( err ) || isInvalidRequestError ( err ) ) throw err throw err } } throw new Error ( 'unreachable' ) } Applying These Patterns to Your Own Agent Minimal Agent Scaffold import Anthropic from '@anthropic-ai/sdk' const anthropic = new Anthropic ( { apiKey : process . env . ANTHROPIC_API_KEY } ) // 1. Define tools using builder pattern const tools = [ buildTool ( { name : 'read_file' , description : 'Read a file from disk' , inputSchema : z . object ( { path : z . string ( ) } ) , handler : async ( { path } ) => fs . readFile ( path , 'utf-8' ) , } ) , ] // 2. Build system prompt with cache segments const systemPrompt = buildSystemPrompt ( { static : CORE_RULES , dynamic : '' } ) // 3. Run conversation loop for await ( const event of conversationLoop ( [ { role : 'user' , content : userInput } ] , tools ) ) { if ( event . type === 'text' ) process . stdout . write ( event . text ) } Thinking / Extended Reasoning Config ( docs/08 ) // Control reasoning effort per request type ThinkingConfig = | { type : 'disabled' } | { type : 'enabled' ; budget_tokens : number } // "ultrathink" = maximum budget const EFFORT_LEVELS = { low : { type : 'enabled' , budget_tokens : 1_000 } , medium : { type : 'enabled' , budget_tokens : 5_000 } , high : { type : 'enabled' , budget_tokens : 10_000 } , ultrathink : { type : 'enabled' , budget_tokens : 32_000 } , } satisfies Record < string , ThinkingConfig

const response = await anthropic . messages . create ( { model : 'claude-opus-4-5' , thinking : EFFORT_LEVELS . ultrathink , messages , } ) Troubleshooting Problem Solution Article links 404 Clone the repo — all articles are in docs/ locally Code examples reference internal modules They're illustrative patterns extracted from analysis, not runnable as-is Need the actual Claude Code source See Anthropic's published CLI source Want to contribute an article Open a PR to docs/ following the existing article format Start Here git clone https://github.com/luyao618/Claude-Code-Source-Study cd Claude-Code-Source-Study

Quick route: global understanding (7 articles)

open docs/01-项目全景.md

AI engineering deep dive (9 articles)

open docs/04-System-Prompt-工程.md

Architecture patterns summary (read last)

open docs/25-架构模式总结.md