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docs: release v4.6.2 - documentation optimization and /memory:load refinement
### Documentation Optimization **Optimized `/memory:load` Command Specification**: - Reduced documentation from 273 to 240 lines (12% reduction) - Merged redundant sections for better information flow - Removed unnecessary internal implementation details - Simplified usage examples while preserving clarity - Maintained all critical information (parameters, workflow, JSON structure) ### Documentation Updates **CHANGELOG.md**: - Added v4.6.2 release entry with documentation improvements **COMMAND_SPEC.md**: - Updated `/memory:load` specification to match actual implementation - Corrected syntax: `[--tool gemini|qwen]` instead of outdated `[--agent] [--json]` flags - Added agent-driven execution details **GETTING_STARTED.md**: - Added "Quick Context Loading for Specific Tasks" section - Positioned between "Full Project Index Rebuild" and "Incremental Related Module Updates" - Includes practical examples and use case guidance **README.md**: - Updated version badge to v4.6.2 - Updated latest release description **COMMAND_REFERENCE.md**: - Added `/memory:load` command reference entry 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
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---
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name: load
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description: Load project memory by delegating to agent, returns structured core content package for subsequent operations
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argument-hint: "[--tool gemini|qwen] \"task context description\""
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allowed-tools: Task(*), Bash(*)
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examples:
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- /memory:load "在当前前端基础上开发用户认证功能"
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- /memory:load --tool qwen "重构支付模块API"
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---
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# Memory Load Command (/memory:load)
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## 1. Overview
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The `memory:load` command **delegates to a general-purpose agent** to analyze the project and return a structured "Core Content Pack". This pack is loaded into the main thread's memory, providing essential context for subsequent agent operations while minimizing token consumption.
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**Core Philosophy**:
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- **Agent-Driven**: Fully delegates execution to general-purpose agent
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- **Read-Only Analysis**: Does not modify code, only extracts context
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- **Structured Output**: Returns standardized JSON content package
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- **Memory Optimization**: Package loaded directly into main thread memory
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- **Token Efficiency**: CLI analysis executed within agent to save tokens
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## 2. Parameters
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- `"task context description"` (Required): Task description to guide context extraction
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- Example: "在当前前端基础上开发用户认证功能"
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- Example: "重构支付模块API"
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- Example: "修复数据库查询性能问题"
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- `--tool <gemini|qwen>` (Optional): Specify CLI tool for agent to use (default: gemini)
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- gemini: Large context window, suitable for complex project analysis
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- qwen: Alternative to Gemini with similar capabilities
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## 3. Agent-Driven Execution Flow
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The command fully delegates to **general-purpose agent**, which autonomously:
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1. **Analyzes Project Structure**: Executes `get_modules_by_depth.sh` to understand architecture
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2. **Loads Documentation**: Reads CLAUDE.md, README.md and other key docs
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3. **Extracts Keywords**: Derives core keywords from task description
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4. **Discovers Files**: Uses MCP code-index or rg/find to locate relevant files
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5. **CLI Deep Analysis**: Executes Gemini/Qwen CLI for deep context analysis
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6. **Generates Content Package**: Returns structured JSON core content package
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## 4. Core Content Package Structure
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**Output Format** - Loaded into main thread memory for subsequent use:
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```json
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{
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"task_context": "在当前前端基础上开发用户认证功能",
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"keywords": ["前端", "用户", "认证", "auth", "login"],
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"project_summary": {
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"architecture": "TypeScript + React frontend with Vite build system",
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"tech_stack": ["React", "TypeScript", "Vite", "TailwindCSS"],
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"key_patterns": [
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"State management via Context API",
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"Functional components with Hooks pattern",
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"API calls encapsulated in custom hooks"
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]
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},
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"relevant_files": [
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{
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"path": "src/components/Auth/LoginForm.tsx",
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"relevance": "Existing login form component",
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"priority": "high"
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},
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{
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"path": "src/contexts/AuthContext.tsx",
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"relevance": "Authentication state management context",
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"priority": "high"
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},
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{
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"path": "CLAUDE.md",
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"relevance": "Project development standards",
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"priority": "high"
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}
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],
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"integration_points": [
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"Must integrate with existing AuthContext",
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"Follow component organization pattern: src/components/[Feature]/",
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"API calls should use src/hooks/useApi.ts wrapper"
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],
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"constraints": [
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"Maintain backward compatibility",
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"Follow TypeScript strict mode",
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"Use existing UI component library"
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]
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}
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```
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## 5. Agent Invocation
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```javascript
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Task(
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subagent_type="general-purpose",
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description="Load project memory: ${task_description}",
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prompt=`
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## Mission: Load Project Memory Context
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**Task Context**: "${task_description}"
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**Mode**: Read-only analysis
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**Tool**: ${tool || 'gemini'}
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## Execution Steps
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### Step 1: Foundation Analysis
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1. **Project Structure**
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\`\`\`bash
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bash(~/.claude/scripts/get_modules_by_depth.sh)
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\`\`\`
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2. **Core Documentation**
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\`\`\`javascript
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Read(CLAUDE.md)
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Read(README.md)
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\`\`\`
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### Step 2: Keyword Extraction & File Discovery
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1. Extract core keywords from task description
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2. Discover relevant files using MCP code-index or rg:
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\`\`\`javascript
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// Prefer MCP tools
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mcp__code-index__find_files(pattern="*{keyword}*")
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mcp__code-index__search_code_advanced(pattern="{keyword}", context_lines=2)
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// Fallback: use rg
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bash(rg -l "{keyword}" --type ts --type md)
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\`\`\`
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### Step 3: Deep Analysis via CLI
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Execute Gemini/Qwen CLI for deep analysis (saves main thread tokens):
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\`\`\`bash
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cd . && ~/.claude/scripts/${tool}-wrapper -p "
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PURPOSE: Extract project core context for task: ${task_description}
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TASK: Analyze project architecture, tech stack, key patterns, relevant files
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MODE: analysis
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CONTEXT: @{CLAUDE.md,README.md,${discovered_files}}
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EXPECTED: Structured project summary and integration point analysis
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RULES:
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- Focus on task-relevant core information
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- Identify key architecture patterns and technical constraints
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- Extract integration points and development standards
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- Output concise, structured format
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"
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\`\`\`
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### Step 4: Generate Core Content Package
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Generate structured JSON content package (format shown above)
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**Required Fields**:
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- task_context: Original task description
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- keywords: Extracted keyword array
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- project_summary: Architecture, tech stack, key patterns
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- relevant_files: File list with path, relevance, priority
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- integration_points: Integration guidance
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- constraints: Development constraints
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### Step 5: Return Content Package
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Return JSON content package as final output for main thread to load into memory.
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## Quality Checklist
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Before returning:
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- [ ] Valid JSON format
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- [ ] All required fields complete
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- [ ] relevant_files contains 3-10 files minimum
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- [ ] project_summary accurately reflects architecture
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- [ ] integration_points clearly specify integration paths
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- [ ] keywords accurately extracted (3-8 keywords)
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- [ ] Content concise, avoiding redundancy (< 5KB total)
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`
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)
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```
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## 6. Usage Examples
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### Example 1: Load Context for New Feature
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```bash
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/memory:load "在当前前端基础上开发用户认证功能"
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```
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**Agent Execution**:
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1. Analyzes project structure (`get_modules_by_depth.sh`)
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2. Reads CLAUDE.md, README.md
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3. Extracts keywords: ["前端", "用户", "认证", "auth"]
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4. Uses MCP to search relevant files
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5. Executes Gemini CLI for deep analysis
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6. Returns core content package
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**Returned Package** (loaded into memory):
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```json
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{
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"task_context": "在当前前端基础上开发用户认证功能",
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"keywords": ["前端", "认证", "auth", "login"],
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"project_summary": { ... },
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"relevant_files": [ ... ],
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"integration_points": [ ... ],
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"constraints": [ ... ]
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}
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```
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### Example 2: Using Qwen Tool
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```bash
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/memory:load --tool qwen "重构支付模块API"
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```
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Agent uses Qwen CLI for analysis, returns same structured package.
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### Example 3: Bug Fix Context
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```bash
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/memory:load "修复登录验证错误"
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```
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Returns core context related to login validation, including test files and validation logic.
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### Memory Persistence
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- **Session-Scoped**: Content package valid for current session
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- **Subsequent Reference**: All subsequent agents/commands can access
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- **Reload Required**: New sessions need to re-execute /memory:load
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## 8. Notes
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- **Read-Only**: Does not modify any code, pure analysis
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- **Token Optimization**: CLI analysis executed within agent, saves main thread tokens
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- **Memory Loading**: Returned JSON loaded directly into main thread memory
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- **Subsequent Use**: Other commands/agents can reference this package for development
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- **Session-Level**: Content package valid for current session
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27
CHANGELOG.md
27
CHANGELOG.md
@@ -5,6 +5,33 @@ All notable changes to Claude Code Workflow (CCW) will be documented in this fil
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The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
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and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
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n## [4.6.2] - 2025-10-20
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### 📝 Documentation Optimization
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#### Improved
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**`/memory:load` Command Documentation**: Optimized command specification from 273 to 240 lines (12% reduction)
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- Merged redundant sections for better information flow
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- Removed unnecessary internal implementation details
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- Simplified usage examples while preserving clarity
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- Maintained all critical information (parameters, workflow, JSON structure)
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- Improved user-centric documentation structure
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#### Updated
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**COMMAND_SPEC.md**: Updated `/memory:load` specification to match actual implementation
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- Corrected syntax: `[--tool gemini|qwen]` instead of outdated `[--agent] [--json]` flags
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- Added agent-driven execution details
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- Clarified core philosophy and token-efficiency benefits
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**GETTING_STARTED.md**: Added "Quick Context Loading for Specific Tasks" section
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- Positioned between "Full Project Index Rebuild" and "Incremental Related Module Updates"
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- Includes practical examples and use case guidance
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- Explains how `/memory:load` works and when to use it
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---
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## [4.6.0] - 2025-10-18
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### 🎯 Concept Clarification & Agent-Driven Analysis
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@@ -127,6 +127,7 @@ Commands for managing individual tasks within a workflow session.
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| Command | Description |
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|---|---|
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| `/memory:update-full` | Complete project-wide CLAUDE.md documentation update. |
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| `/memory:load` | Quickly load key project context into memory based on a task description. |
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| `/memory:update-related` | Context-aware CLAUDE.md documentation updates based on recent changes. |
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| `/version` | Display version information and check for updates. |
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| `/enhance-prompt` | Context-aware prompt enhancement using session memory and codebase analysis. |
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@@ -299,6 +299,27 @@ Commands for managing individual tasks within a workflow session.
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/memory:update-full
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```
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### **/memory:load**
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- **Syntax**: `/memory:load [--tool gemini|qwen] "task context description"`
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- **Parameters**:
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- `"task context description"` (Required, String): Task description to guide context extraction.
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- `--tool <gemini|qwen>` (Optional): Specify CLI tool for agent to use (default: gemini).
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- **Responsibilities**: Delegates to `@general-purpose` agent to analyze the project and return a structured "Core Content Pack". This pack is loaded into the main thread's memory, providing essential context for subsequent operations.
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- **Agent-Driven Execution**: Fully delegates to general-purpose agent which autonomously:
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1. Analyzes project structure and documentation
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2. Extracts keywords from task description
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3. Discovers relevant files using MCP code-index or search tools
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4. Executes Gemini/Qwen CLI for deep analysis
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5. Generates structured JSON content package
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- **Core Philosophy**: Read-only analysis, token-efficient (CLI analysis in agent), structured output
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- **Agent Calls**: `@general-purpose` agent.
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- **Integration**: Provides quick, task-relevant context for subsequent agent operations while minimizing token consumption.
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- **Example**:
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```bash
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/memory:load "在当前前端基础上开发用户认证功能"
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/memory:load --tool qwen "重构支付模块API"
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```
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### **/memory:update-related**
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- **Syntax**: `/memory:update-related [--tool gemini|qwen|codex]`
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- **Responsibilities**: Performs a context-aware update of `CLAUDE.md` files for modules affected by recent git changes.
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@@ -226,6 +226,31 @@ Suitable for large-scale refactoring, architectural changes, or first-time CCW u
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- Weekly routine maintenance
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- When AI output drift is detected
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#### Quick Context Loading for Specific Tasks
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When you need immediate, task-specific context without updating documentation:
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```bash
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# Load context for a specific task into memory
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/memory:load "在当前前端基础上开发用户认证功能"
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# Use alternative CLI tool for analysis
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/memory:load --tool qwen "重构支付模块API"
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```
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**How It Works**:
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- Delegates to an AI agent for autonomous project analysis
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- Discovers relevant files and extracts task-specific keywords
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- Uses CLI tools (Gemini/Qwen) for deep analysis to save tokens
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- Returns a structured "Core Content Pack" loaded into memory
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- Provides context for subsequent agent operations
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**When to Use**:
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- Before starting a new feature or task
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- When you need quick context without full documentation rebuild
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- For task-specific architectural or pattern discovery
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- As preparation for agent-based development workflows
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#### Incremental Related Module Updates
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Suitable for daily development, updating only modules affected by changes:
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@@ -2,7 +2,7 @@
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<div align="center">
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[](https://github.com/catlog22/Claude-Code-Workflow/releases)
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[](https://github.com/catlog22/Claude-Code-Workflow/releases)
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[](LICENSE)
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[]()
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[](https://github.com/modelcontextprotocol)
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@@ -15,7 +15,7 @@
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**Claude Code Workflow (CCW)** transforms AI development from simple prompt chaining into a robust, context-first orchestration system. It solves execution uncertainty and error accumulation through structured planning, deterministic execution, and intelligent multi-model orchestration.
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> **🎉 Latest: v4.6.0** - Concept Clarification & Agent-Driven Analysis. See [CHANGELOG.md](CHANGELOG.md) for details.
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> **🎉 Latest: v4.6.2** - Documentation Optimization & `/memory:load` Command Refinement. See [CHANGELOG.md](CHANGELOG.md) for details.
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> 📚 **New to CCW?** Check out the [**Getting Started Guide**](GETTING_STARTED.md) for a beginner-friendly 5-minute tutorial!
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