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- Corrected syntax: `[--tool gemini|qwen]` instead of outdated `[--agent] [--json]` flags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>
This commit is contained in:
catlog22
2025-10-20 10:58:31 +08:00
parent 436c7909b0
commit 51a0cb3a3c
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@@ -226,6 +226,31 @@ Suitable for large-scale refactoring, architectural changes, or first-time CCW u
- Weekly routine maintenance
- When AI output drift is detected
#### Quick Context Loading for Specific Tasks
When you need immediate, task-specific context without updating documentation:
```bash
# Load context for a specific task into memory
/memory:load "在当前前端基础上开发用户认证功能"
# Use alternative CLI tool for analysis
/memory:load --tool qwen "重构支付模块API"
```
**How It Works**:
- Delegates to an AI agent for autonomous project analysis
- Discovers relevant files and extracts task-specific keywords
- Uses CLI tools (Gemini/Qwen) for deep analysis to save tokens
- Returns a structured "Core Content Pack" loaded into memory
- Provides context for subsequent agent operations
**When to Use**:
- Before starting a new feature or task
- When you need quick context without full documentation rebuild
- For task-specific architectural or pattern discovery
- As preparation for agent-based development workflows
#### Incremental Related Module Updates
Suitable for daily development, updating only modules affected by changes: