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- 更新所有69个命令文件的description字段,基于实际功能重新生成详细描述 - 重新生成5个索引文件(all-commands, by-category, by-use-case, essential-commands, command-relationships) - 移动analyze_commands.py到scripts/目录并完善功能 - 移除临时备份文件 命令描述改进示例: - workflow:plan: 增加了工具和代理的详细说明(Gemini, action-planning-agent) - cli:execute: 说明了YOLO权限和多种执行模式 - memory:update-related: 详细说明了批处理策略和工具回退链 索引文件改进: - usage_scenario从2种扩展到10种(更精细分类) - command-relationships覆盖所有69个命令 - 区分built-in(内置调用)和sequential(用户顺序执行)关系 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
183 lines
6.8 KiB
Markdown
183 lines
6.8 KiB
Markdown
---
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name: load-skill-memory
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description: Activate SKILL package (auto-detect from paths/keywords or manual) and intelligently load documentation based on task intent keywords
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argument-hint: "[skill_name] \"task intent description\""
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allowed-tools: Bash(*), Read(*), Skill(*)
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---
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# Memory Load SKILL Command (/memory:load-skill-memory)
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## 1. Overview
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The `memory:load-skill-memory` command **activates SKILL package** (auto-detect from task or manual specification) and intelligently loads documentation based on user's task intent. The system automatically determines which documentation files to read based on the intent description.
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**Core Philosophy**:
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- **Flexible Activation**: Auto-detect skill from task description/paths, or user explicitly specifies
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- **Intent-Driven Loading**: System analyzes task intent to determine documentation scope
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- **Intelligent Selection**: Automatically chooses appropriate documentation level and modules
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- **Direct Context Loading**: Loads selected documentation into conversation memory
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**When to Use**:
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- Manually activate a known SKILL package for a specific task
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- Load SKILL context when system hasn't auto-triggered it
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- Force reload SKILL documentation with specific intent focus
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**Note**: Normal SKILL activation happens automatically via description triggers or path mentions (system extracts skill name from file paths for intelligent triggering). Use this command only when manual activation is needed.
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## 2. Parameters
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- `[skill_name]` (Optional): Name of SKILL package to activate
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- If omitted: System auto-detects from task description or file paths
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- If specified: Direct activation of named SKILL package
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- Example: `my_project`, `api_service`
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- Must match directory name under `.claude/skills/`
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- `"task intent description"` (Required): Description of what you want to do
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- Used for both: auto-detection (if skill_name omitted) and documentation scope selection
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- **Analysis tasks**: "分析builder pattern实现", "理解参数系统架构"
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- **Modification tasks**: "修改workflow逻辑", "增强thermal template功能"
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- **Learning tasks**: "学习接口设计模式", "了解测试框架使用"
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- **With paths**: "修改D:\projects\my_project\src\auth.py的认证逻辑" (auto-extracts `my_project`)
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## 3. Execution Flow
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### Step 1: Determine SKILL Name (if not provided)
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**Auto-Detection Strategy** (when skill_name parameter is omitted):
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1. **Path Extraction**: Scan task description for file paths
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- Extract potential project names from path segments
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- Example: `"修改D:\projects\my_project\src\auth.py"` → extracts `my_project`
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2. **Keyword Matching**: Match task keywords against SKILL descriptions
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- Search for project-specific terms, domain keywords
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3. **Validation**: Check if extracted name matches `.claude/skills/{skill_name}/`
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**Result**: Either uses provided skill_name or auto-detected name for activation
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### Step 2: Activate SKILL and Analyze Intent
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**Activate SKILL Package**:
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```javascript
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Skill(command: "${skill_name}") // Uses provided or auto-detected name
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```
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**What Happens After Activation**:
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1. If SKILL exists in memory: System reads `.claude/skills/${skill_name}/SKILL.md`
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2. If SKILL not found in memory: Error - SKILL package doesn't exist
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3. SKILL description triggers are loaded into memory
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4. Progressive loading mechanism becomes available
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5. Documentation structure is now accessible
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**Intent Analysis**:
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Based on task intent description, system determines:
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- **Action type**: analyzing, modifying, learning
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- **Scope**: specific module, architecture overview, complete system
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- **Depth**: quick reference, detailed API, full documentation
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### Step 3: Intelligent Documentation Loading
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**Loading Strategy**:
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The system automatically selects documentation based on intent keywords:
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1. **Quick Understanding** ("了解", "快速理解", "什么是"):
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- Load: Level 0 (README.md only, ~2K tokens)
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- Use case: Quick overview of capabilities
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2. **Specific Module Analysis** ("分析XXX模块", "理解XXX实现"):
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- Load: Module-specific README.md + API.md (~5K tokens)
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- Use case: Deep dive into specific component
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3. **Architecture Review** ("架构", "设计模式", "整体结构"):
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- Load: README.md + ARCHITECTURE.md (~10K tokens)
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- Use case: System design understanding
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4. **Implementation/Modification** ("修改", "增强", "实现"):
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- Load: Relevant module docs + EXAMPLES.md (~15K tokens)
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- Use case: Code modification with examples
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5. **Comprehensive Learning** ("学习", "完整了解", "深入理解"):
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- Load: Level 3 (All documentation, ~40K tokens)
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- Use case: Complete system mastery
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**Documentation Loaded into Memory**:
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After loading, the selected documentation content is available in conversation memory for subsequent operations.
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## 4. Usage Examples
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### Example 1: Manual Specification
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**User Command**:
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```bash
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/memory:load-skill-memory my_project "修改认证模块增加OAuth支持"
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```
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**Execution**:
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```javascript
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// Step 1: Use provided skill_name
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skill_name = "my_project" // Directly from parameter
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// Step 2: Activate SKILL
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Skill(command: "my_project")
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// Step 3: Intent Analysis
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Keywords: ["修改", "认证模块", "增加", "OAuth"]
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Action: modifying (implementation)
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Scope: auth module + examples
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// Load documentation based on intent
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Read(.workflow/docs/my_project/auth/README.md)
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Read(.workflow/docs/my_project/auth/API.md)
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Read(.workflow/docs/my_project/EXAMPLES.md)
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```
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### Example 2: Auto-Detection from Path
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**User Command**:
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```bash
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/memory:load-skill-memory "修改D:\projects\my_project\src\services\api.py的接口逻辑"
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```
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**Execution**:
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```javascript
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// Step 1: Auto-detect skill_name from path
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Path detected: "D:\projects\my_project\src\services\api.py"
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Extracted: "my_project"
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Validated: .claude/skills/my_project/ exists ✓
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skill_name = "my_project"
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// Step 2: Activate SKILL
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Skill(command: "my_project")
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// Step 3: Intent Analysis
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Keywords: ["修改", "services", "接口逻辑"]
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Action: modifying (implementation)
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Scope: services module + examples
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// Load documentation based on intent
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Read(.workflow/docs/my_project/services/README.md)
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Read(.workflow/docs/my_project/services/API.md)
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Read(.workflow/docs/my_project/EXAMPLES.md)
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```
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## 5. Intent Keyword Mapping
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**Quick Reference**:
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- **Triggers**: "了解", "快速", "什么是", "简介"
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- **Loads**: README.md only (~2K)
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**Module-Specific**:
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- **Triggers**: "XXX模块", "XXX组件", "分析XXX"
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- **Loads**: Module README + API (~5K)
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**Architecture**:
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- **Triggers**: "架构", "设计", "整体结构", "系统设计"
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- **Loads**: README + ARCHITECTURE (~10K)
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**Implementation**:
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- **Triggers**: "修改", "增强", "实现", "开发", "集成"
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- **Loads**: Relevant module + EXAMPLES (~15K)
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**Comprehensive**:
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- **Triggers**: "完整", "深入", "全面", "学习整个"
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- **Loads**: All documentation (~40K)
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