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refactor: update load-skill-memory command to manual activation and intent-driven loading

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--- ---
name: load-skill-memory name: load-skill-memory
description: Automatically discover and activate SKILL packages based on task context with intelligent matching description: Manually activate specified SKILL package and load documentation based on task intent
argument-hint: "\"task description or file path\"" argument-hint: "<skill_name> \"task intent description\""
allowed-tools: Bash(*), Read(*), Glob(*), Skill(*) allowed-tools: Bash(*), Read(*), Skill(*)
examples:
- /memory:load-skill-memory "分析热模型builder pattern实现"
- /memory:load-skill-memory "修改workflow文档生成逻辑"
- /memory:load-skill-memory "D:\dongdiankaifa9\hydro_generator_module\builders\base.py"
--- ---
# Memory Load SKILL Command (/memory:load-skill-memory) # Memory Load SKILL Command (/memory:load-skill-memory)
## 1. Overview ## 1. Overview
The `memory:load-skill-memory` command **automatically discovers and activates** the most relevant SKILL package based on task description or file path. It dynamically matches user intent against available SKILL descriptions and activates the best match. The `memory:load-skill-memory` command **manually activates a specified SKILL package** and intelligently loads documentation based on user's task intent. The system automatically determines which documentation files to read based on the intent description.
**Core Philosophy**: **Core Philosophy**:
- **Dynamic SKILL Discovery**: Automatically finds relevant SKILL without manual specification - **Manual Activation**: User explicitly specifies which SKILL to activate
- **Intelligent Matching**: Matches task keywords against SKILL descriptions - **Intent-Driven Loading**: System analyzes task intent to determine documentation scope
- **Path-Based Detection**: Recognizes project paths and activates corresponding SKILL - **Intelligent Selection**: Automatically chooses appropriate documentation level and modules
- **Automatic Activation**: Uses Skill() tool to load comprehensive context - **Direct Context Loading**: Loads selected documentation into conversation memory
**When to Use**:
- Manually activate a known SKILL package for a specific task
- Load SKILL context when system hasn't auto-triggered it
- Force reload SKILL documentation with specific intent focus
**Note**: Normal SKILL activation happens automatically via description triggers. Use this command only when manual activation is needed.
## 2. Parameters ## 2. Parameters
- `"task description or file path"` (Required): Task context or file path for SKILL matching - `<skill_name>` (Required): Name of SKILL package to activate
- **Task description**: "分析热模型实现", "修改workflow逻辑", "学习参数系统" - Example: `hydro_generator_module`, `Claude_dms3`
- **File path**: "D:\dongdiankaifa9\hydro_generator_module\builders\base.py" - Must match directory name under `.claude/skills/`
- **Domain keywords**: "thermal modeling", "workflow management", "multi-physics"
- `"task intent description"` (Required): Description of what you want to do
- **Analysis tasks**: "分析builder pattern实现", "理解参数系统架构"
- **Modification tasks**: "修改workflow逻辑", "增强thermal template功能"
- **Learning tasks**: "学习接口设计模式", "了解测试框架使用"
## 3. Execution Flow ## 3. Execution Flow
### Step 1: Discover Available SKILLs ### Step 1: Activate SKILL and Analyze Intent
**List All SKILL Packages**: **Activate SKILL Package**:
```bash
bash(ls -1 .claude/skills/ 2>/dev/null || echo "No SKILLs available")
```
**Read Each SKILL.md for Matching**:
```bash
# For each SKILL directory found
for skill in $(ls -1 .claude/skills/); do
Read(.claude/skills/${skill}/SKILL.md)
done
```
**Extract Matching Information**:
- SKILL name
- Description (with trigger keywords)
- Location path (from description)
- Domain keywords
### Step 2: Match Most Relevant SKILL
**Matching Algorithm**:
1. **Path-Based Matching** (Highest Priority):
- Extract path from user input if provided
- Compare against SKILL location paths in descriptions
- Exact match: `D:\dongdiankaifa9\hydro_generator_module` → `hydro_generator_module` SKILL
2. **Keyword Matching** (Secondary Priority):
- Extract keywords from task description
- Match against SKILL description keywords
- Score each SKILL by keyword overlap count
3. **Action Matching** (Tertiary Priority):
- Detect action verbs: "分析", "修改", "学习", "实现"
- Match against SKILL description triggers
- Prefer SKILLs with matching action patterns
**Scoring Example**:
```javascript ```javascript
Task: "分析热模型builder pattern实现" Skill(command: "${skill_name}")
hydro_generator_module SKILL:
- Path match: No
- Keywords: "热模型"(1), "builder"(1), "实现"(1) = 3 points
- Action match: "analyzing"(1) = 1 point
- Total: 4 points [Winner]
Claude_dms3 SKILL:
- Path match: No
- Keywords: "workflow"(0) = 0 points
- Action match: "analyzing"(1) = 1 point
- Total: 1 point
```
**No Match Handling**:
```
[Warning] No matching SKILL found for: "{task_description}"
Available SKILLs:
- hydro_generator_module - Hydro-generator thermal modeling
- Claude_dms3 - Workflow orchestration system
Generate SKILL for your project: /memory:skill-memory [path]
```
### Step 3: Activate Matched SKILL
**Validation and Activation**:
```javascript
// Validate SKILL existence
skill_path = `.claude/skills/${skill_name}/SKILL.md`
if (!exists(skill_path)) {
list_available_skills()
return error_message
}
// Activate SKILL
Skill(command: "{matched_skill_name}")
``` ```
**What Happens After Activation**: **What Happens After Activation**:
1. System reads `.claude/skills/{matched_skill_name}/SKILL.md` 1. If SKILL exists in memory: System reads `.claude/skills/${skill_name}/SKILL.md`
2. Automatically loads appropriate documentation based on: 2. If SKILL not found in memory: Error - SKILL package doesn't exist
- SKILL description triggers (analyzing, modifying, learning) 3. SKILL description triggers are loaded into memory
- Current conversation context 4. Progressive loading mechanism becomes available
- Memory gaps detection 5. Documentation structure is now accessible
3. Progressive loading levels (0-3) handled automatically
4. Context loaded directly into conversation memory
**Confirmation Output**: **Intent Analysis**:
``` Based on task intent description, system determines:
[OK] Matched and activated SKILL: {matched_skill_name} - **Action type**: analyzing, modifying, learning
Match reason: {path/keyword/action match} - **Scope**: specific module, architecture overview, complete system
Location: {project_path} - **Depth**: quick reference, detailed API, full documentation
Context loaded for: {domain_description}
```
## 4. Matching Strategy ### Step 2: Intelligent Documentation Loading
**SKILL Trigger Patterns**: **Loading Strategy**:
The SKILL.md description includes trigger patterns that automatically activate when: The system automatically selects documentation based on intent keywords:
1. **Keyword Matching**: 1. **Quick Understanding** ("了解", "快速理解", "什么是"):
- User mentions domain keywords (e.g., "热模型", "workflow", "多物理场") - Load: Level 0 (README.md only, ~2K tokens)
- Description keywords match task requirements - Use case: Quick overview of capabilities
2. **Action Detection**: 2. **Specific Module Analysis** ("分析XXX模块", "理解XXX实现"):
- "analyzing" triggers for analysis tasks - Load: Module-specific README.md + API.md (~5K tokens)
- "modifying" triggers for code modification - Use case: Deep dive into specific component
- "learning" triggers for exploration
3. **Memory Gap Detection**: 3. **Architecture Review** ("架构", "设计模式", "整体结构"):
- "especially when no relevant context exists in memory" - Load: README.md + ARCHITECTURE.md (~10K tokens)
- System prioritizes SKILL loading when conversation lacks context - Use case: System design understanding
4. **Path-Based Triggering**: 4. **Implementation/Modification** ("修改", "增强", "实现"):
- User mentions file paths matching SKILL location - Load: Relevant module docs + EXAMPLES.md (~15K tokens)
- "files under this path" clause activates - Use case: Code modification with examples
**Progressive Loading (Automatic)**: 5. **Comprehensive Learning** ("学习", "完整了解", "深入理解"):
- Level 0: ~2K tokens (Quick overview) - Load: Level 3 (All documentation, ~40K tokens)
- Level 1: ~10K tokens (Core modules) - Use case: Complete system mastery
- Level 2: ~25K tokens (Complete system)
- Level 3: ~40K tokens (Full documentation)
System automatically selects appropriate level based on task complexity and context requirements. **Documentation Loaded into Memory**:
After loading, the selected documentation content is available in conversation memory for subsequent operations.
## 5. Usage Examples ## 4. Usage Example
### Example 1: Task-Based Discovery (Keyword Matching)
**User Command**: **User Command**:
```bash ```bash
/memory:load-skill-memory "分析热模型builder pattern实现" /memory:load-skill-memory my_project "修改认证模块增加OAuth支持"
``` ```
**Execution Flow**: **Execution**:
```javascript ```javascript
// Step 1: Discover available SKILLs // Step 1: Activate SKILL
bash(ls -1 .claude/skills/) Skill(command: "my_project")
// Output: hydro_generator_module, Claude_dms3
// Read each SKILL.md // Intent Analysis
Read(.claude/skills/hydro_generator_module/SKILL.md) Keywords: ["修改", "认证模块", "增加", "OAuth"]
Read(.claude/skills/Claude_dms3/SKILL.md) Action: modifying (implementation)
Scope: auth module + examples
// Step 2: Match keywords // Step 2: Load documentation based on intent
Keywords extracted: ["热模型", "builder", "pattern", "实现", "分析"] Read(.workflow/docs/my_project/auth/README.md)
Read(.workflow/docs/my_project/auth/API.md)
Matching scores: Read(.workflow/docs/my_project/EXAMPLES.md)
- hydro_generator_module: 4 points (thermal modeling, builder, analyzing)
- Claude_dms3: 1 point (analyzing only)
Best match: hydro_generator_module
// Step 3: Activate matched SKILL
Skill(command: "hydro_generator_module")
``` ```
**Output**: ## 5. Intent Keyword Mapping
```
[OK] Matched and activated SKILL: hydro_generator_module
Match reason: Keywords ["thermal", "builder"] + Action ["analyzing"]
Location: D:\dongdiankaifa9\hydro_generator_module
Context loaded for: hydro-generator thermal modeling
```
### Example 2: Path-Based Discovery (Direct Path Match) **Quick Reference**:
- **Triggers**: "了解", "快速", "什么是", "简介"
- **Loads**: README.md only (~2K)
**User Command**: **Module-Specific**:
```bash - **Triggers**: "XXX模块", "XXX组件", "分析XXX"
/memory:load-skill-memory "D:\dongdiankaifa9\hydro_generator_module\builders\base.py" - **Loads**: Module README + API (~5K)
```
**Execution Flow**: **Architecture**:
```javascript - **Triggers**: "架构", "设计", "整体结构", "系统设计"
// Step 1: Discover SKILLs - **Loads**: README + ARCHITECTURE (~10K)
bash(ls -1 .claude/skills/)
// Step 2: Match path **Implementation**:
Path extracted: "D:\dongdiankaifa9\hydro_generator_module" - **Triggers**: "修改", "增强", "实现", "开发", "集成"
- **Loads**: Relevant module + EXAMPLES (~15K)
Matching: **Comprehensive**:
- hydro_generator_module location: "D:\dongdiankaifa9\hydro_generator_module" [Exact match] - **Triggers**: "完整", "深入", "全面", "学习整个"
- Claude_dms3 location: "D:\Claude_dms3" [No match] - **Loads**: All documentation (~40K)
Best match: hydro_generator_module (path match - highest priority)
// Step 3: Activate
Skill(command: "hydro_generator_module")
```
**Output**:
```
[OK] Matched and activated SKILL: hydro_generator_module
Match reason: Path match (D:\dongdiankaifa9\hydro_generator_module)
Location: D:\dongdiankaifa9\hydro_generator_module
Context loaded for: hydro-generator thermal modeling
```
### Example 3: Domain Keyword Discovery
**User Command**:
```bash
/memory:load-skill-memory "修改workflow文档生成调度逻辑"
```
**Execution Flow**:
```javascript
// Step 1: Discover SKILLs
bash(ls -1 .claude/skills/)
// Step 2: Match keywords
Keywords: ["workflow", "文档生成", "调度", "修改"]
Matching scores:
- Claude_dms3: 3 points (workflow, docs generation, modifying)
- hydro_generator_module: 1 point (modifying only)
Best match: Claude_dms3
// Step 3: Activate
Skill(command: "Claude_dms3")
```
**Output**:
```
[OK] Matched and activated SKILL: Claude_dms3
Match reason: Keywords ["workflow", "docs"] + Action ["modifying"]
Location: D:\Claude_dms3
Context loaded for: workflow orchestration and documentation
```
## 6. Integration & Token Optimization
### Workflow Integration
**Using SKILL Context for Planning**:
```javascript
// 1. Activate SKILL context
Skill(command: "hydro_generator_module")
// 2. Use loaded context for planning
SlashCommand(command: "/workflow:plan \"增强thermal template支持动态阻抗\"")
// 3. Execute implementation
SlashCommand(command: "/workflow:execute")
```
**Memory Refresh Pattern**:
```javascript
// Refresh SKILL context after code changes
Skill(command: "hydro_generator_module")
// System automatically detects changes and loads updated documentation
```
### Token Optimization Strategy
**Automatic Progressive Loading**:
The SKILL system automatically handles token optimization:
1. **Initial Load**: Starts with minimum required context
2. **On-Demand Escalation**: Loads more documentation if needed
3. **Task-Driven**: Adjusts depth based on task complexity
4. **Memory-Aware**: Avoids loading redundant context
**Token Budget (Automatic)**:
- **Simple queries**: ~2-10K tokens
- **Code analysis**: ~10-25K tokens
- **Implementation**: ~25-40K tokens
**Optimization Benefits**:
- No manual level selection required
- System learns from conversation context
- Efficient memory usage
- Automatic reload when context insufficient
## 7. Error Handling
### SKILL Not Found
```
[Error] SKILL 'unknown_module' not found.
Available SKILLs:
- hydro_generator_module (D:\dongdiankaifa9\hydro_generator_module)
- Claude_dms3 (D:\Claude_dms3)
Activate SKILL: Skill(command: "skill_name")
Generate new SKILL: /memory:skill-memory [path]
```
### Documentation Missing
```
[Warning] SKILL 'hydro_generator_module' exists but documentation incomplete.
Missing files:
- .workflow/docs/hydro_generator_module/ARCHITECTURE.md
Regenerate documentation: /memory:skill-memory --regenerate
```
## 8. Notes
- **Validation First**: Always checks SKILL existence before activation
- **Automatic Loading**: Skill tool handles all documentation reading
- **Session-Scoped**: Activated SKILL context valid for current session
- **Trigger-Based**: Description patterns drive automatic activation
- **Path-Aware**: Triggers on project path mentions
- **Memory-Smart**: Prioritizes loading when conversation lacks context
- **Read-Only**: Does not modify SKILL files or documentation
- **Reactivation**: Can re-activate SKILL to refresh context after changes