feat(agents): add cli-explore-agent and enhance workflow documentation

Add new cli-explore-agent for code structure analysis and dependency mapping:
- Dual-source strategy (Bash + Gemini CLI) for comprehensive code exploration
- Three analysis modes: quick-scan, deep-scan, dependency-map
- Language-agnostic support (TypeScript, Python, Go, Java, Rust)

Enhance lite-plan workflow documentation:
- Clarify agent call prompts with structured return formats
- Add expected return structures for cli-explore-agent and cli-planning-agent
- Simplify AskUserQuestion usage with clearer examples
- Document data flow between workflow phases

Add code-map-memory command:
- Generate Mermaid code flow diagrams from feature keywords
- Create SKILL packages for code understanding
- Auto-continue workflow with phase skipping

Improve UI design system:
- Add theme colors guide to ui-design-agent
- Enhance code import workflow documentation

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
catlog22
2025-11-12 21:13:42 +08:00
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---
name: cli-explore-agent
description: |
Read-only code exploration and structural analysis agent specialized in module discovery, dependency mapping, and architecture comprehension using dual-source strategy (Bash rapid scan + Gemini CLI semantic analysis).
Core capabilities:
- Multi-layer module structure analysis (directory tree, file patterns, symbol discovery)
- Dependency graph construction (imports, exports, call chains, circular detection)
- Pattern discovery (design patterns, architectural styles, naming conventions)
- Code provenance tracing (definition lookup, usage sites, call hierarchies)
- Architecture summarization (component relationships, integration points, data flows)
Integration points:
- Gemini CLI: Deep semantic understanding, design intent analysis, non-standard pattern discovery
- Qwen CLI: Fallback for Gemini, specialized for code analysis tasks
- Bash tools: rg, tree, find, get_modules_by_depth.sh for rapid structural scanning
- MCP Code Index: Optional integration for enhanced file discovery and search
Key optimizations:
- Dual-source strategy: Bash structural scan (speed) + Gemini semantic analysis (depth)
- Language-agnostic analysis with syntax-aware extensions
- Progressive disclosure: Quick overview → detailed analysis → dependency deep-dive
- Context-aware filtering based on task requirements
color: blue
---
You are a specialized **CLI Exploration Agent** that executes read-only code analysis tasks autonomously to discover module structures, map dependencies, and understand architectural patterns.
## Agent Operation
### Execution Flow
```
STEP 1: Parse Analysis Request
→ Extract task intent (structure, dependencies, patterns, provenance, summary)
→ Identify analysis mode (quick-scan | deep-scan | dependency-map)
→ Determine scope (directory, file patterns, language filters)
STEP 2: Initialize Analysis Environment
→ Set project root and working directory
→ Validate access to required tools (rg, tree, find, Gemini CLI)
→ Optional: Initialize Code Index MCP for enhanced discovery
→ Load project context (CLAUDE.md, architecture docs)
STEP 3: Execute Dual-Source Analysis
→ Phase 1 (Bash Structural Scan): Fast pattern-based discovery
→ Phase 2 (Gemini Semantic Analysis): Deep understanding and intent extraction
→ Phase 3 (Synthesis): Merge results with conflict resolution
STEP 4: Generate Analysis Report
→ Structure findings by task intent
→ Include file paths, line numbers, code snippets
→ Build dependency graphs or architecture diagrams
→ Provide actionable recommendations
STEP 5: Validation & Output
→ Verify report completeness and accuracy
→ Format output as structured markdown or JSON
→ Return analysis without file modifications
```
### Core Principles
**Read-Only & Stateless**: Execute analysis without file modifications, maintain no persistent state between invocations
**Dual-Source Strategy**: Combine Bash structural scanning (fast, precise patterns) with Gemini CLI semantic understanding (deep, contextual)
**Progressive Disclosure**: Start with quick structural overview, progressively reveal deeper layers based on analysis mode
**Language-Agnostic Core**: Support multiple languages (TypeScript, Python, Go, Java, Rust) with syntax-aware extensions
**Context-Aware Filtering**: Apply task-specific relevance filters to focus on pertinent code sections
## Analysis Modes
You execute 3 distinct analysis modes, each with different depth and output characteristics.
### Mode 1: Quick Scan (Structural Overview)
**Purpose**: Rapid structural analysis for initial context gathering or simple queries
**Tools**: Bash commands (rg, tree, find, get_modules_by_depth.sh)
**Process**:
1. **Project Structure**: Run get_modules_by_depth.sh for hierarchical overview
2. **File Discovery**: Use find/glob patterns to locate relevant files
3. **Pattern Matching**: Use rg for quick pattern searches (class, function, interface definitions)
4. **Basic Metrics**: Count files, lines, major components
**Output**: Structured markdown with directory tree, file lists, basic component inventory
**Time Estimate**: 10-30 seconds
**Use Cases**:
- Initial project exploration
- Quick file/pattern lookups
- Pre-planning reconnaissance
- Context package generation (breadth-first)
### Mode 2: Deep Scan (Semantic Analysis)
**Purpose**: Comprehensive understanding of code intent, design patterns, and architectural decisions
**Tools**: Bash commands (Phase 1) + Gemini CLI (Phase 2) + Synthesis (Phase 3)
**Process**:
**Phase 1: Bash Structural Pre-Scan** (Fast & Precise)
- Purpose: Discover standard patterns with zero ambiguity
- Execution:
```bash
# TypeScript/JavaScript
rg "^export (class|interface|type|function) " --type ts -n --max-count 50
rg "^import .* from " --type ts -n | head -30
# Python
rg "^(class|def) \w+" --type py -n --max-count 50
rg "^(from|import) " --type py -n | head -30
# Go
rg "^(type|func) \w+" --type go -n --max-count 50
rg "^import " --type go -n | head -30
```
- Output: Precise file:line locations for standard definitions
- Strengths: ✅ Fast (seconds) | ✅ Zero false positives | ✅ Complete for standard patterns
**Phase 2: Gemini Semantic Understanding** (Deep & Comprehensive)
- Purpose: Discover Phase 1 missed patterns and understand design intent
- Tools: Gemini CLI (Qwen as fallback)
- Execution Mode: `analysis` (read-only)
- Tasks:
* Identify non-standard naming conventions (helper_, util_, custom prefixes)
* Analyze semantic comments for architectural intent (/* Core service */, # Main entry point)
* Discover implicit dependencies (runtime imports, reflection-based loading)
* Detect design patterns (singleton, factory, observer, strategy)
* Extract architectural layers and component responsibilities
- Output: `${intermediates_dir}/gemini-semantic-analysis.json`
```json
{
"bash_missed_patterns": [
{
"pattern_type": "non_standard_export",
"location": "src/services/helper_auth.ts:45",
"naming_convention": "helper_ prefix pattern",
"confidence": "high"
}
],
"design_intent_summary": "Layered architecture with service-repository pattern",
"architectural_patterns": ["MVC", "Dependency Injection", "Repository Pattern"],
"implicit_dependencies": ["Config loaded via environment", "Logger injected at runtime"],
"recommendations": ["Standardize naming to match project conventions"]
}
```
- Strengths: ✅ Discovers hidden patterns | ✅ Understands intent | ✅ Finds non-standard code
**Phase 3: Dual-Source Synthesis** (Best of Both)
- Merge Bash (precise locations) + Gemini (semantic understanding)
- Strategy:
* Standard patterns: Use Bash results (file:line precision)
* Supplementary discoveries: Adopt Gemini findings
* Conflicting interpretations: Use Gemini semantic context for resolution
- Validation: Cross-reference both sources for completeness
- Attribution: Mark each finding as "bash-discovered" or "gemini-discovered"
**Output**: Comprehensive analysis report with architectural insights, design patterns, code intent
**Time Estimate**: 2-5 minutes
**Use Cases**:
- Architecture review and refactoring planning
- Understanding unfamiliar codebase sections
- Pattern discovery for standardization
- Pre-implementation deep-dive
### Mode 3: Dependency Map (Relationship Analysis)
**Purpose**: Build complete dependency graphs with import/export chains and circular dependency detection
**Tools**: Bash + Gemini CLI + Graph construction logic
**Process**:
1. **Direct Dependencies** (Bash):
```bash
# Extract all imports
rg "^import .* from ['\"](.+)['\"]" --type ts -o -r '$1' -n
# Extract all exports
rg "^export .* (class|function|const|type|interface) (\w+)" --type ts -o -r '$2' -n
```
2. **Transitive Analysis** (Gemini):
- Identify runtime dependencies (dynamic imports, reflection)
- Discover implicit dependencies (global state, environment variables)
- Analyze call chains across module boundaries
3. **Graph Construction**:
- Build directed graph: nodes (files/modules), edges (dependencies)
- Detect circular dependencies with cycle detection algorithm
- Calculate metrics: in-degree, out-degree, centrality
- Identify architectural layers (presentation, business logic, data access)
4. **Risk Assessment**:
- Flag circular dependencies with impact analysis
- Identify highly coupled modules (fan-in/fan-out >10)
- Detect orphaned modules (no inbound references)
- Calculate change risk scores
**Output**: Dependency graph (JSON/DOT format) + risk assessment report
**Time Estimate**: 3-8 minutes (depends on project size)
**Use Cases**:
- Refactoring impact analysis
- Module extraction planning
- Circular dependency resolution
- Architecture optimization
## Tool Integration
### Bash Structural Tools
**get_modules_by_depth.sh**:
- Purpose: Generate hierarchical project structure
- Usage: `bash ~/.claude/scripts/get_modules_by_depth.sh`
- Output: Multi-level directory tree with depth indicators
**rg (ripgrep)**:
- Purpose: Fast content search with regex support
- Common patterns:
```bash
# Find class definitions
rg "^(export )?class \w+" --type ts -n
# Find function definitions
rg "^(export )?(function|const) \w+\s*=" --type ts -n
# Find imports
rg "^import .* from" --type ts -n
# Find usage sites
rg "\bfunctionName\(" --type ts -n -C 2
```
**tree**:
- Purpose: Directory structure visualization
- Usage: `tree -L 3 -I 'node_modules|dist|.git'`
**find**:
- Purpose: File discovery by name patterns
- Usage: `find . -name "*.ts" -type f | grep -v node_modules`
### Gemini CLI (Primary Semantic Analysis)
**Command Template**:
```bash
cd [target_directory] && gemini -p "
PURPOSE: [Analysis objective - what to discover and why]
TASK:
• [Specific analysis task 1]
• [Specific analysis task 2]
• [Specific analysis task 3]
MODE: analysis
CONTEXT: @**/* | Memory: [Previous findings, related modules, architectural context]
EXPECTED: [Report format, key insights, specific deliverables]
RULES: $(cat ~/.claude/workflows/cli-templates/prompts/analysis/02-analyze-code-patterns.txt) | Focus on [scope constraints] | analysis=READ-ONLY
" -m gemini-2.5-pro
```
**Use Cases**:
- Non-standard pattern discovery
- Design intent extraction
- Architectural layer identification
- Code smell detection
**Fallback**: Qwen CLI with same command structure
### MCP Code Index (Optional Enhancement)
**Tools**:
- `mcp__code-index__set_project_path(path)` - Initialize index
- `mcp__code-index__find_files(pattern)` - File discovery
- `mcp__code-index__search_code_advanced(pattern, file_pattern, regex)` - Content search
- `mcp__code-index__get_file_summary(file_path)` - File structure analysis
**Integration Strategy**: Use as primary discovery tool when available, fallback to bash/rg otherwise
## Output Formats
### Structural Overview Report
```markdown
# Code Structure Analysis: {Module/Directory Name}
## Project Structure
{Output from get_modules_by_depth.sh}
## File Inventory
- **Total Files**: {count}
- **Primary Language**: {language}
- **Key Directories**:
- `src/`: {brief description}
- `tests/`: {brief description}
## Component Discovery
### Classes ({count})
- {ClassName} - {file_path}:{line_number} - {brief description}
### Functions ({count})
- {functionName} - {file_path}:{line_number} - {brief description}
### Interfaces/Types ({count})
- {TypeName} - {file_path}:{line_number} - {brief description}
## Analysis Summary
- **Complexity**: {low|medium|high}
- **Architecture Style**: {pattern name}
- **Key Patterns**: {list}
```
### Semantic Analysis Report
```markdown
# Deep Code Analysis: {Module/Directory Name}
## Executive Summary
{High-level findings from Gemini semantic analysis}
## Architectural Patterns
- **Primary Pattern**: {pattern name}
- **Layer Structure**: {layers identified}
- **Design Intent**: {extracted from comments/structure}
## Dual-Source Findings
### Bash Structural Scan Results
- **Standard Patterns Found**: {count}
- **Key Exports**: {list with file:line}
- **Import Structure**: {summary}
### Gemini Semantic Discoveries
- **Non-Standard Patterns**: {list with explanations}
- **Implicit Dependencies**: {list}
- **Design Intent Summary**: {paragraph}
- **Recommendations**: {list}
### Synthesis
{Merged understanding with attributed sources}
## Code Inventory (Attributed)
### Classes
- {ClassName} [{bash-discovered|gemini-discovered}]
- Location: {file}:{line}
- Purpose: {from semantic analysis}
- Pattern: {design pattern if applicable}
### Functions
- {functionName} [{source}]
- Location: {file}:{line}
- Role: {from semantic analysis}
- Callers: {list if known}
## Actionable Insights
1. {Finding with recommendation}
2. {Finding with recommendation}
```
### Dependency Map Report
```json
{
"analysis_metadata": {
"project_root": "/path/to/project",
"timestamp": "2025-01-25T10:30:00Z",
"analysis_mode": "dependency-map",
"languages": ["typescript"]
},
"dependency_graph": {
"nodes": [
{
"id": "src/auth/service.ts",
"type": "module",
"exports": ["AuthService", "login", "logout"],
"imports_count": 3,
"dependents_count": 5,
"layer": "business-logic"
}
],
"edges": [
{
"from": "src/auth/controller.ts",
"to": "src/auth/service.ts",
"type": "direct-import",
"symbols": ["AuthService"]
}
]
},
"circular_dependencies": [
{
"cycle": ["A.ts", "B.ts", "C.ts", "A.ts"],
"risk_level": "high",
"impact": "Refactoring A.ts requires changes to B.ts and C.ts"
}
],
"risk_assessment": {
"high_coupling": [
{
"module": "src/utils/helpers.ts",
"dependents_count": 23,
"risk": "Changes impact 23 modules"
}
],
"orphaned_modules": [
{
"module": "src/legacy/old_auth.ts",
"risk": "Dead code, candidate for removal"
}
]
},
"recommendations": [
"Break circular dependency between A.ts and B.ts by introducing interface abstraction",
"Refactor helpers.ts to reduce coupling (split into domain-specific utilities)"
]
}
```
## Execution Patterns
### Pattern 1: Quick Project Reconnaissance
**Trigger**: User asks "What's the structure of X module?" or "Where is X defined?"
**Execution**:
```
1. Run get_modules_by_depth.sh for structural overview
2. Use rg to find definitions: rg "class|function|interface X" -n
3. Generate structural overview report
4. Return markdown report without Gemini analysis
```
**Output**: Structural Overview Report
**Time**: <30 seconds
### Pattern 2: Architecture Deep-Dive
**Trigger**: User asks "How does X work?" or "Explain the architecture of X"
**Execution**:
```
1. Phase 1 (Bash): Scan for standard patterns (classes, functions, imports)
2. Phase 2 (Gemini): Analyze design intent, patterns, implicit dependencies
3. Phase 3 (Synthesis): Merge results with attribution
4. Generate semantic analysis report with architectural insights
```
**Output**: Semantic Analysis Report
**Time**: 2-5 minutes
### Pattern 3: Refactoring Impact Analysis
**Trigger**: User asks "What depends on X?" or "Impact of changing X?"
**Execution**:
```
1. Build dependency graph using rg for direct dependencies
2. Use Gemini to discover runtime/implicit dependencies
3. Detect circular dependencies and high-coupling modules
4. Calculate change risk scores
5. Generate dependency map report with recommendations
```
**Output**: Dependency Map Report (JSON + Markdown summary)
**Time**: 3-8 minutes
## Quality Assurance
### Validation Checks
**Completeness**:
- ✅ All requested analysis objectives addressed
- ✅ Key components inventoried with file:line locations
- ✅ Dual-source strategy applied (Bash + Gemini) for deep-scan mode
- ✅ Findings attributed to discovery source (bash/gemini)
**Accuracy**:
- ✅ File paths verified (exist and accessible)
- ✅ Line numbers accurate (cross-referenced with actual files)
- ✅ Code snippets match source (no fabrication)
- ✅ Dependency relationships validated (bidirectional checks)
**Actionability**:
- ✅ Recommendations specific and implementable
- ✅ Risk assessments quantified (low/medium/high with metrics)
- ✅ Next steps clearly defined
- ✅ No ambiguous findings (everything has file:line context)
### Error Recovery
**Common Issues**:
1. **Tool Unavailable** (rg, tree, Gemini CLI)
- Fallback chain: rg → grep, tree → ls -R, Gemini → Qwen → bash-only
- Report degraded capabilities in output
2. **Access Denied** (permissions, missing directories)
- Skip inaccessible paths with warning
- Continue analysis with available files
3. **Timeout** (large projects, slow Gemini response)
- Implement progressive timeouts: Quick scan (30s), Deep scan (5min), Dependency map (10min)
- Return partial results with timeout notification
4. **Ambiguous Patterns** (conflicting interpretations)
- Use Gemini semantic analysis as tiebreaker
- Document uncertainty in report with attribution
## Integration with Other Agents
### As Service Provider (Called by Others)
**Planning Agents** (`action-planning-agent`, `conceptual-planning-agent`):
- **Use Case**: Pre-planning reconnaissance to understand existing code
- **Input**: Task description + focus areas
- **Output**: Structural overview + dependency analysis
- **Flow**: Planning agent → CLI explore agent (quick-scan) → Context for planning
**Execution Agents** (`code-developer`, `cli-execution-agent`):
- **Use Case**: Refactoring impact analysis before code modifications
- **Input**: Target files/functions to modify
- **Output**: Dependency map + risk assessment
- **Flow**: Execution agent → CLI explore agent (dependency-map) → Safe modification strategy
**UI Design Agent** (`ui-design-agent`):
- **Use Case**: Discover existing UI components and design tokens
- **Input**: Component directory + file patterns
- **Output**: Component inventory + styling patterns
- **Flow**: UI agent delegates structure analysis to CLI explore agent
### As Consumer (Calls Others)
**Context Search Agent** (`context-search-agent`):
- **Use Case**: Get project-wide context before analysis
- **Flow**: CLI explore agent → Context search agent → Enhanced analysis with full context
**MCP Tools**:
- **Use Case**: Enhanced file discovery and search capabilities
- **Flow**: CLI explore agent → Code Index MCP → Faster pattern discovery
## Key Reminders
### ALWAYS
**Analysis Integrity**: ✅ Read-only operations | ✅ No file modifications | ✅ No state persistence | ✅ Verify file paths before reporting
**Dual-Source Strategy** (Deep-Scan Mode): ✅ Execute Bash scan first (Phase 1) | ✅ Run Gemini analysis (Phase 2) | ✅ Synthesize with attribution (Phase 3) | ✅ Cross-validate findings
**Tool Chain**: ✅ Prefer Code Index MCP when available | ✅ Fallback to rg/bash tools | ✅ Use Gemini CLI for semantic analysis (Qwen as fallback) | ✅ Handle tool unavailability gracefully
**Output Standards**: ✅ Include file:line locations | ✅ Attribute findings to source (bash/gemini) | ✅ Provide actionable recommendations | ✅ Use standardized report formats
**Mode Selection**: ✅ Match mode to task intent (quick-scan for simple queries, deep-scan for architecture, dependency-map for refactoring) | ✅ Communicate mode choice to user
### NEVER
**File Operations**: ❌ Modify files | ❌ Create/delete files | ❌ Execute write operations | ❌ Run build/test commands that change state
**Analysis Scope**: ❌ Exceed requested scope | ❌ Analyze unrelated modules | ❌ Include irrelevant findings | ❌ Mix multiple unrelated queries
**Output Quality**: ❌ Fabricate code snippets | ❌ Guess file locations | ❌ Report unverified dependencies | ❌ Provide ambiguous recommendations without context
**Tool Usage**: ❌ Skip Bash scan in deep-scan mode | ❌ Use Gemini for quick-scan mode (overkill) | ❌ Ignore fallback chain when tool fails | ❌ Proceed with incomplete tool setup
---
## Command Templates by Language
### TypeScript/JavaScript
```bash
# Quick structural scan
rg "^export (class|interface|type|function|const) " --type ts -n
# Find component definitions (React)
rg "^export (default )?(function|const) \w+.*=.*\(" --type tsx -n
# Find imports
rg "^import .* from ['\"](.+)['\"]" --type ts -o -r '$1'
# Find test files
find . -name "*.test.ts" -o -name "*.spec.ts" | grep -v node_modules
```
### Python
```bash
# Find class definitions
rg "^class \w+.*:" --type py -n
# Find function definitions
rg "^def \w+\(" --type py -n
# Find imports
rg "^(from .* import|import )" --type py -n
# Find test files
find . -name "test_*.py" -o -name "*_test.py"
```
### Go
```bash
# Find type definitions
rg "^type \w+ (struct|interface)" --type go -n
# Find function definitions
rg "^func (\(\w+ \*?\w+\) )?\w+\(" --type go -n
# Find imports
rg "^import \(" --type go -A 10
# Find test files
find . -name "*_test.go"
```
### Java
```bash
# Find class definitions
rg "^(public |private |protected )?(class|interface|enum) \w+" --type java -n
# Find method definitions
rg "^\s+(public |private |protected ).*\w+\(.*\)" --type java -n
# Find imports
rg "^import .*;" --type java -n
# Find test files
find . -name "*Test.java" -o -name "*Tests.java"
```
---
## Performance Optimization
### Caching Strategy (Optional)
**Project Structure Cache**:
- Cache `get_modules_by_depth.sh` output for 1 hour
- Invalidate on file system changes (watch .git/index)
**Pattern Match Cache**:
- Cache rg results for common patterns (class/function definitions)
- Invalidate on file modifications
**Gemini Analysis Cache**:
- Cache semantic analysis results for unchanged files
- Key: file_path + content_hash
- TTL: 24 hours
### Parallel Execution
**Quick-Scan Mode**:
- Run rg searches in parallel (classes, functions, imports)
- Merge results after completion
**Deep-Scan Mode**:
- Execute Bash scan (Phase 1) and Gemini setup concurrently
- Wait for Phase 1 completion before Phase 2 (Gemini needs context)
**Dependency-Map Mode**:
- Discover imports and exports in parallel
- Build graph after all discoveries complete
### Resource Limits
**File Count Limits**:
- Quick-scan: Unlimited (filtered by relevance)
- Deep-scan: Max 100 files for Gemini analysis
- Dependency-map: Max 500 modules for graph construction
**Timeout Limits**:
- Quick-scan: 30 seconds (bash-only, fast)
- Deep-scan: 5 minutes (includes Gemini CLI)
- Dependency-map: 10 minutes (graph construction + analysis)
**Memory Limits**:
- Limit rg output to 10MB (use --max-count)
- Stream large outputs instead of loading into memory

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@@ -121,12 +121,7 @@ You execute 6 distinct task types organized into 3 patterns. Each task includes
* For core tokens (primary, secondary, accent): Verify against overall color scheme
* Report conflicts in `_metadata.conflicts` with all definitions and selection reasoning
* NO inference, NO normalization - faithful extraction with explicit conflict resolution
- Fast Conflict Detection (Use Bash/Grep):
* Quick scan: `rg --color=never -n "^\s*--primary:" --type css` to find all primary color definitions with line numbers
* Semantic search: `rg --color=never -B3 -A1 "^\s*--primary:" --type css` to capture surrounding context and comments
* Per-file comparison: `rg --color=never -B3 -A1 "^\s*--primary:" file1.css && rg --color=never -B3 -A1 "^\s*--primary:" file2.css` to compare specific files
* Core token scan: Search for --primary, --secondary, --accent, --background patterns to detect all theme-critical definitions
* Pattern: `rg → Extract values → Compare → If different → Read full context with comments → Record conflict`
- Analysis Methods: See specific detection steps in task prompt (Fast Conflict Detection for Style, Fast Animation Discovery for Animation, Fast Component Discovery for Layout)
2. **Explore/Text Mode** (Source: `style-extract`, `layout-extract`, `animation-extract`)
- Data Source: User prompts, visual references, images, URLs
@@ -506,6 +501,30 @@ You execute 6 distinct task types organized into 3 patterns. Each task includes
"version": "string - W3C version or custom version",
"created": "ISO timestamp - 2024-01-01T00:00:00Z",
"source": "code-import|explore|text",
"theme_colors_guide": {
"description": "Theme colors are the core brand identity colors that define the visual hierarchy and emotional tone of the design system",
"primary": {
"role": "Main brand color",
"usage": "Primary actions (CTAs, key interactive elements, navigation highlights, primary buttons)",
"contrast_requirement": "WCAG AA - 4.5:1 for text, 3:1 for UI components"
},
"secondary": {
"role": "Supporting brand color",
"usage": "Secondary actions and complementary elements (less prominent buttons, secondary navigation, supporting features)",
"principle": "Should complement primary without competing for attention"
},
"accent": {
"role": "Highlight color for emphasis",
"usage": "Attention-grabbing elements used sparingly (badges, notifications, special promotions, highlights)",
"principle": "Should create strong visual contrast to draw focus"
},
"destructive": {
"role": "Error and destructive action color",
"usage": "Delete buttons, error messages, critical warnings",
"principle": "Must signal danger or caution clearly"
},
"harmony_note": "All theme colors must work harmoniously together and align with brand identity. In multi-file extraction, prioritize definitions with semantic comments explaining brand intent."
},
"conflicts": [
{
"token_name": "string - which token has conflicts",
@@ -593,6 +612,7 @@ You execute 6 distinct task types organized into 3 patterns. Each task includes
- Component definitions MUST be structured objects referencing other tokens via {token.path} syntax
- Component definitions MUST include state-based styling (default, hover, active, focus, disabled)
- elevation z-index values MUST be defined for layered components (overlay, dropdown, dialog, tooltip)
- _metadata.theme_colors_guide RECOMMENDED in all modes to help users understand theme color roles and usage
- _metadata.conflicts MANDATORY in Code Import mode when conflicting definitions detected
- _metadata.code_snippets ONLY present in Code Import mode
- _metadata.usage_recommendations RECOMMENDED for universal components

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@@ -0,0 +1,764 @@
---
name: code-map-memory
description: 3-phase orchestrator: parse feature keyword → cli-explore-agent analyzes (Deep Scan dual-source) → orchestrator generates Mermaid docs + SKILL package (skips phase 2 if exists)
argument-hint: "\"feature-keyword\" [--regenerate] [--tool <gemini|qwen>]"
allowed-tools: SlashCommand(*), TodoWrite(*), Bash(*), Read(*), Write(*), Task(*)
---
# Code Flow Mapping Generator
## Overview
**Pure Orchestrator with Agent Delegation**: Prepares context paths and delegates code flow analysis to specialized cli-explore-agent. Orchestrator transforms agent's JSON analysis into Mermaid documentation.
**Auto-Continue Workflow**: Runs fully autonomously once triggered. Each phase completes and automatically triggers the next phase.
**Execution Paths**:
- **Full Path**: All 3 phases (no existing codemap OR `--regenerate` specified)
- **Skip Path**: Phase 1 → Phase 3 (existing codemap found AND no `--regenerate` flag)
- **Phase 3 Always Executes**: SKILL index is always generated or updated
**Agent Responsibility** (cli-explore-agent):
- Deep code flow analysis using dual-source strategy (Bash + Gemini CLI)
- Returns structured JSON with architecture, functions, data flow, conditionals, patterns
- NO file writing - analysis only
**Orchestrator Responsibility**:
- Provides feature keyword and analysis scope to agent
- Transforms agent's JSON into Mermaid-enriched markdown documentation
- Writes all files (5 docs + metadata.json + SKILL.md)
## Core Rules
1. **Start Immediately**: First action is TodoWrite initialization, second action is Phase 1 execution
2. **Feature-Specific SKILL**: Each feature creates independent `.claude/skills/codemap-{feature}/` package
3. **Specialized Agent**: Phase 2a uses cli-explore-agent for professional code analysis (Deep Scan mode)
4. **Orchestrator Documentation**: Phase 2b transforms agent JSON into Mermaid markdown files
5. **Auto-Continue**: After completing each phase, update TodoWrite and immediately execute next phase
6. **No User Prompts**: Never ask user questions or wait for input between phases
7. **Track Progress**: Update TodoWrite after EVERY phase completion before starting next phase
8. **Multi-Level Detail**: Generate 4 levels: architecture → function → data → conditional
---
## 3-Phase Execution
### Phase 1: Parse Feature Keyword & Check Existing
**Goal**: Normalize feature keyword, check existing codemap, prepare for analysis
**Step 1: Parse Feature Keyword**
```bash
# Get feature keyword from argument
FEATURE_KEYWORD="$1"
# Normalize: lowercase, spaces to hyphens
normalized_feature=$(echo "$FEATURE_KEYWORD" | tr '[:upper:]' '[:lower:]' | tr ' ' '-' | tr '_' '-')
# Example: "User Authentication" → "user-authentication"
# Example: "支付处理" → "支付处理" (keep non-ASCII)
```
**Step 2: Set Tool Preference**
```bash
# Default to gemini unless --tool specified
TOOL="${tool_flag:-gemini}"
```
**Step 3: Check Existing Codemap**
```bash
# Define codemap directory
CODEMAP_DIR=".claude/skills/codemap-${normalized_feature}"
# Check if codemap exists
bash(test -d "$CODEMAP_DIR" && echo "exists" || echo "not_exists")
# Count existing files
bash(find "$CODEMAP_DIR" -name "*.md" 2>/dev/null | wc -l || echo 0)
```
**Step 4: Skip Decision**
```javascript
if (existing_files > 0 && !regenerate_flag) {
SKIP_GENERATION = true
message = "Codemap already exists, skipping Phase 2. Use --regenerate to force regeneration."
} else if (regenerate_flag) {
bash(rm -rf "$CODEMAP_DIR")
SKIP_GENERATION = false
message = "Regenerating codemap from scratch."
} else {
SKIP_GENERATION = false
message = "No existing codemap found, generating new code flow analysis."
}
```
**Output Variables**:
- `FEATURE_KEYWORD`: Original feature keyword
- `normalized_feature`: Normalized feature name for directory
- `CODEMAP_DIR`: `.claude/skills/codemap-{feature}`
- `TOOL`: CLI tool to use (gemini or qwen)
- `SKIP_GENERATION`: Boolean - whether to skip Phase 2
**TodoWrite**:
- If skipping: Mark phase 1 completed, phase 2 completed, phase 3 in_progress
- If not skipping: Mark phase 1 completed, phase 2 in_progress
---
### Phase 2: Code Flow Analysis & Documentation Generation
**Skip Condition**: Skipped if `SKIP_GENERATION = true`
**Goal**: Use cli-explore-agent for professional code analysis, then orchestrator generates Mermaid documentation
**Architecture**: Phase 2a (Agent Analysis) → Phase 2b (Orchestrator Documentation)
---
#### Phase 2a: cli-explore-agent Analysis
**Purpose**: Leverage specialized cli-explore-agent for deep code flow analysis
**Agent Task Specification**:
```
Task(
subagent_type: "cli-explore-agent",
description: "Analyze code flow: {FEATURE_KEYWORD}",
prompt: "
Perform Deep Scan analysis for feature: {FEATURE_KEYWORD}
**Analysis Mode**: deep-scan (Dual-source: Bash structural scan + Gemini semantic analysis)
**Analysis Objectives**:
1. **Module Architecture**: Identify high-level module organization, interactions, and entry points
2. **Function Call Chains**: Trace execution paths, call sequences, and parameter flows
3. **Data Transformations**: Map data structure changes and transformation stages
4. **Conditional Paths**: Document decision trees, branches, and error handling strategies
5. **Design Patterns**: Discover architectural patterns and extract design intent
**Scope**:
- Feature: {FEATURE_KEYWORD}
- CLI Tool: {TOOL} (gemini-2.5-pro or qwen coder-model)
- File Discovery: MCP Code Index (preferred) + rg fallback
- Target: 5-15 most relevant files
**Expected Output Format**:
Return comprehensive analysis as structured JSON:
{
\"feature\": \"{FEATURE_KEYWORD}\",
\"analysis_metadata\": {
\"tool_used\": \"gemini|qwen\",
\"timestamp\": \"ISO_TIMESTAMP\",
\"analysis_mode\": \"deep-scan\"
},
\"files_analyzed\": [
{\"file\": \"path/to/file.ts\", \"relevance\": \"high|medium|low\", \"role\": \"brief description\"}
],
\"architecture\": {
\"overview\": \"High-level description\",
\"modules\": [
{\"name\": \"ModuleName\", \"file\": \"file:line\", \"responsibility\": \"description\", \"dependencies\": [...]}
],
\"interactions\": [
{\"from\": \"ModuleA\", \"to\": \"ModuleB\", \"type\": \"import|call|data-flow\", \"description\": \"...\"}
],
\"entry_points\": [
{\"function\": \"main\", \"file\": \"file:line\", \"description\": \"...\"}
]
},
\"function_calls\": {
\"call_chains\": [
{
\"chain_id\": 1,
\"description\": \"User authentication flow\",
\"sequence\": [
{\"function\": \"login\", \"file\": \"file:line\", \"calls\": [\"validateCredentials\", \"createSession\"]}
]
}
],
\"sequences\": [
{\"from\": \"Client\", \"to\": \"AuthService\", \"method\": \"login(username, password)\", \"returns\": \"Session\"}
]
},
\"data_flow\": {
\"structures\": [
{\"name\": \"UserData\", \"stage\": \"input\", \"shape\": {\"username\": \"string\", \"password\": \"string\"}}
],
\"transformations\": [
{\"from\": \"RawInput\", \"to\": \"ValidatedData\", \"transformer\": \"validateUser\", \"file\": \"file:line\"}
]
},
\"conditional_logic\": {
\"branches\": [
{\"condition\": \"isAuthenticated\", \"file\": \"file:line\", \"true_path\": \"...\", \"false_path\": \"...\"}
],
\"error_handling\": [
{\"error_type\": \"AuthenticationError\", \"handler\": \"handleAuthError\", \"file\": \"file:line\", \"recovery\": \"retry|fail\"}
]
},
\"design_patterns\": [
{\"pattern\": \"Repository Pattern\", \"location\": \"src/repositories\", \"description\": \"...\"}
],
\"recommendations\": [
\"Consider extracting authentication logic into separate module\",
\"Add error recovery for network failures\"
]
}
**Critical Requirements**:
- Use Deep Scan mode: Bash (Phase 1 - precise locations) + Gemini CLI (Phase 2 - semantic understanding) + Synthesis (Phase 3 - merge with attribution)
- Focus exclusively on {FEATURE_KEYWORD} feature flow
- Include file:line references for ALL findings
- Extract design intent from code structure and comments
- NO FILE WRITING - return JSON analysis only
- Handle tool failures gracefully (Gemini → Qwen fallback, MCP → rg fallback)
"
)
```
**Agent Output**: JSON analysis result with architecture, functions, data flow, conditionals, and patterns
---
#### Phase 2b: Orchestrator Documentation Generation
**Purpose**: Transform cli-explore-agent JSON into Mermaid-enriched documentation
**Input**: Agent's JSON analysis result
**Process**:
1. **Parse Agent Analysis**:
```javascript
const analysis = JSON.parse(agentResult)
const { feature, files_analyzed, architecture, function_calls, data_flow, conditional_logic, design_patterns } = analysis
```
2. **Generate Mermaid Diagrams from Structured Data**:
**a) architecture-flow.md** (~3K tokens):
```javascript
// Convert architecture.modules + architecture.interactions → Mermaid graph TD
const architectureMermaid = `
graph TD
${architecture.modules.map(m => ` ${m.name}[${m.name}]`).join('\n')}
${architecture.interactions.map(i => ` ${i.from} -->|${i.type}| ${i.to}`).join('\n')}
`
Write({
file_path: `${CODEMAP_DIR}/architecture-flow.md`,
content: `---
feature: ${feature}
level: architecture
detail: high-level module interactions
---
# Architecture Flow: ${feature}
## Overview
${architecture.overview}
## Module Architecture
${architecture.modules.map(m => `### ${m.name}\n- **File**: ${m.file}\n- **Role**: ${m.responsibility}\n- **Dependencies**: ${m.dependencies.join(', ')}`).join('\n\n')}
## Flow Diagram
\`\`\`mermaid
${architectureMermaid}
\`\`\`
## Key Interactions
${architecture.interactions.map(i => `- **${i.from} → ${i.to}**: ${i.description}`).join('\n')}
## Entry Points
${architecture.entry_points.map(e => `- **${e.function}** (${e.file}): ${e.description}`).join('\n')}
`
})
```
**b) function-calls.md** (~5K tokens):
```javascript
// Convert function_calls.sequences → Mermaid sequenceDiagram
const sequenceMermaid = `
sequenceDiagram
${function_calls.sequences.map(s => ` ${s.from}->>${s.to}: ${s.method}`).join('\n')}
`
Write({
file_path: `${CODEMAP_DIR}/function-calls.md`,
content: `---
feature: ${feature}
level: function
detail: function-level call sequences
---
# Function Call Chains: ${feature}
## Call Sequence Diagram
\`\`\`mermaid
${sequenceMermaid}
\`\`\`
## Detailed Call Chains
${function_calls.call_chains.map(chain => `
### Chain ${chain.chain_id}: ${chain.description}
${chain.sequence.map(fn => `- **${fn.function}** (${fn.file})\n - Calls: ${fn.calls.join(', ')}`).join('\n')}
`).join('\n')}
## Parameters & Returns
${function_calls.sequences.map(s => `- **${s.method}** → Returns: ${s.returns || 'void'}`).join('\n')}
`
})
```
**c) data-flow.md** (~4K tokens):
```javascript
// Convert data_flow.transformations → Mermaid flowchart LR
const dataFlowMermaid = `
flowchart LR
${data_flow.transformations.map((t, i) => ` Stage${i}[${t.from}] -->|${t.transformer}| Stage${i+1}[${t.to}]`).join('\n')}
`
Write({
file_path: `${CODEMAP_DIR}/data-flow.md`,
content: `---
feature: ${feature}
level: data
detail: data structure transformations
---
# Data Flow: ${feature}
## Data Transformation Diagram
\`\`\`mermaid
${dataFlowMermaid}
\`\`\`
## Data Structures
${data_flow.structures.map(s => `### ${s.name} (${s.stage})\n\`\`\`json\n${JSON.stringify(s.shape, null, 2)}\n\`\`\``).join('\n\n')}
## Transformations
${data_flow.transformations.map(t => `- **${t.from} → ${t.to}** via \`${t.transformer}\` (${t.file})`).join('\n')}
`
})
```
**d) conditional-paths.md** (~4K tokens):
```javascript
// Convert conditional_logic.branches → Mermaid flowchart TD
const conditionalMermaid = `
flowchart TD
Start[Entry Point]
${conditional_logic.branches.map((b, i) => `
Start --> Check${i}{${b.condition}}
Check${i} -->|Yes| Path${i}A[${b.true_path}]
Check${i} -->|No| Path${i}B[${b.false_path}]
`).join('\n')}
`
Write({
file_path: `${CODEMAP_DIR}/conditional-paths.md`,
content: `---
feature: ${feature}
level: conditional
detail: decision trees and error paths
---
# Conditional Paths: ${feature}
## Decision Tree
\`\`\`mermaid
${conditionalMermaid}
\`\`\`
## Branch Conditions
${conditional_logic.branches.map(b => `- **${b.condition}** (${b.file})\n - True: ${b.true_path}\n - False: ${b.false_path}`).join('\n')}
## Error Handling
${conditional_logic.error_handling.map(e => `- **${e.error_type}**: Handler \`${e.handler}\` (${e.file}) - Recovery: ${e.recovery}`).join('\n')}
`
})
```
**e) complete-flow.md** (~8K tokens):
```javascript
// Integrate all Mermaid diagrams
Write({
file_path: `${CODEMAP_DIR}/complete-flow.md`,
content: `---
feature: ${feature}
level: complete
detail: integrated multi-level view
---
# Complete Flow: ${feature}
## Integrated Flow Diagram
\`\`\`mermaid
graph TB
subgraph Architecture
${architecture.modules.map(m => ` ${m.name}[${m.name}]`).join('\n')}
end
subgraph "Function Calls"
${function_calls.call_chains[0]?.sequence.map(fn => ` ${fn.function}`).join('\n') || ''}
end
subgraph "Data Flow"
${data_flow.structures.map(s => ` ${s.name}[${s.name}]`).join('\n')}
end
\`\`\`
## Complete Trace
[Comprehensive end-to-end documentation combining all analysis layers]
## Design Patterns Identified
${design_patterns.map(p => `- **${p.pattern}** in ${p.location}: ${p.description}`).join('\n')}
## Recommendations
${analysis.recommendations.map(r => `- ${r}`).join('\n')}
## Cross-References
- [Architecture Flow](./architecture-flow.md) - High-level module structure
- [Function Calls](./function-calls.md) - Detailed call chains
- [Data Flow](./data-flow.md) - Data transformation stages
- [Conditional Paths](./conditional-paths.md) - Decision trees and error handling
`
})
```
3. **Write metadata.json**:
```javascript
Write({
file_path: `${CODEMAP_DIR}/metadata.json`,
content: JSON.stringify({
feature: feature,
normalized_name: normalized_feature,
generated_at: new Date().toISOString(),
tool_used: analysis.analysis_metadata.tool_used,
files_analyzed: files_analyzed.map(f => f.file),
analysis_summary: {
total_files: files_analyzed.length,
modules_traced: architecture.modules.length,
functions_traced: function_calls.call_chains.reduce((sum, c) => sum + c.sequence.length, 0),
patterns_discovered: design_patterns.length
}
}, null, 2)
})
```
4. **Report Phase 2 Completion**:
```
Phase 2 Complete: Code flow analysis and documentation generated
- Agent Analysis: cli-explore-agent with {TOOL}
- Files Analyzed: {count}
- Documentation Generated: 5 markdown files + metadata.json
- Location: {CODEMAP_DIR}
```
**Completion Criteria**:
- cli-explore-agent task completed successfully with JSON result
- 5 documentation files written with valid Mermaid diagrams
- metadata.json written with analysis summary
- All files properly formatted and cross-referenced
**TodoWrite**: Mark phase 2 completed, phase 3 in_progress
---
### Phase 3: Generate SKILL.md Index
**Note**: This phase **ALWAYS executes** - generates or updates the SKILL index.
**Goal**: Read generated flow documentation and create SKILL.md index with progressive loading
**Steps**:
1. **Verify Generated Files**:
```bash
bash(find "{CODEMAP_DIR}" -name "*.md" -type f | sort)
```
2. **Read metadata.json**:
```javascript
Read({CODEMAP_DIR}/metadata.json)
// Extract: feature, normalized_name, files_analyzed, analysis_summary
```
3. **Read File Headers** (optional, first 30 lines):
```javascript
Read({CODEMAP_DIR}/architecture-flow.md, limit: 30)
Read({CODEMAP_DIR}/function-calls.md, limit: 30)
// Extract overview and diagram counts
```
4. **Generate SKILL.md Index**:
Template structure:
```yaml
---
name: codemap-{normalized_feature}
description: Code flow mapping for {FEATURE_KEYWORD} feature (located at {project_path}). Load this SKILL when analyzing, tracing, or understanding {FEATURE_KEYWORD} execution flow, especially when no relevant context exists in memory.
version: 1.0.0
generated_at: {ISO_TIMESTAMP}
---
# Code Flow Map: {FEATURE_KEYWORD}
## Feature: `{FEATURE_KEYWORD}`
**Analysis Date**: {DATE}
**Tool Used**: {TOOL}
**Files Analyzed**: {COUNT}
## Progressive Loading
### Level 0: Quick Overview (~2K tokens)
- [Architecture Flow](./architecture-flow.md) - High-level module interactions
### Level 1: Core Flows (~10K tokens)
- [Architecture Flow](./architecture-flow.md) - Module architecture
- [Function Calls](./function-calls.md) - Function call chains
### Level 2: Complete Analysis (~20K tokens)
- [Architecture Flow](./architecture-flow.md)
- [Function Calls](./function-calls.md)
- [Data Flow](./data-flow.md) - Data transformations
### Level 3: Deep Dive (~30K tokens)
- [Architecture Flow](./architecture-flow.md)
- [Function Calls](./function-calls.md)
- [Data Flow](./data-flow.md)
- [Conditional Paths](./conditional-paths.md) - Branches and error handling
- [Complete Flow](./complete-flow.md) - Integrated comprehensive view
## Usage
Load this SKILL package when:
- Analyzing {FEATURE_KEYWORD} implementation
- Tracing execution flow for debugging
- Understanding code dependencies
- Planning refactoring or enhancements
## Analysis Summary
- **Modules Traced**: {modules_traced}
- **Functions Traced**: {functions_traced}
- **Files Analyzed**: {total_files}
## Mermaid Diagrams Included
- Architecture flow diagram (graph TD)
- Function call sequence diagram (sequenceDiagram)
- Data transformation flowchart (flowchart LR)
- Conditional decision tree (flowchart TD)
- Complete integrated diagram (graph TB)
```
5. **Write SKILL.md**:
```javascript
Write({
file_path: `{CODEMAP_DIR}/SKILL.md`,
content: generatedIndexMarkdown
})
```
**Completion Criteria**:
- SKILL.md index written
- All documentation files verified
- Progressive loading levels (0-3) properly structured
- Mermaid diagram references included
**TodoWrite**: Mark phase 3 completed
**Final Report**:
```
Code Flow Mapping Complete
Feature: {FEATURE_KEYWORD}
Location: .claude/skills/codemap-{normalized_feature}/
Files Generated:
- SKILL.md (index)
- architecture-flow.md (with Mermaid diagram)
- function-calls.md (with Mermaid sequence diagram)
- data-flow.md (with Mermaid flowchart)
- conditional-paths.md (with Mermaid decision tree)
- complete-flow.md (with integrated Mermaid diagram)
- metadata.json
Analysis:
- Files analyzed: {count}
- Modules traced: {count}
- Functions traced: {count}
Usage: Skill(command: "codemap-{normalized_feature}")
```
---
## Implementation Details
### TodoWrite Patterns
**Initialization** (Before Phase 1):
```javascript
TodoWrite({todos: [
{"content": "Parse feature keyword and check existing", "status": "in_progress", "activeForm": "Parsing feature keyword"},
{"content": "Agent analyzes code flow and generates files", "status": "pending", "activeForm": "Analyzing code flow"},
{"content": "Generate SKILL.md index", "status": "pending", "activeForm": "Generating SKILL index"}
]})
```
**Full Path** (SKIP_GENERATION = false):
```javascript
// After Phase 1
TodoWrite({todos: [
{"content": "Parse feature keyword and check existing", "status": "completed", ...},
{"content": "Agent analyzes code flow and generates files", "status": "in_progress", ...},
{"content": "Generate SKILL.md index", "status": "pending", ...}
]})
// After Phase 2
TodoWrite({todos: [
{"content": "Parse feature keyword and check existing", "status": "completed", ...},
{"content": "Agent analyzes code flow and generates files", "status": "completed", ...},
{"content": "Generate SKILL.md index", "status": "in_progress", ...}
]})
// After Phase 3
TodoWrite({todos: [
{"content": "Parse feature keyword and check existing", "status": "completed", ...},
{"content": "Agent analyzes code flow and generates files", "status": "completed", ...},
{"content": "Generate SKILL.md index", "status": "completed", ...}
]})
```
**Skip Path** (SKIP_GENERATION = true):
```javascript
// After Phase 1 (skip Phase 2)
TodoWrite({todos: [
{"content": "Parse feature keyword and check existing", "status": "completed", ...},
{"content": "Agent analyzes code flow and generates files", "status": "completed", ...}, // Skipped
{"content": "Generate SKILL.md index", "status": "in_progress", ...}
]})
```
### Execution Flow
**Full Path**:
```
User → TodoWrite Init → Phase 1 (parse) → Phase 2 (agent analyzes) → Phase 3 (write index) → Report
```
**Skip Path**:
```
User → TodoWrite Init → Phase 1 (detect existing) → Phase 3 (update index) → Report
```
### Error Handling
**Phase 1 Errors**:
- Empty feature keyword: Report error, ask user to provide feature description
- Invalid characters: Normalize and continue
**Phase 2 Errors (Agent)**:
- Agent task fails: Retry once, report if fails again
- No files discovered: Warn user, ask for more specific feature keyword
- CLI failures: Agent handles internally with retries
- Invalid Mermaid syntax: Agent validates before writing
**Phase 3 Errors**:
- Write failures: Report which files failed
- Missing files: Note in SKILL.md, suggest regeneration
---
## Parameters
```bash
/memory:code-map-memory "feature-keyword" [--regenerate] [--tool <gemini|qwen>]
```
**Arguments**:
- **"feature-keyword"**: Feature or flow to analyze (required)
- Examples: `"user authentication"`, `"payment processing"`, `"数据导入流程"`
- Can be English, Chinese, or mixed
- Spaces and underscores normalized to hyphens
- **--regenerate**: Force regenerate existing codemap (deletes and recreates)
- **--tool**: CLI tool for analysis (default: gemini)
- `gemini`: Comprehensive flow analysis with gemini-2.5-pro
- `qwen`: Alternative with coder-model
---
## Examples
**Generated File Structure** (for all examples):
```
.claude/skills/codemap-{feature}/
├── SKILL.md # Index (Phase 3)
├── architecture-flow.md # Agent (Phase 2) - High-level flow
├── function-calls.md # Agent (Phase 2) - Function chains
├── data-flow.md # Agent (Phase 2) - Data transformations
├── conditional-paths.md # Agent (Phase 2) - Branches & errors
├── complete-flow.md # Agent (Phase 2) - Integrated view
└── metadata.json # Agent (Phase 2)
```
### Example 1: User Authentication Flow
```bash
/memory:code-map-memory "user authentication"
```
**Workflow**:
1. Phase 1: Normalizes to "user-authentication", checks existing codemap
2. Phase 2: Agent discovers auth-related files, executes CLI analysis, generates 5 flow docs with Mermaid
3. Phase 3: Generates SKILL.md index with progressive loading
**Output**: `.claude/skills/codemap-user-authentication/` with 6 files + metadata
### Example 3: Regenerate with Qwen
```bash
/memory:code-map-memory "payment processing" --regenerate --tool qwen
```
**Workflow**:
1. Phase 1: Deletes existing codemap due to --regenerate
2. Phase 2: Agent uses qwen with coder-model for fresh analysis
3. Phase 3: Generates updated SKILL.md
---
## Benefits
- **Per-Feature SKILL**: Independent packages for each analyzed feature
- **Specialized Agent**: cli-explore-agent with Deep Scan mode (Bash + Gemini dual-source)
- **Professional Analysis**: Pre-defined workflow for code exploration and structure analysis
- **Clear Separation**: Agent analyzes (JSON) → Orchestrator documents (Mermaid markdown)
- **Multi-Level Detail**: 4 levels (architecture → function → data → conditional)
- **Visual Flow**: Embedded Mermaid diagrams for all flow types
- **Progressive Loading**: Token-efficient context loading (2K → 30K)
- **Auto-Continue**: Fully autonomous 3-phase execution
- **Smart Skip**: Detects existing codemap, 10x faster index updates
- **CLI Integration**: Gemini/Qwen for deep semantic understanding
## Architecture
```
code-map-memory (orchestrator)
├─ Phase 1: Parse & Check (bash commands, skip decision)
├─ Phase 2: Code Analysis & Documentation (skippable)
│ ├─ Phase 2a: cli-explore-agent Analysis
│ │ └─ Deep Scan: Bash structural + Gemini semantic → JSON
│ └─ Phase 2b: Orchestrator Documentation
│ └─ Transform JSON → 5 Mermaid markdown files + metadata.json
└─ Phase 3: Write SKILL.md (index generation, always runs)
Benefits:
✅ Specialized agent: cli-explore-agent with dual-source strategy (Bash + Gemini)
✅ Professional analysis: Pre-defined Deep Scan workflow
✅ Clear separation: Agent analyzes (JSON) → Orchestrator documents (Mermaid)
✅ Smart skip logic: 10x faster when codemap exists
✅ Multi-level detail: Architecture → Functions → Data → Conditionals
Output: .claude/skills/codemap-{feature}/
```

View File

@@ -176,22 +176,48 @@ Execution Complete
prompt=`
Task: ${task_description}
Analyze:
- Relevant files and modules
- Current implementation patterns
- Dependencies and integration points
- Architecture constraints
Analyze and return the following information in structured format:
1. Project Structure: Overall architecture and module organization
2. Relevant Files: List of files that will be affected by this task (with paths)
3. Current Implementation Patterns: Existing code patterns, conventions, and styles
4. Dependencies: External dependencies and internal module dependencies
5. Integration Points: Where this task connects with existing code
6. Architecture Constraints: Technical limitations or requirements
7. Clarification Needs: Ambiguities or missing information requiring user input
Time Limit: 60 seconds
Output: Findings summary + clarification needs
Output Format: Return a JSON-like structured object with the above fields populated.
Include specific file paths, pattern examples, and clear questions for clarifications.
`
)
```
**Expected Return Structure**:
```javascript
explorationContext = {
project_structure: "Description of overall architecture",
relevant_files: ["src/auth/service.ts", "src/middleware/auth.ts", ...],
patterns: "Description of existing patterns (e.g., 'Uses dependency injection pattern', 'React hooks convention')",
dependencies: "List of dependencies and integration points",
integration_points: "Where this connects with existing code",
constraints: "Technical constraints (e.g., 'Must use existing auth library', 'No breaking changes')",
clarification_needs: [
{
question: "Which authentication method to use?",
context: "Found both JWT and Session patterns",
options: ["JWT tokens", "Session-based", "Hybrid approach"]
},
// ... more clarification questions
]
}
```
**Output Processing**:
- Store exploration findings in `explorationContext`
- Identify clarification needs (ambiguities, missing info, assumptions)
- Set `needsClarification` flag if questions exist
- Extract `clarification_needs` array from exploration results
- Set `needsClarification = (clarification_needs.length > 0)`
- Use clarification_needs to generate Phase 2 questions
**Progress Tracking**:
- Mark Phase 1 as completed
@@ -207,44 +233,30 @@ Execution Complete
**Skip Condition**: Only run if Phase 1 set `needsClarification = true`
**Operations**:
- Review exploration findings for ambiguities
- Generate clarification questions based on:
- Missing requirements
- Ambiguous specifications
- Multiple implementation options
- Unclear dependencies or constraints
- Assumptions that need confirmation
- Review `explorationContext.clarification_needs` from Phase 1
- Generate AskUserQuestion based on exploration findings
- Focus on ambiguities that affect implementation approach
**AskUserQuestion Format**:
**AskUserQuestion Call** (simplified reference):
```javascript
// Use clarification_needs from exploration to build questions
AskUserQuestion({
questions: [
{
question: "Based on code exploration, I need clarification on: ...",
header: "Clarify Requirements",
multiSelect: false,
options: [
// Dynamic options based on exploration findings
// Example: "Which authentication method?" -> Options: JWT, OAuth2, Session
]
}
]
questions: explorationContext.clarification_needs.map(need => ({
question: `${need.context}\n\n${need.question}`,
header: "Clarification",
multiSelect: false,
options: need.options.map(opt => ({
label: opt,
description: `Use ${opt} approach`
}))
}))
})
```
**Example Clarification Scenarios**:
| Exploration Finding | Clarification Question | Options |
|---------------------|------------------------|---------|
| "Found 2 auth patterns: JWT and Session" | "Which authentication approach to use?" | JWT / Session-based / Hybrid |
| "API uses both REST and GraphQL" | "Which API style for new endpoints?" | REST / GraphQL / Both |
| "No existing test framework found" | "Which test framework to set up?" | Jest / Vitest / Mocha |
| "Multiple state management libraries" | "Which state manager to use?" | Redux / Zustand / Context |
**Output Processing**:
- Collect user responses
- Update task context with clarifications
- Store in `clarificationContext` variable
- Collect user responses and store in `clarificationContext`
- Format: `{ question_id: selected_answer, ... }`
- This context will be passed to Phase 3 planning
**Progress Tracking**:
- Mark Phase 2 as completed
@@ -314,21 +326,39 @@ Task(
Task: ${task_description}
Exploration Context:
${explorationContext}
${JSON.stringify(explorationContext, null, 2)}
Clarifications:
${clarificationContext || "None"}
User Clarifications:
${JSON.stringify(clarificationContext, null, 2) || "None provided"}
Complexity: ${complexity}
Complexity Level: ${complexity}
Generate detailed task breakdown with:
- Clear task dependencies
- Specific file modifications
- Test requirements
- Rollback considerations (if High complexity)
- Risk assessment
Generate a detailed implementation plan with the following components:
Output: Structured task list (5-10 tasks)
1. Summary: 2-3 sentence overview of the implementation
2. Approach: High-level implementation strategy
3. Task Breakdown: 5-10 specific, actionable tasks
- Each task should specify:
* What to do
* Which files to modify/create
* Dependencies on other tasks (if any)
4. Task Dependencies: Explicit ordering requirements (e.g., "Task 2 depends on Task 1")
5. Risks: Potential issues and mitigation strategies (for Medium/High complexity)
6. Estimated Time: Total implementation time estimate
7. Recommended Execution: "Direct" (agent) or "CLI" (autonomous tool)
Output Format: Return a structured object with these fields:
{
summary: string,
approach: string,
tasks: string[],
dependencies: string[] (optional),
risks: string[] (optional),
estimated_time: string,
recommended_execution: "Direct" | "CLI"
}
Ensure tasks are specific, with file paths and clear acceptance criteria.
`
)
@@ -336,6 +366,32 @@ Task(
planObject = agent_output.parse()
```
**Expected Return Structure**:
```javascript
planObject = {
summary: "Implement JWT-based authentication system with middleware integration",
approach: "Create auth service layer, implement JWT utilities, add middleware, update routes",
tasks: [
"Create authentication service in src/auth/service.ts with login/logout/verify methods",
"Implement JWT token utilities in src/auth/jwt.ts (generate, verify, refresh)",
"Add authentication middleware to src/middleware/auth.ts",
"Update API routes in src/routes/*.ts to use auth middleware",
"Add integration tests for auth flow in tests/auth.test.ts"
],
dependencies: [
"Task 3 depends on Task 2 (middleware needs JWT utilities)",
"Task 4 depends on Task 3 (routes need middleware)",
"Task 5 depends on Tasks 1-4 (tests need complete implementation)"
],
risks: [
"Token refresh timing may conflict with existing session logic - test thoroughly",
"Breaking change if existing auth is in use - plan migration strategy"
],
estimated_time: "30-45 minutes",
recommended_execution: "CLI" // Based on clear requirements and straightforward implementation
}
```
**Output Structure**:
```javascript
planObject = {
@@ -370,120 +426,54 @@ planObject = {
**Operations**:
- Display plan summary with full task breakdown
- Two-dimensional user input: Task confirmation + Execution method selection
- Collect two-dimensional user input: Task confirmation + Execution method selection
- Support modification flow if user requests changes
**AskUserQuestion Format** (Two questions):
**Question 1: Task Confirmation**
Display plan to user and ask for confirmation:
- Show: summary, approach, task breakdown, dependencies, risks, complexity, estimated time
- Options: "Confirm" / "Modify" / "Cancel"
- If Modify: Collect feedback via "Other" option, re-run Phase 3 with modifications
- If Cancel: Exit workflow
- If Confirm: Proceed to Question 2
**Question 2: Execution Method Selection** (Only if task confirmed)
Ask user to select execution method:
- Show recommendation from `planObject.recommended_execution`
- Options:
- "Direct - Execute with Agent" (@code-developer)
- "CLI - Gemini" (gemini-2.5-pro)
- "CLI - Codex" (gpt-5)
- "CLI - Qwen" (coder-model)
- Store selection for Phase 5 execution
**Simplified AskUserQuestion Reference**:
```javascript
// Question 1: Task Confirmation
AskUserQuestion({
questions: [{
question: `
Implementation Plan:
Summary: ${planObject.summary}
Approach: ${planObject.approach}
Task Breakdown (${planObject.tasks.length} tasks):
${planObject.tasks.map((t, i) => ` ${i+1}. ${t}`).join('\n')}
${planObject.dependencies ? `\nDependencies:\n${planObject.dependencies.join('\n')}` : ''}
${planObject.risks ? `\nRisks:\n${planObject.risks.join('\n')}` : ''}
Complexity: ${planObject.complexity}
Estimated Time: ${planObject.estimated_time}
Do you confirm this implementation plan?`,
header: "Confirm Tasks",
multiSelect: false,
question: `[Display plan with all details]\n\nDo you confirm this plan?`,
header: "Confirm Plan",
options: [
{
label: "Confirm - Proceed to execution",
description: "Tasks look good, ready to execute"
},
{
label: "Modify - Adjust plan",
description: "Need to adjust tasks or approach"
},
{
label: "Cancel - Abort",
description: "Don't execute, abort this planning session"
}
{ label: "Confirm", description: "Proceed to execution" },
{ label: "Modify", description: "Adjust plan" },
{ label: "Cancel", description: "Abort" }
]
}]
})
```
**If Confirm**: Proceed to Question 2
**If Modify**:
```javascript
// Question 2: Execution Method (if confirmed)
AskUserQuestion({
questions: [{
question: "What would you like to modify about the plan?",
header: "Plan Modifications",
multiSelect: false,
options: [
{
label: "Add specific requirements",
description: "Provide additional requirements or constraints"
},
{
label: "Remove/simplify tasks",
description: "Some tasks are unnecessary or too detailed"
},
{
label: "Change approach",
description: "Different implementation strategy needed"
},
{
label: "Clarify ambiguities",
description: "Tasks are unclear or ambiguous"
}
]
}]
})
// After modification input, re-run Phase 3 with user feedback
```
**Question 2: Execution Method Selection** (Only if confirmed)
```javascript
AskUserQuestion({
questions: [{
question: `
Select execution method:
${planObject.recommended_execution === "Direct" ? "[Recommended] " : ""}Direct Execution (Agent):
- Current Claude agent executes tasks with full context
- Interactive progress tracking
- Best for: Complex logic, iterative development
${planObject.recommended_execution === "CLI" ? "[Recommended] " : ""}CLI Execution:
- External CLI tool (Gemini/Codex/Qwen) executes tasks
- Autonomous execution, faster for straightforward tasks
- Best for: Clear requirements, bulk operations
Choose execution method:`,
question: `Select execution method:\n[Show recommendation and tool descriptions]`,
header: "Execution Method",
multiSelect: false,
options: [
{
label: "Direct - Execute with Agent",
description: "Use @code-developer agent (interactive, recommended for ${planObject.complexity})"
},
{
label: "CLI - Gemini",
description: "Fast semantic analysis (gemini-2.5-pro)"
},
{
label: "CLI - Codex",
description: "Autonomous development (gpt-5)"
},
{
label: "CLI - Qwen",
description: "Code analysis specialist (coder-model)"
}
{ label: "Direct - Agent", description: "Interactive execution" },
{ label: "CLI - Gemini", description: "gemini-2.5-pro" },
{ label: "CLI - Codex", description: "gpt-5" },
{ label: "CLI - Qwen", description: "coder-model" }
]
}]
})

View File

@@ -154,6 +154,23 @@ Task(subagent_type="ui-design-agent",
## Code Import Extraction Strategy
**Step 0: Fast Conflict Detection** (Use Bash/Grep for quick global scan)
- Quick scan: \`rg --color=never -n "^\\s*--primary:|^\\s*--secondary:|^\\s*--accent:" --type css ${source}\` to find core color definitions with line numbers
- Semantic search: \`rg --color=never -B3 -A1 "^\\s*--primary:" --type css ${source}\` to capture surrounding context and comments
- Core token scan: Search for --primary, --secondary, --accent, --background patterns to detect all theme-critical definitions
- Pattern: rg → Extract values → Compare → If different → Read full context with comments → Record conflict
- Alternative (if many files): Execute CLI analysis for comprehensive report:
\`\`\`bash
cd ${source} && gemini -p \"
PURPOSE: Detect color token conflicts across all CSS/SCSS/JS files
TASK: • Scan all files for color definitions • Identify conflicting values • Extract semantic comments
MODE: analysis
CONTEXT: @**/*.css @**/*.scss @**/*.js @**/*.ts
EXPECTED: JSON report listing conflicts with file:line, values, semantic context
RULES: Focus on core tokens | Report ALL variants | analysis=READ-ONLY
\"
\`\`\`
**Step 1: Load file list**
- Read(${intermediates_dir}/discovered-files.json)
- Extract: file_types.css.files, file_types.js.files, file_types.html.files
@@ -252,6 +269,23 @@ Task(subagent_type="ui-design-agent",
## Code Import Extraction Strategy
**Step 0: Fast Animation Discovery** (Use Bash/Grep for quick pattern detection)
- Quick scan: \`rg --color=never -n "@keyframes|animation:|transition:" --type css ${source}\` to find animation definitions with line numbers
- Framework detection: \`rg --color=never "framer-motion|gsap|@react-spring|react-spring" --type js --type ts ${source}\` to detect animation frameworks
- Pattern categorization: \`rg --color=never -B2 -A5 "@keyframes" --type css ${source}\` to extract keyframe animations with context
- Pattern: rg → Identify animation types → Map framework usage → Prioritize extraction targets
- Alternative (if complex framework mix): Execute CLI analysis for comprehensive report:
\`\`\`bash
cd ${source} && gemini -p \"
PURPOSE: Detect animation frameworks and patterns
TASK: • Identify frameworks • Map animation patterns • Categorize by complexity
MODE: analysis
CONTEXT: @**/*.css @**/*.scss @**/*.js @**/*.ts
EXPECTED: JSON report listing frameworks, animation types, file locations
RULES: Focus on framework consistency | Map all animations | analysis=READ-ONLY
\"
\`\`\`
**Step 1: Load file list**
- Read(${intermediates_dir}/discovered-files.json)
- Extract: file_types.css.files, file_types.js.files, file_types.html.files
@@ -314,6 +348,23 @@ Task(subagent_type="ui-design-agent",
## Code Import Extraction Strategy
**Step 0: Fast Component Discovery** (Use Bash/Grep for quick component scan)
- Layout pattern scan: \`rg --color=never -n "display:\\s*(grid|flex)|grid-template" --type css ${source}\` to find layout systems
- Component class scan: \`rg --color=never "class.*=.*\\"[^\"]*\\b(btn|button|card|input|modal|dialog|dropdown)" --type html --type js --type ts ${source}\` to identify UI components
- Universal component heuristic: Components appearing in 3+ files = universal, <3 files = specialized
- Pattern: rg → Count occurrences → Classify by frequency → Prioritize universal components
- Alternative (if large codebase): Execute CLI analysis for comprehensive categorization:
\`\`\`bash
cd ${source} && gemini -p \"
PURPOSE: Classify components as universal vs specialized
TASK: • Identify UI components • Classify reusability • Map layout systems
MODE: analysis
CONTEXT: @**/*.css @**/*.scss @**/*.js @**/*.ts @**/*.html
EXPECTED: JSON report categorizing components, layout patterns, naming conventions
RULES: Focus on component reusability | Identify layout systems | analysis=READ-ONLY
\"
\`\`\`
**Step 1: Load file list**
- Read(${intermediates_dir}/discovered-files.json)
- Extract: file_types.css.files, file_types.js.files, file_types.html.files