Enhance skill generator documentation and templates

- Updated Phase 1 and Phase 2 documentation to include next phase links and data flow details.
- Expanded Phase 5 documentation to include comprehensive validation and README generation steps, along with validation report structure.
- Added purpose and usage context sections to various action and script templates (e.g., autonomous-action, llm-action, script-bash).
- Improved commands management by simplifying the command scanning logic and enabling/disabling commands through renaming files.
- Enhanced dashboard command manager to format group names and display nested groups with appropriate icons and colors.
- Updated LiteLLM executor to allow model overrides during execution.
- Added action reference guide and template reference sections to the skill-tuning SKILL.md for better navigation and understanding.
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---
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
**MANDATORY FIRST STEP**:
Read: ~/.claude/workflows/cli-templates/schemas/codemap-json-schema.json
**Output**: Return JSON following schema exactly. NO FILE WRITING - return JSON analysis only.
**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
---
## 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)
Output: .claude/skills/codemap-{feature}/
```

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---
name: docs
description: Plan documentation workflow with dynamic grouping (≤10 docs/task), generates IMPL tasks for parallel module trees, README, ARCHITECTURE, and HTTP API docs
argument-hint: "[path] [--tool <gemini|qwen|codex>] [--mode <full|partial>] [--cli-execute]"
---
# Documentation Workflow (/memory:docs)
## Overview
Lightweight planner that analyzes project structure, decomposes documentation work into tasks, and generates execution plans. Does NOT generate documentation content itself - delegates to doc-generator agent.
**Execution Strategy**:
- **Dynamic Task Grouping**: Level 1 tasks grouped by top-level directories with document count limit
- **Primary constraint**: Each task generates ≤10 documents (API.md + README.md count)
- **Optimization goal**: Prefer grouping 2 top-level directories per task for context sharing
- **Conflict resolution**: If 2 dirs exceed 10 docs, reduce to 1 dir/task; if 1 dir exceeds 10 docs, split by subdirectories
- **Context benefit**: Same-task directories analyzed together via single Gemini call
- **Parallel Execution**: Multiple Level 1 tasks execute concurrently for faster completion
- **Pre-computed Analysis**: Phase 2 performs unified analysis once, stored in `.process/` for reuse
- **Efficient Data Loading**: All existing docs loaded once in Phase 2, shared across tasks
**Path Mirroring**: Documentation structure mirrors source code under `.workflow/docs/{project_name}/`
- Example: `my_app/src/core/``.workflow/docs/my_app/src/core/API.md`
**Two Execution Modes**:
- **Default (Agent Mode)**: CLI analyzes in `pre_analysis` (MODE=analysis), agent writes docs
- **--cli-execute (CLI Mode)**: CLI generates docs in `implementation_approach` (MODE=write), agent executes CLI commands
## Path Mirroring Strategy
**Principle**: Documentation structure **mirrors** source code structure under project-specific directory.
| Source Path | Project Name | Documentation Path |
|------------|--------------|-------------------|
| `my_app/src/core/` | `my_app` | `.workflow/docs/my_app/src/core/API.md` |
| `my_app/src/modules/auth/` | `my_app` | `.workflow/docs/my_app/src/modules/auth/API.md` |
| `another_project/lib/utils/` | `another_project` | `.workflow/docs/another_project/lib/utils/API.md` |
## Parameters
```bash
/memory:docs [path] [--tool <gemini|qwen|codex>] [--mode <full|partial>] [--cli-execute]
```
- **path**: Source directory to analyze (default: current directory)
- Specifies the source code directory to be documented
- Documentation is generated in a separate `.workflow/docs/{project_name}/` directory at the workspace root, **not** within the source `path` itself
- The source path's structure is mirrored within the project-specific documentation folder
- Example: analyzing `src/modules` produces documentation at `.workflow/docs/{project_name}/src/modules/`
- **--mode**: Documentation generation mode (default: full)
- `full`: Complete documentation (modules + README + ARCHITECTURE + EXAMPLES + HTTP API)
- `partial`: Module documentation only (API.md + README.md)
- **--tool**: CLI tool selection (default: gemini)
- `gemini`: Comprehensive documentation, pattern recognition
- `qwen`: Architecture analysis, system design focus
- `codex`: Implementation validation, code quality
- **--cli-execute**: Enable CLI-based documentation generation (optional)
## Planning Workflow
### Phase 1: Initialize Session
```bash
# Get target path, project name, and root
bash(pwd && basename "$(pwd)" && git rev-parse --show-toplevel 2>/dev/null || pwd && date +%Y%m%d-%H%M%S)
```
```javascript
// Create docs session (type: docs)
SlashCommand(command="/workflow:session:start --type docs --new \"{project_name}-docs-{timestamp}\"")
// Parse output to get sessionId
```
```bash
# Update workflow-session.json with docs-specific fields
bash(jq '. + {"target_path":"{target_path}","project_root":"{project_root}","project_name":"{project_name}","mode":"full","tool":"gemini","cli_execute":false}' .workflow/active/{sessionId}/workflow-session.json > tmp.json && mv tmp.json .workflow/active/{sessionId}/workflow-session.json)
```
### Phase 2: Analyze Structure
**Smart filter**: Auto-detect and skip tests/build/config/vendor based on project tech stack.
**Commands** (collect data with simple bash):
```bash
# 1. Run folder analysis
bash(ccw tool exec get_modules_by_depth '{}' | ccw tool exec classify_folders '{}')
# 2. Get top-level directories (first 2 path levels)
bash(ccw tool exec get_modules_by_depth '{}' | ccw tool exec classify_folders '{}' | awk -F'|' '{print $1}' | sed 's|^\./||' | awk -F'/' '{if(NF>=2) print $1"/"$2; else if(NF==1) print $1}' | sort -u)
# 3. Find existing docs (if directory exists)
bash(if [ -d .workflow/docs/\${project_name} ]; then find .workflow/docs/\${project_name} -type f -name "*.md" ! -path "*/README.md" ! -path "*/ARCHITECTURE.md" ! -path "*/EXAMPLES.md" ! -path "*/api/*" 2>/dev/null; fi)
# 4. Read existing docs content (if files exist)
bash(if [ -d .workflow/docs/\${project_name} ]; then find .workflow/docs/\${project_name} -type f -name "*.md" ! -path "*/README.md" ! -path "*/ARCHITECTURE.md" ! -path "*/EXAMPLES.md" ! -path "*/api/*" 2>/dev/null | xargs cat 2>/dev/null; fi)
```
**Data Processing**: Parse bash outputs, calculate statistics, use **Write tool** to create `${session_dir}/.process/doc-planning-data.json` with structure:
```json
{
"metadata": {
"generated_at": "2025-11-03T16:57:30.469669",
"project_name": "project_name",
"project_root": "/path/to/project"
},
"folder_analysis": [
{"path": "./src/core", "type": "code", "code_count": 5, "dirs_count": 2}
],
"top_level_dirs": ["src/modules", "lib/core"],
"existing_docs": {
"file_list": [".workflow/docs/project/src/core/API.md"],
"content": "... existing docs content ..."
},
"unified_analysis": [],
"statistics": {
"total": 15,
"code": 8,
"navigation": 7,
"top_level": 3
}
}
```
**Then** use **Edit tool** to update `workflow-session.json` adding analysis field.
**Output**: Single `doc-planning-data.json` with all analysis data (no temp files or Python scripts).
**Auto-skipped**: Tests (`**/test/**`, `**/*.test.*`), Build (`**/node_modules/**`, `**/dist/**`), Config (root-level files), Vendor directories.
### Phase 3: Detect Update Mode
**Commands**:
```bash
# Count existing docs from doc-planning-data.json
bash(cat .workflow/active/WFS-docs-{timestamp}/.process/doc-planning-data.json | jq '.existing_docs.file_list | length')
```
**Data Processing**: Use count result, then use **Edit tool** to update `workflow-session.json`:
- Add `"update_mode": "update"` if count > 0, else `"create"`
- Add `"existing_docs": <count>`
### Phase 4: Decompose Tasks
**Task Hierarchy** (Dynamic based on document count):
```
Small Projects (total ≤10 docs):
Level 1: IMPL-001 (all directories in single task, shared context)
Level 2: IMPL-002 (README, full mode only)
Level 3: IMPL-003 (ARCHITECTURE+EXAMPLES), IMPL-004 (HTTP API, optional)
Medium Projects (Example: 7 top-level dirs, 18 total docs):
Step 1: Count docs per top-level dir
├─ dir1: 3 docs, dir2: 4 docs → Group 1 (7 docs)
├─ dir3: 5 docs, dir4: 3 docs → Group 2 (8 docs)
├─ dir5: 2 docs → Group 3 (2 docs, can add more)
Step 2: Create tasks with ≤10 docs constraint
Level 1: IMPL-001 to IMPL-003 (parallel groups)
├─ IMPL-001: Group 1 (dir1 + dir2, 7 docs, shared context)
├─ IMPL-002: Group 2 (dir3 + dir4, 8 docs, shared context)
└─ IMPL-003: Group 3 (remaining dirs, ≤10 docs)
Level 2: IMPL-004 (README, depends on Level 1, full mode only)
Level 3: IMPL-005 (ARCHITECTURE+EXAMPLES), IMPL-006 (HTTP API, optional)
Large Projects (single dir >10 docs):
Step 1: Detect oversized directory
└─ src/modules/: 15 subdirs → 30 docs (exceeds limit)
Step 2: Split by subdirectories
Level 1: IMPL-001 to IMPL-003 (split oversized dir)
├─ IMPL-001: src/modules/ subdirs 1-5 (10 docs)
├─ IMPL-002: src/modules/ subdirs 6-10 (10 docs)
└─ IMPL-003: src/modules/ subdirs 11-15 (10 docs)
```
**Grouping Algorithm**:
1. Count total docs for each top-level directory
2. Try grouping 2 directories (optimization for context sharing)
3. If group exceeds 10 docs, split to 1 dir/task
4. If single dir exceeds 10 docs, split by subdirectories
5. Create parallel Level 1 tasks with ≤10 docs each
**Commands**:
```bash
# 1. Get top-level directories from doc-planning-data.json
bash(cat .workflow/active/WFS-docs-{timestamp}/.process/doc-planning-data.json | jq -r '.top_level_dirs[]')
# 2. Get mode from workflow-session.json
bash(cat .workflow/active/WFS-docs-{timestamp}/workflow-session.json | jq -r '.mode // "full"')
# 3. Check for HTTP API
bash(grep -r "router\.|@Get\|@Post" src/ 2>/dev/null && echo "API_FOUND" || echo "NO_API")
```
**Data Processing**:
1. Count documents for each top-level directory (from folder_analysis):
- Code folders: 2 docs each (API.md + README.md)
- Navigation folders: 1 doc each (README.md only)
2. Apply grouping algorithm with ≤10 docs constraint:
- Try grouping 2 directories, calculate total docs
- If total ≤10 docs: create group
- If total >10 docs: split to 1 dir/group or subdivide
- If single dir >10 docs: split by subdirectories
3. Use **Edit tool** to update `doc-planning-data.json` adding groups field:
```json
"groups": {
"count": 3,
"assignments": [
{"group_id": "001", "directories": ["src/modules", "src/utils"], "doc_count": 5},
{"group_id": "002", "directories": ["lib/core"], "doc_count": 6},
{"group_id": "003", "directories": ["lib/helpers"], "doc_count": 3}
]
}
```
**Task ID Calculation**:
```bash
group_count=$(jq '.groups.count' .workflow/active/WFS-docs-{timestamp}/.process/doc-planning-data.json)
readme_id=$((group_count + 1)) # Next ID after groups
arch_id=$((group_count + 2))
api_id=$((group_count + 3))
```
### Phase 5: Generate Task JSONs
**CLI Strategy**:
| Mode | cli_execute | Placement | CLI MODE | Approval Flag | Agent Role |
|------|-------------|-----------|----------|---------------|------------|
| **Agent** | false | pre_analysis | analysis | (none) | Generate docs in implementation_approach |
| **CLI** | true | implementation_approach | write | --mode write | Execute CLI commands, validate output |
**Command Patterns**:
- Gemini/Qwen: `ccw cli -p "..." --tool gemini --mode analysis --cd dir`
- CLI Mode: `ccw cli -p "..." --tool gemini --mode write --cd dir`
- Codex: `ccw cli -p "..." --tool codex --mode write --cd dir`
**Generation Process**:
1. Read configuration values (tool, cli_execute, mode) from workflow-session.json
2. Read group assignments from doc-planning-data.json
3. Generate Level 1 tasks (IMPL-001 to IMPL-N, one per group)
4. Generate Level 2+ tasks if mode=full (README, ARCHITECTURE, HTTP API)
## Task Templates
### Level 1: Module Trees Group Task (Unified)
**Execution Model**: Each task processes assigned directory group (max 2 directories) using pre-analyzed data from Phase 2.
```json
{
"id": "IMPL-${group_number}",
"title": "Document Module Trees Group ${group_number}",
"status": "pending",
"meta": {
"type": "docs-tree-group",
"agent": "@doc-generator",
"tool": "gemini",
"cli_execute": false,
"group_number": "${group_number}",
"total_groups": "${total_groups}"
},
"context": {
"requirements": [
"Process directories from group ${group_number} in doc-planning-data.json",
"Generate docs to .workflow/docs/${project_name}/ (mirrored structure)",
"Code folders: API.md + README.md; Navigation folders: README.md only",
"Use pre-analyzed data from Phase 2 (no redundant analysis)"
],
"focus_paths": ["${group_dirs_from_json}"],
"precomputed_data": {
"phase2_analysis": "${session_dir}/.process/doc-planning-data.json"
}
},
"flow_control": {
"pre_analysis": [
{
"step": "load_precomputed_data",
"action": "Load Phase 2 analysis and extract group directories",
"commands": [
"bash(cat ${session_dir}/.process/doc-planning-data.json)",
"bash(jq '.groups.assignments[] | select(.group_id == \"${group_number}\") | .directories' ${session_dir}/.process/doc-planning-data.json)"
],
"output_to": "phase2_context",
"note": "Single JSON file contains all Phase 2 analysis results"
}
],
"implementation_approach": [
{
"step": 1,
"title": "Generate documentation for assigned directory group",
"description": "Process directories in Group ${group_number} using pre-analyzed data",
"modification_points": [
"Read group directories from [phase2_context].groups.assignments[${group_number}].directories",
"For each directory: parse folder types from folder_analysis, parse structure from unified_analysis",
"Map source_path to .workflow/docs/${project_name}/{path}",
"Generate API.md for code folders, README.md for all folders",
"Preserve user modifications from [phase2_context].existing_docs.content"
],
"logic_flow": [
"phase2 = parse([phase2_context])",
"dirs = phase2.groups.assignments[${group_number}].directories",
"for dir in dirs:",
" folder_info = find(dir, phase2.folder_analysis)",
" outline = find(dir, phase2.unified_analysis)",
" if folder_info.type == 'code': generate API.md + README.md",
" elif folder_info.type == 'navigation': generate README.md only",
" write to .workflow/docs/${project_name}/{dir}/"
],
"depends_on": [],
"output": "group_module_docs"
}
],
"target_files": [
".workflow/docs/${project_name}/*/API.md",
".workflow/docs/${project_name}/*/README.md"
]
}
}
```
**CLI Execute Mode Note**: When `cli_execute=true`, add Step 2 in `implementation_approach`:
```json
{
"step": 2,
"title": "Batch generate documentation via CLI",
"command": "ccw cli -p 'PURPOSE: Generate module docs\\nTASK: Create documentation\\nMODE: write\\nCONTEXT: @**/* [phase2_context]\\nEXPECTED: API.md and README.md\\nRULES: Mirror structure' --tool gemini --mode write --cd ${dirs_from_group}",
"depends_on": [1],
"output": "generated_docs"
}
```
### Level 2: Project README Task
**Task ID**: `IMPL-${readme_id}` (where `readme_id = group_count + 1`)
**Dependencies**: Depends on all Level 1 tasks completing.
```json
{
"id": "IMPL-${readme_id}",
"title": "Generate Project README",
"status": "pending",
"depends_on": ["IMPL-001", "...", "IMPL-${group_count}"],
"meta": {"type": "docs", "agent": "@doc-generator", "tool": "gemini", "cli_execute": false},
"flow_control": {
"pre_analysis": [
{
"step": "load_existing_readme",
"command": "bash(cat .workflow/docs/${project_name}/README.md 2>/dev/null || echo 'No existing README')",
"output_to": "existing_readme"
},
{
"step": "load_module_docs",
"command": "bash(find .workflow/docs/${project_name} -type f -name '*.md' ! -path '.workflow/docs/${project_name}/README.md' ! -path '.workflow/docs/${project_name}/ARCHITECTURE.md' ! -path '.workflow/docs/${project_name}/EXAMPLES.md' ! -path '.workflow/docs/${project_name}/api/*' | xargs cat)",
"output_to": "all_module_docs"
},
{
"step": "analyze_project",
"command": "bash(ccw cli -p \"PURPOSE: Analyze project structure\\nTASK: Extract overview from modules\\nMODE: analysis\\nCONTEXT: [all_module_docs]\\nEXPECTED: Project outline\" --tool gemini --mode analysis)",
"output_to": "project_outline"
}
],
"implementation_approach": [
{
"step": 1,
"title": "Generate project README",
"description": "Generate project README with navigation links while preserving user modifications",
"modification_points": [
"Parse [project_outline] and [all_module_docs]",
"Generate README structure with navigation links",
"Preserve [existing_readme] user modifications"
],
"logic_flow": ["Parse data", "Generate README with navigation", "Preserve modifications"],
"depends_on": [],
"output": "project_readme"
}
],
"target_files": [".workflow/docs/${project_name}/README.md"]
}
}
```
### Level 3: Architecture & Examples Documentation Task
**Task ID**: `IMPL-${arch_id}` (where `arch_id = group_count + 2`)
**Dependencies**: Depends on Level 2 (Project README).
```json
{
"id": "IMPL-${arch_id}",
"title": "Generate Architecture & Examples Documentation",
"status": "pending",
"depends_on": ["IMPL-${readme_id}"],
"meta": {"type": "docs", "agent": "@doc-generator", "tool": "gemini", "cli_execute": false},
"flow_control": {
"pre_analysis": [
{"step": "load_existing_docs", "command": "bash(cat .workflow/docs/${project_name}/{ARCHITECTURE,EXAMPLES}.md 2>/dev/null || echo 'No existing docs')", "output_to": "existing_arch_examples"},
{"step": "load_all_docs", "command": "bash(cat .workflow/docs/${project_name}/README.md && find .workflow/docs/${project_name} -type f -name '*.md' ! -path '*/README.md' ! -path '*/ARCHITECTURE.md' ! -path '*/EXAMPLES.md' ! -path '*/api/*' | xargs cat)", "output_to": "all_docs"},
{"step": "analyze_architecture", "command": "bash(ccw cli -p \"PURPOSE: Analyze system architecture\\nTASK: Synthesize architectural overview and examples\\nMODE: analysis\\nCONTEXT: [all_docs]\\nEXPECTED: Architecture + Examples outline\" --tool gemini --mode analysis)", "output_to": "arch_examples_outline"}
],
"implementation_approach": [
{
"step": 1,
"title": "Generate architecture and examples documentation",
"modification_points": [
"Parse [arch_examples_outline] and [all_docs]",
"Generate ARCHITECTURE.md (system design, patterns)",
"Generate EXAMPLES.md (code snippets, usage)",
"Preserve [existing_arch_examples] modifications"
],
"depends_on": [],
"output": "arch_examples_docs"
}
],
"target_files": [".workflow/docs/${project_name}/ARCHITECTURE.md", ".workflow/docs/${project_name}/EXAMPLES.md"]
}
}
```
### Level 4: HTTP API Documentation Task (Optional)
**Task ID**: `IMPL-${api_id}` (where `api_id = group_count + 3`)
**Dependencies**: Depends on Level 3.
```json
{
"id": "IMPL-${api_id}",
"title": "Generate HTTP API Documentation",
"status": "pending",
"depends_on": ["IMPL-${arch_id}"],
"meta": {"type": "docs", "agent": "@doc-generator", "tool": "gemini", "cli_execute": false},
"flow_control": {
"pre_analysis": [
{"step": "discover_api", "command": "bash(rg 'router\\.| @(Get|Post)' -g '*.{ts,js}')", "output_to": "endpoint_discovery"},
{"step": "load_existing_api", "command": "bash(cat .workflow/docs/${project_name}/api/README.md 2>/dev/null || echo 'No existing API docs')", "output_to": "existing_api_docs"},
{"step": "analyze_api", "command": "bash(ccw cli -p \"PURPOSE: Document HTTP API\\nTASK: Analyze endpoints\\nMODE: analysis\\nCONTEXT: @src/api/**/* [endpoint_discovery]\\nEXPECTED: API outline\" --tool gemini --mode analysis)", "output_to": "api_outline"}
],
"implementation_approach": [
{
"step": 1,
"title": "Generate HTTP API documentation",
"modification_points": [
"Parse [api_outline] and [endpoint_discovery]",
"Document endpoints, request/response formats",
"Preserve [existing_api_docs] modifications"
],
"depends_on": [],
"output": "api_docs"
}
],
"target_files": [".workflow/docs/${project_name}/api/README.md"]
}
}
```
## Session Structure
**Unified Structure** (single JSON replaces multiple text files):
```
.workflow/active/
└── WFS-docs-{timestamp}/
├── workflow-session.json # Session metadata
├── IMPL_PLAN.md
├── TODO_LIST.md
├── .process/
│ └── doc-planning-data.json # All Phase 2 analysis data (replaces 7+ files)
└── .task/
├── IMPL-001.json # Small: all modules | Large: group 1
├── IMPL-00N.json # (Large only: groups 2-N)
├── IMPL-{N+1}.json # README (full mode)
├── IMPL-{N+2}.json # ARCHITECTURE+EXAMPLES (full mode)
└── IMPL-{N+3}.json # HTTP API (optional)
```
**doc-planning-data.json Structure**:
```json
{
"metadata": {
"generated_at": "2025-11-03T16:41:06+08:00",
"project_name": "Claude_dms3",
"project_root": "/d/Claude_dms3"
},
"folder_analysis": [
{"path": "./src/core", "type": "code", "code_count": 5, "dirs_count": 2},
{"path": "./src/utils", "type": "navigation", "code_count": 0, "dirs_count": 4}
],
"top_level_dirs": ["src/modules", "src/utils", "lib/core"],
"existing_docs": {
"file_list": [".workflow/docs/project/src/core/API.md"],
"content": "... concatenated existing docs ..."
},
"unified_analysis": [
{"module_path": "./src/core", "outline_summary": "Core functionality"}
],
"groups": {
"count": 4,
"assignments": [
{"group_id": "001", "directories": ["src/modules", "src/utils"], "doc_count": 6},
{"group_id": "002", "directories": ["lib/core", "lib/helpers"], "doc_count": 7}
]
},
"statistics": {
"total": 15,
"code": 8,
"navigation": 7,
"top_level": 3
}
}
```
**Workflow Session Structure** (workflow-session.json):
```json
{
"session_id": "WFS-docs-{timestamp}",
"project": "{project_name} documentation",
"status": "planning",
"timestamp": "2024-01-20T14:30:22+08:00",
"path": ".",
"target_path": "/path/to/project",
"project_root": "/path/to/project",
"project_name": "{project_name}",
"mode": "full",
"tool": "gemini",
"cli_execute": false,
"update_mode": "update",
"existing_docs": 5,
"analysis": {
"total": "15",
"code": "8",
"navigation": "7",
"top_level": "3"
}
}
```
## Generated Documentation
**Structure mirrors project source directories under project-specific folder**:
```
.workflow/docs/
└── {project_name}/ # Project-specific root
├── src/ # Mirrors src/ directory
│ ├── modules/
│ │ ├── README.md # Navigation
│ │ ├── auth/
│ │ │ ├── API.md # API signatures
│ │ │ ├── README.md # Module docs
│ │ │ └── middleware/
│ │ │ ├── API.md
│ │ │ └── README.md
│ │ └── api/
│ │ ├── API.md
│ │ └── README.md
│ └── utils/
│ └── README.md
├── lib/ # Mirrors lib/ directory
│ └── core/
│ ├── API.md
│ └── README.md
├── README.md # Project root
├── ARCHITECTURE.md # System design
├── EXAMPLES.md # Usage examples
└── api/ # Optional
└── README.md # HTTP API reference
```
## Execution Commands
```bash
# Execute entire workflow (auto-discovers active session)
/workflow:execute
# Or specify session
/workflow:execute --resume-session="WFS-docs-yyyymmdd-hhmmss"
# Individual task execution
/task:execute IMPL-001
```
## Template Reference
**Available Templates** (`~/.claude/workflows/cli-templates/prompts/documentation/`):
- `api.txt`: Code API (Part A) + HTTP API (Part B)
- `module-readme.txt`: Module purpose, usage, dependencies
- `folder-navigation.txt`: Navigation README for folders with subdirectories
- `project-readme.txt`: Project overview, getting started, navigation
- `project-architecture.txt`: System structure, module map, design patterns
- `project-examples.txt`: End-to-end usage examples
## Execution Mode Summary
| Mode | CLI Placement | CLI MODE | Approval Flag | Agent Role |
|------|---------------|----------|---------------|------------|
| **Agent (default)** | pre_analysis | analysis | (none) | Generates documentation content |
| **CLI (--cli-execute)** | implementation_approach | write | --mode write | Executes CLI commands, validates output |
**Execution Flow**:
- **Phase 2**: Unified analysis once, results in `.process/`
- **Phase 4**: Dynamic grouping (max 2 dirs per group)
- **Level 1**: Parallel processing for module tree groups
- **Level 2+**: Sequential execution for project-level docs
## Related Commands
- `/workflow:execute` - Execute documentation tasks
- `/workflow:status` - View task progress
- `/workflow:session:complete` - Mark session complete

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@@ -1,182 +0,0 @@
---
name: load-skill-memory
description: Activate SKILL package (auto-detect from paths/keywords or manual) and intelligently load documentation based on task intent keywords
argument-hint: "[skill_name] \"task intent description\""
allowed-tools: Bash(*), Read(*), Skill(*)
---
# Memory Load SKILL Command (/memory:load-skill-memory)
## 1. Overview
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.
**Core Philosophy**:
- **Flexible Activation**: Auto-detect skill from task description/paths, or user explicitly specifies
- **Intent-Driven Loading**: System analyzes task intent to determine documentation scope
- **Intelligent Selection**: Automatically chooses appropriate documentation level and modules
- **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 or path mentions (system extracts skill name from file paths for intelligent triggering). Use this command only when manual activation is needed.
## 2. Parameters
- `[skill_name]` (Optional): Name of SKILL package to activate
- If omitted: System auto-detects from task description or file paths
- If specified: Direct activation of named SKILL package
- Example: `my_project`, `api_service`
- Must match directory name under `.claude/skills/`
- `"task intent description"` (Required): Description of what you want to do
- Used for both: auto-detection (if skill_name omitted) and documentation scope selection
- **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"
- **With paths**: "修改D:\projects\my_project\src\auth.py的认证逻辑" (auto-extracts `my_project`)
## 3. Execution Flow
### Step 1: Determine SKILL Name (if not provided)
**Auto-Detection Strategy** (when skill_name parameter is omitted):
1. **Path Extraction**: Scan task description for file paths
- Extract potential project names from path segments
- Example: `"修改D:\projects\my_project\src\auth.py"` → extracts `my_project`
2. **Keyword Matching**: Match task keywords against SKILL descriptions
- Search for project-specific terms, domain keywords
3. **Validation**: Check if extracted name matches `.claude/skills/{skill_name}/`
**Result**: Either uses provided skill_name or auto-detected name for activation
### Step 2: Activate SKILL and Analyze Intent
**Activate SKILL Package**:
```javascript
Skill(command: "${skill_name}") // Uses provided or auto-detected name
```
**What Happens After Activation**:
1. If SKILL exists in memory: System reads `.claude/skills/${skill_name}/SKILL.md`
2. If SKILL not found in memory: Error - SKILL package doesn't exist
3. SKILL description triggers are loaded into memory
4. Progressive loading mechanism becomes available
5. Documentation structure is now accessible
**Intent Analysis**:
Based on task intent description, system determines:
- **Action type**: analyzing, modifying, learning
- **Scope**: specific module, architecture overview, complete system
- **Depth**: quick reference, detailed API, full documentation
### Step 3: Intelligent Documentation Loading
**Loading Strategy**:
The system automatically selects documentation based on intent keywords:
1. **Quick Understanding** ("了解", "快速理解", "什么是"):
- Load: Level 0 (README.md only, ~2K tokens)
- Use case: Quick overview of capabilities
2. **Specific Module Analysis** ("分析XXX模块", "理解XXX实现"):
- Load: Module-specific README.md + API.md (~5K tokens)
- Use case: Deep dive into specific component
3. **Architecture Review** ("架构", "设计模式", "整体结构"):
- Load: README.md + ARCHITECTURE.md (~10K tokens)
- Use case: System design understanding
4. **Implementation/Modification** ("修改", "增强", "实现"):
- Load: Relevant module docs + EXAMPLES.md (~15K tokens)
- Use case: Code modification with examples
5. **Comprehensive Learning** ("学习", "完整了解", "深入理解"):
- Load: Level 3 (All documentation, ~40K tokens)
- Use case: Complete system mastery
**Documentation Loaded into Memory**:
After loading, the selected documentation content is available in conversation memory for subsequent operations.
## 4. Usage Examples
### Example 1: Manual Specification
**User Command**:
```bash
/memory:load-skill-memory my_project "修改认证模块增加OAuth支持"
```
**Execution**:
```javascript
// Step 1: Use provided skill_name
skill_name = "my_project" // Directly from parameter
// Step 2: Activate SKILL
Skill(command: "my_project")
// Step 3: Intent Analysis
Keywords: ["修改", "认证模块", "增加", "OAuth"]
Action: modifying (implementation)
Scope: auth module + examples
// Load documentation based on intent
Read(.workflow/docs/my_project/auth/README.md)
Read(.workflow/docs/my_project/auth/API.md)
Read(.workflow/docs/my_project/EXAMPLES.md)
```
### Example 2: Auto-Detection from Path
**User Command**:
```bash
/memory:load-skill-memory "修改D:\projects\my_project\src\services\api.py的接口逻辑"
```
**Execution**:
```javascript
// Step 1: Auto-detect skill_name from path
Path detected: "D:\projects\my_project\src\services\api.py"
Extracted: "my_project"
Validated: .claude/skills/my_project/ exists
skill_name = "my_project"
// Step 2: Activate SKILL
Skill(command: "my_project")
// Step 3: Intent Analysis
Keywords: ["修改", "services", "接口逻辑"]
Action: modifying (implementation)
Scope: services module + examples
// Load documentation based on intent
Read(.workflow/docs/my_project/services/README.md)
Read(.workflow/docs/my_project/services/API.md)
Read(.workflow/docs/my_project/EXAMPLES.md)
```
## 5. Intent Keyword Mapping
**Quick Reference**:
- **Triggers**: "了解", "快速", "什么是", "简介"
- **Loads**: README.md only (~2K)
**Module-Specific**:
- **Triggers**: "XXX模块", "XXX组件", "分析XXX"
- **Loads**: Module README + API (~5K)
**Architecture**:
- **Triggers**: "架构", "设计", "整体结构", "系统设计"
- **Loads**: README + ARCHITECTURE (~10K)
**Implementation**:
- **Triggers**: "修改", "增强", "实现", "开发", "集成"
- **Loads**: Relevant module + EXAMPLES (~15K)
**Comprehensive**:
- **Triggers**: "完整", "深入", "全面", "学习整个"
- **Loads**: All documentation (~40K)

View File

@@ -1,525 +0,0 @@
---
name: skill-memory
description: 4-phase autonomous orchestrator: check docs → /memory:docs planning → /workflow:execute → generate SKILL.md with progressive loading index (skips phases 2-3 if docs exist)
argument-hint: "[path] [--tool <gemini|qwen|codex>] [--regenerate] [--mode <full|partial>] [--cli-execute]"
allowed-tools: SlashCommand(*), TodoWrite(*), Bash(*), Read(*), Write(*)
---
# Memory SKILL Package Generator
## Orchestrator Role
**Pure Orchestrator**: Execute documentation generation workflow, then generate SKILL.md index. Does NOT create task JSON files.
**Auto-Continue Workflow**: This command runs **fully autonomously** once triggered. Each phase completes and automatically triggers the next phase without user interaction.
**Execution Paths**:
- **Full Path**: All 4 phases (no existing docs OR `--regenerate` specified)
- **Skip Path**: Phase 1 → Phase 4 (existing docs found AND no `--regenerate` flag)
- **Phase 4 Always Executes**: SKILL.md index is never skipped, always generated or updated
## Core Rules
1. **Start Immediately**: First action is TodoWrite initialization, second action is Phase 1 execution
2. **No Task JSON**: This command does not create task JSON files - delegates to /memory:docs
3. **Parse Every Output**: Extract required data from each command output (session_id, task_count, file paths)
4. **Auto-Continue**: After completing each phase, update TodoWrite and immediately execute next phase
5. **Track Progress**: Update TodoWrite after EVERY phase completion before starting next phase
6. **Direct Generation**: Phase 4 directly generates SKILL.md using Write tool
7. **No Manual Steps**: User should never be prompted for decisions between phases
---
## 4-Phase Execution
### Phase 1: Prepare Arguments
**Goal**: Parse command arguments and check existing documentation
**Step 1: Get Target Path and Project Name**
```bash
# Get current directory (or use provided path)
bash(pwd)
# Get project name from directory
bash(basename "$(pwd)")
# Get project root
bash(git rev-parse --show-toplevel 2>/dev/null || pwd)
```
**Output**:
- `target_path`: `/d/my_project`
- `project_name`: `my_project`
- `project_root`: `/d/my_project`
**Step 2: Set Default Parameters**
```bash
# Default values (use these unless user specifies otherwise):
# - tool: "gemini"
# - mode: "full"
# - regenerate: false (no --regenerate flag)
# - cli_execute: false (no --cli-execute flag)
```
**Step 3: Check Existing Documentation**
```bash
# Check if docs directory exists
bash(test -d .workflow/docs/my_project && echo "exists" || echo "not_exists")
# Count existing documentation files
bash(find .workflow/docs/my_project -name "*.md" 2>/dev/null | wc -l || echo 0)
```
**Output**:
- `docs_exists`: `exists` or `not_exists`
- `existing_docs`: `5` (or `0` if no docs)
**Step 4: Determine Execution Path**
**Decision Logic**:
```javascript
if (existing_docs > 0 && !regenerate_flag) {
// Documentation exists and no regenerate flag
SKIP_DOCS_GENERATION = true
message = "Documentation already exists, skipping Phase 2 and Phase 3. Use --regenerate to force regeneration."
} else if (regenerate_flag) {
// Force regeneration: delete existing docs
bash(rm -rf .workflow/docs/my_project 2>/dev/null || true)
SKIP_DOCS_GENERATION = false
message = "Regenerating documentation from scratch."
} else {
// No existing docs
SKIP_DOCS_GENERATION = false
message = "No existing documentation found, generating new documentation."
}
```
**Summary Variables**:
- `PROJECT_NAME`: `my_project`
- `TARGET_PATH`: `/d/my_project`
- `DOCS_PATH`: `.workflow/docs/my_project`
- `TOOL`: `gemini` (default) or user-specified
- `MODE`: `full` (default) or user-specified
- `CLI_EXECUTE`: `false` (default) or `true` if --cli-execute flag
- `REGENERATE`: `false` (default) or `true` if --regenerate flag
- `EXISTING_DOCS`: Count of existing documentation files
- `SKIP_DOCS_GENERATION`: `true` if skipping Phase 2/3, `false` otherwise
**Completion & TodoWrite**:
- If `SKIP_DOCS_GENERATION = true`: Mark phase 1 completed, phase 2&3 completed (skipped), phase 4 in_progress
- If `SKIP_DOCS_GENERATION = false`: Mark phase 1 completed, phase 2 in_progress
**Next Action**:
- If skipping: Display skip message → Jump to Phase 4 (SKILL.md generation)
- If not skipping: Display preparation results → Continue to Phase 2 (documentation planning)
---
### Phase 2: Call /memory:docs
**Skip Condition**: This phase is **skipped if SKIP_DOCS_GENERATION = true** (documentation already exists without --regenerate flag)
**Goal**: Trigger documentation generation workflow
**Command**:
```bash
SlashCommand(command="/memory:docs [targetPath] --tool [tool] --mode [mode] [--cli-execute]")
```
**Example**:
```bash
/memory:docs /d/my_app --tool gemini --mode full
/memory:docs /d/my_app --tool gemini --mode full --cli-execute
```
**Note**: The `--regenerate` flag is handled in Phase 1 by deleting existing documentation. This command always calls `/memory:docs` without the regenerate flag, relying on docs.md's built-in update detection.
**Parse Output**:
- Extract session ID: `WFS-docs-[timestamp]` (store as `docsSessionId`)
- Extract task count (store as `taskCount`)
**Completion Criteria**:
- `/memory:docs` command executed successfully
- Session ID extracted and stored
- Task count retrieved
- Task files created in `.workflow/[docsSessionId]/.task/`
- workflow-session.json exists
**TodoWrite**: Mark phase 2 completed, phase 3 in_progress
**Next Action**: Display docs planning results (session ID, task count) → Auto-continue to Phase 3
---
### Phase 3: Execute Documentation Generation
**Skip Condition**: This phase is **skipped if SKIP_DOCS_GENERATION = true** (documentation already exists without --regenerate flag)
**Goal**: Execute documentation generation tasks
**Command**:
```bash
SlashCommand(command="/workflow:execute")
```
**Note**: `/workflow:execute` automatically discovers active session from Phase 2
**Completion Criteria**:
- `/workflow:execute` command executed successfully
- Documentation files generated in `.workflow/docs/[projectName]/`
- All tasks marked as completed in session
- At minimum: module documentation files exist (API.md and/or README.md)
- For full mode: Project README, ARCHITECTURE, EXAMPLES files generated
**TodoWrite**: Mark phase 3 completed, phase 4 in_progress
**Next Action**: Display execution results (file count, module count) → Auto-continue to Phase 4
---
### Phase 4: Generate SKILL.md Index
**Note**: This phase is **NEVER skipped** - it always executes to generate or update the SKILL index.
**Step 1: Read Key Files** (Use Read tool)
- `.workflow/docs/{project_name}/README.md` (required)
- `.workflow/docs/{project_name}/ARCHITECTURE.md` (optional)
**Step 2: Discover Structure**
```bash
bash(find .workflow/docs/{project_name} -name "*.md" | sed 's|.workflow/docs/{project_name}/||' | awk -F'/' '{if(NF>=2) print $1"/"$2}' | sort -u)
```
**Step 3: Generate Intelligent Description**
Extract from README + structure: Function (capabilities), Modules (names), Keywords (API/CLI/auth/etc.)
**Format**: `{Project} {core capabilities} (located at {project_path}). Load this SKILL when analyzing, modifying, or learning about {domain_description} or files under this path, especially when no relevant context exists in memory.`
**Key Elements**:
- **Path Reference**: Use `TARGET_PATH` from Phase 1 for precise location identification
- **Domain Description**: Extract human-readable domain/feature area from README (e.g., "workflow management", "thermal modeling")
- **Trigger Optimization**: Include project path, emphasize "especially when no relevant context exists in memory"
- **Action Coverage**: analyzing (分析), modifying (修改), learning (了解)
**Example**: "Workflow orchestration system with CLI tools and documentation generation (located at /d/Claude_dms3). Load this SKILL when analyzing, modifying, or learning about workflow management or files under this path, especially when no relevant context exists in memory."
**Step 4: Write SKILL.md** (Use Write tool)
```bash
bash(mkdir -p .claude/skills/{project_name})
```
`.claude/skills/{project_name}/SKILL.md`:
```yaml
---
name: {project_name}
description: {intelligent description from Step 3}
version: 1.0.0
---
# {Project Name} SKILL Package
## Documentation: `../../../.workflow/docs/{project_name}/`
## Progressive Loading
### Level 0: Quick Start (~2K)
- [README](../../../.workflow/docs/{project_name}/README.md)
### Level 1: Core Modules (~8K)
{Module READMEs}
### Level 2: Complete (~25K)
All modules + [Architecture](../../../.workflow/docs/{project_name}/ARCHITECTURE.md)
### Level 3: Deep Dive (~40K)
Everything + [Examples](../../../.workflow/docs/{project_name}/EXAMPLES.md)
```
**Completion Criteria**:
- SKILL.md file created at `.claude/skills/{project_name}/SKILL.md`
- Intelligent description generated from documentation
- Progressive loading levels (0-3) properly structured
- Module index includes all documented modules
- All file references use relative paths
**TodoWrite**: Mark phase 4 completed
**Final Action**: Report completion summary to user
**Return to User**:
```
SKILL Package Generation Complete
Project: {project_name}
Documentation: .workflow/docs/{project_name}/ ({doc_count} files)
SKILL Index: .claude/skills/{project_name}/SKILL.md
Generated:
- {task_count} documentation tasks completed
- SKILL.md with progressive loading (4 levels)
- Module index with {module_count} modules
Usage:
- Load Level 0: Quick project overview (~2K tokens)
- Load Level 1: Core modules (~8K tokens)
- Load Level 2: Complete docs (~25K tokens)
- Load Level 3: Everything (~40K tokens)
```
---
## Implementation Details
### Critical Rules
1. **No User Prompts Between Phases**: Never ask user questions or wait for input between phases
2. **Immediate Phase Transition**: After TodoWrite update, immediately execute next phase command
3. **Status-Driven Execution**: Check TodoList status after each phase:
- If next task is "pending" → Mark it "in_progress" and execute
- If all tasks are "completed" → Report final summary
4. **Phase Completion Pattern**:
```
Phase N completes → Update TodoWrite (N=completed, N+1=in_progress) → Execute Phase N+1
```
### TodoWrite Patterns
#### Initialization (Before Phase 1)
**FIRST ACTION**: Create TodoList with all 4 phases
```javascript
TodoWrite({todos: [
{"content": "Parse arguments and prepare", "status": "in_progress", "activeForm": "Parsing arguments"},
{"content": "Call /memory:docs to plan documentation", "status": "pending", "activeForm": "Calling /memory:docs"},
{"content": "Execute documentation generation", "status": "pending", "activeForm": "Executing documentation"},
{"content": "Generate SKILL.md index", "status": "pending", "activeForm": "Generating SKILL.md"}
]})
```
**SECOND ACTION**: Execute Phase 1 immediately
#### Full Path (SKIP_DOCS_GENERATION = false)
**After Phase 1**:
```javascript
TodoWrite({todos: [
{"content": "Parse arguments and prepare", "status": "completed", "activeForm": "Parsing arguments"},
{"content": "Call /memory:docs to plan documentation", "status": "in_progress", "activeForm": "Calling /memory:docs"},
{"content": "Execute documentation generation", "status": "pending", "activeForm": "Executing documentation"},
{"content": "Generate SKILL.md index", "status": "pending", "activeForm": "Generating SKILL.md"}
]})
// Auto-continue to Phase 2
```
**After Phase 2**:
```javascript
TodoWrite({todos: [
{"content": "Parse arguments and prepare", "status": "completed", "activeForm": "Parsing arguments"},
{"content": "Call /memory:docs to plan documentation", "status": "completed", "activeForm": "Calling /memory:docs"},
{"content": "Execute documentation generation", "status": "in_progress", "activeForm": "Executing documentation"},
{"content": "Generate SKILL.md index", "status": "pending", "activeForm": "Generating SKILL.md"}
]})
// Auto-continue to Phase 3
```
**After Phase 3**:
```javascript
TodoWrite({todos: [
{"content": "Parse arguments and prepare", "status": "completed", "activeForm": "Parsing arguments"},
{"content": "Call /memory:docs to plan documentation", "status": "completed", "activeForm": "Calling /memory:docs"},
{"content": "Execute documentation generation", "status": "completed", "activeForm": "Executing documentation"},
{"content": "Generate SKILL.md index", "status": "in_progress", "activeForm": "Generating SKILL.md"}
]})
// Auto-continue to Phase 4
```
**After Phase 4**:
```javascript
TodoWrite({todos: [
{"content": "Parse arguments and prepare", "status": "completed", "activeForm": "Parsing arguments"},
{"content": "Call /memory:docs to plan documentation", "status": "completed", "activeForm": "Calling /memory:docs"},
{"content": "Execute documentation generation", "status": "completed", "activeForm": "Executing documentation"},
{"content": "Generate SKILL.md index", "status": "completed", "activeForm": "Generating SKILL.md"}
]})
// Report completion summary to user
```
#### Skip Path (SKIP_DOCS_GENERATION = true)
**After Phase 1** (detects existing docs, skips Phase 2 & 3):
```javascript
TodoWrite({todos: [
{"content": "Parse arguments and prepare", "status": "completed", "activeForm": "Parsing arguments"},
{"content": "Call /memory:docs to plan documentation", "status": "completed", "activeForm": "Calling /memory:docs"},
{"content": "Execute documentation generation", "status": "completed", "activeForm": "Executing documentation"},
{"content": "Generate SKILL.md index", "status": "in_progress", "activeForm": "Generating SKILL.md"}
]})
// Display skip message: "Documentation already exists, skipping Phase 2 and Phase 3. Use --regenerate to force regeneration."
// Jump directly to Phase 4
```
**After Phase 4**:
```javascript
TodoWrite({todos: [
{"content": "Parse arguments and prepare", "status": "completed", "activeForm": "Parsing arguments"},
{"content": "Call /memory:docs to plan documentation", "status": "completed", "activeForm": "Calling /memory:docs"},
{"content": "Execute documentation generation", "status": "completed", "activeForm": "Executing documentation"},
{"content": "Generate SKILL.md index", "status": "completed", "activeForm": "Generating SKILL.md"}
]})
// Report completion summary to user
```
### Execution Flow Diagrams
#### Full Path Flow
```
User triggers command
[TodoWrite] Initialize 4 phases (Phase 1 = in_progress)
[Execute] Phase 1: Parse arguments
[TodoWrite] Phase 1 = completed, Phase 2 = in_progress
[Execute] Phase 2: Call /memory:docs
[TodoWrite] Phase 2 = completed, Phase 3 = in_progress
[Execute] Phase 3: Call /workflow:execute
[TodoWrite] Phase 3 = completed, Phase 4 = in_progress
[Execute] Phase 4: Generate SKILL.md
[TodoWrite] Phase 4 = completed
[Report] Display completion summary
```
#### Skip Path Flow
```
User triggers command
[TodoWrite] Initialize 4 phases (Phase 1 = in_progress)
[Execute] Phase 1: Parse arguments, detect existing docs
[TodoWrite] Phase 1 = completed, Phase 2&3 = completed (skipped), Phase 4 = in_progress
[Display] Skip message: "Documentation already exists, skipping Phase 2 and Phase 3"
[Execute] Phase 4: Generate SKILL.md (always runs)
[TodoWrite] Phase 4 = completed
[Report] Display completion summary
```
### Error Handling
- If any phase fails, mark it as "in_progress" (not completed)
- Report error details to user
- Do NOT auto-continue to next phase on failure
---
## Parameters
```bash
/memory:skill-memory [path] [--tool <gemini|qwen|codex>] [--regenerate] [--mode <full|partial>] [--cli-execute]
```
- **path**: Target directory (default: current directory)
- **--tool**: CLI tool for documentation (default: gemini)
- `gemini`: Comprehensive documentation
- `qwen`: Architecture analysis
- `codex`: Implementation validation
- **--regenerate**: Force regenerate all documentation
- When enabled: Deletes existing `.workflow/docs/{project_name}/` before regeneration
- Ensures fresh documentation from source code
- **--mode**: Documentation mode (default: full)
- `full`: Complete docs (modules + README + ARCHITECTURE + EXAMPLES)
- `partial`: Module docs only
- **--cli-execute**: Enable CLI-based documentation generation (optional)
- When enabled: CLI generates docs directly in implementation_approach
- When disabled (default): Agent generates documentation content
---
## Examples
### Example 1: Generate SKILL Package (Default)
```bash
/memory:skill-memory
```
**Workflow**:
1. Phase 1: Detects current directory, checks existing docs
2. Phase 2: Calls `/memory:docs . --tool gemini --mode full` (Agent Mode)
3. Phase 3: Executes documentation generation via `/workflow:execute`
4. Phase 4: Generates SKILL.md at `.claude/skills/{project_name}/SKILL.md`
### Example 2: Regenerate with Qwen
```bash
/memory:skill-memory /d/my_app --tool qwen --regenerate
```
**Workflow**:
1. Phase 1: Parses target path, detects regenerate flag, deletes existing docs
2. Phase 2: Calls `/memory:docs /d/my_app --tool qwen --mode full`
3. Phase 3: Executes documentation regeneration
4. Phase 4: Generates updated SKILL.md
### Example 3: Partial Mode (Modules Only)
```bash
/memory:skill-memory --mode partial
```
**Workflow**:
1. Phase 1: Detects partial mode
2. Phase 2: Calls `/memory:docs . --tool gemini --mode partial` (Agent Mode)
3. Phase 3: Executes module documentation only
4. Phase 4: Generates SKILL.md with module-only index
### Example 4: CLI Execute Mode
```bash
/memory:skill-memory --cli-execute
```
**Workflow**:
1. Phase 1: Detects CLI execute mode
2. Phase 2: Calls `/memory:docs . --tool gemini --mode full --cli-execute` (CLI Mode)
3. Phase 3: Executes CLI-based documentation generation
4. Phase 4: Generates SKILL.md at `.claude/skills/{project_name}/SKILL.md`
### Example 5: Skip Path (Existing Docs)
```bash
/memory:skill-memory
```
**Scenario**: Documentation already exists in `.workflow/docs/{project_name}/`
**Workflow**:
1. Phase 1: Detects existing docs (5 files), sets SKIP_DOCS_GENERATION = true
2. Display: "Documentation already exists, skipping Phase 2 and Phase 3. Use --regenerate to force regeneration."
3. Phase 4: Generates or updates SKILL.md index only (~5-10x faster)
---
## Architecture
```
skill-memory (orchestrator)
├─ Phase 1: Prepare (bash commands, skip decision)
├─ Phase 2: /memory:docs (task planning, skippable)
├─ Phase 3: /workflow:execute (task execution, skippable)
└─ Phase 4: Write SKILL.md (direct file generation, always runs)
No task JSON created by this command
All documentation tasks managed by /memory:docs
Smart skip logic: 5-10x faster when docs exist
```

View File

@@ -1,773 +0,0 @@
---
name: swagger-docs
description: Generate complete Swagger/OpenAPI documentation following RESTful standards with global security, API details, error codes, and validation tests
argument-hint: "[path] [--tool <gemini|qwen|codex>] [--format <yaml|json>] [--version <v3.0|v3.1>] [--lang <zh|en>]"
---
# Swagger API Documentation Workflow (/memory:swagger-docs)
## Overview
Professional Swagger/OpenAPI documentation generator that strictly follows RESTful API design standards to produce enterprise-grade API documentation.
**Core Features**:
- **RESTful Standards**: Strict adherence to REST architecture and HTTP semantics
- **Global Security**: Unified Authorization Token validation mechanism
- **Complete API Docs**: Descriptions, methods, URLs, parameters for each endpoint
- **Organized Structure**: Clear directory hierarchy by business domain
- **Detailed Fields**: Type, required, example, description for each field
- **Error Code Standards**: Unified error response format and code definitions
- **Validation Tests**: Boundary conditions and exception handling tests
**Output Structure** (--lang zh):
```
.workflow/docs/{project_name}/api/
├── swagger.yaml # Main OpenAPI spec file
├── 概述/
│ ├── README.md # API overview
│ ├── 认证说明.md # Authentication guide
│ ├── 错误码规范.md # Error code definitions
│ └── 版本历史.md # Version history
├── 用户模块/ # Grouped by business domain
│ ├── 用户认证.md
│ ├── 用户管理.md
│ └── 权限控制.md
├── 业务模块/
│ └── ...
└── 测试报告/
├── 接口测试.md # API test results
└── 边界测试.md # Boundary condition tests
```
**Output Structure** (--lang en):
```
.workflow/docs/{project_name}/api/
├── swagger.yaml # Main OpenAPI spec file
├── overview/
│ ├── README.md # API overview
│ ├── authentication.md # Authentication guide
│ ├── error-codes.md # Error code definitions
│ └── changelog.md # Version history
├── users/ # Grouped by business domain
│ ├── authentication.md
│ ├── management.md
│ └── permissions.md
├── orders/
│ └── ...
└── test-reports/
├── api-tests.md # API test results
└── boundary-tests.md # Boundary condition tests
```
## Parameters
```bash
/memory:swagger-docs [path] [--tool <gemini|qwen|codex>] [--format <yaml|json>] [--version <v3.0|v3.1>] [--lang <zh|en>]
```
- **path**: API source code directory (default: current directory)
- **--tool**: CLI tool selection (default: gemini)
- `gemini`: Comprehensive analysis, pattern recognition
- `qwen`: Architecture analysis, system design
- `codex`: Implementation validation, code quality
- **--format**: OpenAPI spec format (default: yaml)
- `yaml`: YAML format (recommended, better readability)
- `json`: JSON format
- **--version**: OpenAPI version (default: v3.0)
- `v3.0`: OpenAPI 3.0.x
- `v3.1`: OpenAPI 3.1.0 (supports JSON Schema 2020-12)
- **--lang**: Documentation language (default: zh)
- `zh`: Chinese documentation with Chinese directory names
- `en`: English documentation with English directory names
## Planning Workflow
### Phase 1: Initialize Session
```bash
# Get project info
bash(pwd && basename "$(pwd)" && git rev-parse --show-toplevel 2>/dev/null || pwd && date +%Y%m%d-%H%M%S)
```
```javascript
// Create swagger-docs session
SlashCommand(command="/workflow:session:start --type swagger-docs --new \"{project_name}-swagger-{timestamp}\"")
// Parse output to get sessionId
```
```bash
# Update workflow-session.json
bash(jq '. + {"target_path":"{target_path}","project_root":"{project_root}","project_name":"{project_name}","format":"yaml","openapi_version":"3.0.3","lang":"{lang}","tool":"gemini"}' .workflow/active/{sessionId}/workflow-session.json > tmp.json && mv tmp.json .workflow/active/{sessionId}/workflow-session.json)
```
### Phase 2: Scan API Endpoints
**Discovery Patterns**: Auto-detect framework signatures and API definition styles.
**Supported Frameworks**:
| Framework | Detection Pattern | Example |
|-----------|-------------------|---------|
| Express.js | `router.get/post/put/delete` | `router.get('/users/:id')` |
| Fastify | `fastify.route`, `@Route` | `fastify.get('/api/users')` |
| NestJS | `@Controller`, `@Get/@Post` | `@Get('users/:id')` |
| Koa | `router.get`, `ctx.body` | `router.get('/users')` |
| Hono | `app.get/post`, `c.json` | `app.get('/users/:id')` |
| FastAPI | `@app.get`, `@router.post` | `@app.get("/users/{id}")` |
| Flask | `@app.route`, `@bp.route` | `@app.route('/users')` |
| Spring | `@GetMapping`, `@PostMapping` | `@GetMapping("/users/{id}")` |
| Go Gin | `r.GET`, `r.POST` | `r.GET("/users/:id")` |
| Go Chi | `r.Get`, `r.Post` | `r.Get("/users/{id}")` |
**Commands**:
```bash
# 1. Detect API framework type
bash(
if rg -q "@Controller|@Get|@Post|@Put|@Delete" --type ts 2>/dev/null; then echo "NESTJS";
elif rg -q "router\.(get|post|put|delete|patch)" --type ts --type js 2>/dev/null; then echo "EXPRESS";
elif rg -q "fastify\.(get|post|route)" --type ts --type js 2>/dev/null; then echo "FASTIFY";
elif rg -q "@app\.(get|post|put|delete)" --type py 2>/dev/null; then echo "FASTAPI";
elif rg -q "@GetMapping|@PostMapping|@RequestMapping" --type java 2>/dev/null; then echo "SPRING";
elif rg -q 'r\.(GET|POST|PUT|DELETE)' --type go 2>/dev/null; then echo "GO_GIN";
else echo "UNKNOWN"; fi
)
# 2. Scan all API endpoint definitions
bash(rg -n "(router|app|fastify)\.(get|post|put|delete|patch)|@(Get|Post|Put|Delete|Patch|Controller|RequestMapping)" --type ts --type js --type py --type java --type go -g '!*.test.*' -g '!*.spec.*' -g '!node_modules/**' 2>/dev/null | head -200)
# 3. Extract route paths
bash(rg -o "['\"](/api)?/[a-zA-Z0-9/:_-]+['\"]" --type ts --type js --type py -g '!*.test.*' 2>/dev/null | sort -u | head -100)
# 4. Detect existing OpenAPI/Swagger files
bash(find . -type f \( -name "swagger.yaml" -o -name "swagger.json" -o -name "openapi.yaml" -o -name "openapi.json" \) ! -path "*/node_modules/*" 2>/dev/null)
# 5. Extract DTO/Schema definitions
bash(rg -n "export (interface|type|class).*Dto|@ApiProperty|class.*Schema" --type ts -g '!*.test.*' 2>/dev/null | head -100)
```
**Data Processing**: Parse outputs, use **Write tool** to create `${session_dir}/.process/swagger-planning-data.json`:
```json
{
"metadata": {
"generated_at": "2025-01-01T12:00:00+08:00",
"project_name": "project_name",
"project_root": "/path/to/project",
"openapi_version": "3.0.3",
"format": "yaml",
"lang": "zh"
},
"framework": {
"type": "NESTJS",
"detected_patterns": ["@Controller", "@Get", "@Post"],
"base_path": "/api/v1"
},
"endpoints": [
{
"file": "src/modules/users/users.controller.ts",
"line": 25,
"method": "GET",
"path": "/api/v1/users/:id",
"handler": "getUser",
"controller": "UsersController"
}
],
"existing_specs": {
"found": false,
"files": []
},
"dto_schemas": [
{
"name": "CreateUserDto",
"file": "src/modules/users/dto/create-user.dto.ts",
"properties": ["email", "password", "name"]
}
],
"statistics": {
"total_endpoints": 45,
"by_method": {"GET": 20, "POST": 15, "PUT": 5, "DELETE": 5},
"by_module": {"users": 12, "auth": 8, "orders": 15, "products": 10}
}
}
```
### Phase 3: Analyze API Structure
**Commands**:
```bash
# 1. Analyze controller/route file structure
bash(cat ${session_dir}/.process/swagger-planning-data.json | jq -r '.endpoints[].file' | sort -u | head -20)
# 2. Extract request/response types
bash(for f in $(jq -r '.dto_schemas[].file' ${session_dir}/.process/swagger-planning-data.json | head -20); do echo "=== $f ===" && cat "$f" 2>/dev/null; done)
# 3. Analyze authentication middleware
bash(rg -n "auth|guard|middleware|jwt|bearer|token" -i --type ts --type js -g '!*.test.*' -g '!node_modules/**' 2>/dev/null | head -50)
# 4. Detect error handling patterns
bash(rg -n "HttpException|BadRequest|Unauthorized|Forbidden|NotFound|throw new" --type ts --type js -g '!*.test.*' 2>/dev/null | head -50)
```
**Deep Analysis via Gemini CLI**:
```bash
ccw cli -p "
PURPOSE: Analyze API structure and generate OpenAPI specification outline for comprehensive documentation
TASK:
• Parse all API endpoints and identify business module boundaries
• Extract request parameters, request bodies, and response formats
• Identify authentication mechanisms and security requirements
• Discover error handling patterns and error codes
• Map endpoints to logical module groups
MODE: analysis
CONTEXT: @src/**/*.controller.ts @src/**/*.routes.ts @src/**/*.dto.ts @src/**/middleware/**/*
EXPECTED: JSON format API structure analysis report with modules, endpoints, security schemes, and error codes
CONSTRAINTS: Strict RESTful standards | Identify all public endpoints | Document output language: {lang}
" --tool gemini --mode analysis --rule analysis-code-patterns --cd {project_root}
```
**Update swagger-planning-data.json** with analysis results:
```json
{
"api_structure": {
"modules": [
{
"name": "Users",
"name_zh": "用户模块",
"base_path": "/api/v1/users",
"endpoints": [
{
"path": "/api/v1/users",
"method": "GET",
"operation_id": "listUsers",
"summary": "List all users",
"summary_zh": "获取用户列表",
"description": "Paginated list of system users with filtering by status and role",
"description_zh": "分页获取系统用户列表,支持按状态、角色筛选",
"tags": ["User Management"],
"tags_zh": ["用户管理"],
"security": ["bearerAuth"],
"parameters": {
"query": ["page", "limit", "status", "role"]
},
"responses": {
"200": "UserListResponse",
"401": "UnauthorizedError",
"403": "ForbiddenError"
}
}
]
}
],
"security_schemes": {
"bearerAuth": {
"type": "http",
"scheme": "bearer",
"bearerFormat": "JWT",
"description": "JWT Token authentication. Add Authorization: Bearer <token> to request header"
}
},
"error_codes": [
{"code": "AUTH_001", "status": 401, "message": "Invalid or expired token", "message_zh": "Token 无效或已过期"},
{"code": "AUTH_002", "status": 401, "message": "Authentication required", "message_zh": "未提供认证信息"},
{"code": "AUTH_003", "status": 403, "message": "Insufficient permissions", "message_zh": "权限不足"}
]
}
}
```
### Phase 4: Task Decomposition
**Task Hierarchy**:
```
Level 1: Infrastructure Tasks (Parallel)
├─ IMPL-001: Generate main OpenAPI spec file (swagger.yaml)
├─ IMPL-002: Generate global security config and auth documentation
└─ IMPL-003: Generate unified error code specification
Level 2: Module Documentation Tasks (Parallel, by business module)
├─ IMPL-004: Users module API documentation
├─ IMPL-005: Auth module API documentation
├─ IMPL-006: Business module N API documentation
└─ ...
Level 3: Aggregation Tasks (Depends on Level 1-2)
├─ IMPL-N+1: Generate API overview and navigation
└─ IMPL-N+2: Generate version history and changelog
Level 4: Validation Tasks (Depends on Level 1-3)
├─ IMPL-N+3: API endpoint validation tests
└─ IMPL-N+4: Boundary condition tests
```
**Grouping Strategy**:
1. Group by business module (users, orders, products, etc.)
2. Maximum 10 endpoints per task
3. Large modules (>10 endpoints) split by submodules
**Commands**:
```bash
# 1. Count endpoints by module
bash(cat ${session_dir}/.process/swagger-planning-data.json | jq '.statistics.by_module')
# 2. Calculate task groupings
bash(cat ${session_dir}/.process/swagger-planning-data.json | jq -r '.api_structure.modules[] | "\(.name):\(.endpoints | length)"')
```
**Data Processing**: Use **Edit tool** to update `swagger-planning-data.json` with task groups:
```json
{
"task_groups": {
"level1_count": 3,
"level2_count": 5,
"total_count": 12,
"assignments": [
{"task_id": "IMPL-001", "level": 1, "type": "openapi-spec", "title": "Generate OpenAPI main spec file"},
{"task_id": "IMPL-002", "level": 1, "type": "security", "title": "Generate global security config"},
{"task_id": "IMPL-003", "level": 1, "type": "error-codes", "title": "Generate error code specification"},
{"task_id": "IMPL-004", "level": 2, "type": "module-doc", "module": "users", "endpoint_count": 12},
{"task_id": "IMPL-005", "level": 2, "type": "module-doc", "module": "auth", "endpoint_count": 8}
]
}
}
```
### Phase 5: Generate Task JSONs
**Generation Process**:
1. Read configuration values from workflow-session.json
2. Read task groups from swagger-planning-data.json
3. Generate Level 1 tasks (infrastructure)
4. Generate Level 2 tasks (by module)
5. Generate Level 3-4 tasks (aggregation and validation)
## Task Templates
### Level 1-1: OpenAPI Main Spec File
```json
{
"id": "IMPL-001",
"title": "Generate OpenAPI main specification file",
"status": "pending",
"meta": {
"type": "swagger-openapi-spec",
"agent": "@doc-generator",
"tool": "gemini",
"priority": "critical"
},
"context": {
"requirements": [
"Generate OpenAPI 3.0.3 compliant swagger.yaml",
"Include complete info, servers, tags, paths, components definitions",
"Follow RESTful design standards, use {lang} for descriptions"
],
"precomputed_data": {
"planning_data": "${session_dir}/.process/swagger-planning-data.json"
}
},
"flow_control": {
"pre_analysis": [
{
"step": "load_analysis_data",
"action": "Load API analysis data",
"commands": [
"bash(cat ${session_dir}/.process/swagger-planning-data.json)"
],
"output_to": "api_analysis"
}
],
"implementation_approach": [
{
"step": 1,
"title": "Generate OpenAPI spec file",
"description": "Create complete swagger.yaml specification file",
"cli_prompt": "PURPOSE: Generate OpenAPI 3.0.3 specification file from analyzed API structure\nTASK:\n• Define openapi version: 3.0.3\n• Define info: title, description, version, contact, license\n• Define servers: development, staging, production environments\n• Define tags: organized by business modules\n• Define paths: all API endpoints with complete specifications\n• Define components: schemas, securitySchemes, parameters, responses\nMODE: write\nCONTEXT: @[api_analysis]\nEXPECTED: Complete swagger.yaml file following OpenAPI 3.0.3 specification\nCONSTRAINTS: Use {lang} for all descriptions | Strict RESTful standards\n--rule documentation-swagger-api",
"output": "swagger.yaml"
}
],
"target_files": [
".workflow/docs/${project_name}/api/swagger.yaml"
]
}
}
```
### Level 1-2: Global Security Configuration
```json
{
"id": "IMPL-002",
"title": "Generate global security configuration and authentication guide",
"status": "pending",
"meta": {
"type": "swagger-security",
"agent": "@doc-generator",
"tool": "gemini"
},
"context": {
"requirements": [
"Document Authorization header format in detail",
"Describe token acquisition, refresh, and expiration mechanisms",
"List permission requirements for each endpoint"
]
},
"flow_control": {
"pre_analysis": [
{
"step": "analyze_auth",
"command": "bash(rg -n 'auth|guard|jwt|bearer' -i --type ts -g '!*.test.*' 2>/dev/null | head -50)",
"output_to": "auth_patterns"
}
],
"implementation_approach": [
{
"step": 1,
"title": "Generate authentication documentation",
"cli_prompt": "PURPOSE: Generate comprehensive authentication documentation for API security\nTASK:\n• Document authentication mechanism: JWT Bearer Token\n• Explain header format: Authorization: Bearer <token>\n• Describe token lifecycle: acquisition, refresh, expiration handling\n• Define permission levels: public, user, admin, super_admin\n• Document authentication failure responses: 401/403 error handling\nMODE: write\nCONTEXT: @[auth_patterns] @src/**/auth/**/* @src/**/guard/**/*\nEXPECTED: Complete authentication guide in {lang}\nCONSTRAINTS: Include code examples | Clear step-by-step instructions\n--rule development-feature",
"output": "{auth_doc_name}"
}
],
"target_files": [
".workflow/docs/${project_name}/api/{overview_dir}/{auth_doc_name}"
]
}
}
```
### Level 1-3: Unified Error Code Specification
```json
{
"id": "IMPL-003",
"title": "Generate unified error code specification",
"status": "pending",
"meta": {
"type": "swagger-error-codes",
"agent": "@doc-generator",
"tool": "gemini"
},
"context": {
"requirements": [
"Define unified error response format",
"Create categorized error code system (auth, business, system)",
"Provide detailed description and examples for each error code"
]
},
"flow_control": {
"implementation_approach": [
{
"step": 1,
"title": "Generate error code specification document",
"cli_prompt": "PURPOSE: Generate comprehensive error code specification for consistent API error handling\nTASK:\n• Define error response format: {code, message, details, timestamp}\n• Document authentication errors (AUTH_xxx): 401/403 series\n• Document parameter errors (PARAM_xxx): 400 series\n• Document business errors (BIZ_xxx): business logic errors\n• Document system errors (SYS_xxx): 500 series\n• For each error code: HTTP status, error message, possible causes, resolution suggestions\nMODE: write\nCONTEXT: @src/**/*.exception.ts @src/**/*.filter.ts\nEXPECTED: Complete error code specification in {lang} with tables and examples\nCONSTRAINTS: Include response examples | Clear categorization\n--rule development-feature",
"output": "{error_doc_name}"
}
],
"target_files": [
".workflow/docs/${project_name}/api/{overview_dir}/{error_doc_name}"
]
}
}
```
### Level 2: Module API Documentation (Template)
```json
{
"id": "IMPL-${module_task_id}",
"title": "Generate ${module_name} API documentation",
"status": "pending",
"depends_on": ["IMPL-001", "IMPL-002", "IMPL-003"],
"meta": {
"type": "swagger-module-doc",
"agent": "@doc-generator",
"tool": "gemini",
"module": "${module_name}",
"endpoint_count": "${endpoint_count}"
},
"context": {
"requirements": [
"Complete documentation for all endpoints in this module",
"Each endpoint: description, method, URL, parameters, responses",
"Include success and failure response examples",
"Mark API version and last update time"
],
"focus_paths": ["${module_source_paths}"]
},
"flow_control": {
"pre_analysis": [
{
"step": "load_module_endpoints",
"action": "Load module endpoint information",
"commands": [
"bash(cat ${session_dir}/.process/swagger-planning-data.json | jq '.api_structure.modules[] | select(.name == \"${module_name}\")')"
],
"output_to": "module_endpoints"
},
{
"step": "read_source_files",
"action": "Read module source files",
"commands": [
"bash(cat ${module_source_files})"
],
"output_to": "source_code"
}
],
"implementation_approach": [
{
"step": 1,
"title": "Generate module API documentation",
"description": "Generate complete API documentation for ${module_name}",
"cli_prompt": "PURPOSE: Generate complete RESTful API documentation for ${module_name} module\nTASK:\n• Create module overview: purpose, use cases, prerequisites\n• Generate endpoint index: grouped by functionality\n• For each endpoint document:\n - Functional description: purpose and business context\n - Request method: GET/POST/PUT/DELETE\n - URL path: complete API path\n - Request headers: Authorization and other required headers\n - Path parameters: {id} and other path variables\n - Query parameters: pagination, filters, etc.\n - Request body: JSON Schema format\n - Response body: success and error responses\n - Field description table: type, required, example, description\n• Add usage examples: cURL, JavaScript, Python\n• Add version info: v1.0.0, last updated date\nMODE: write\nCONTEXT: @[module_endpoints] @[source_code]\nEXPECTED: Complete module API documentation in {lang} with all endpoints fully documented\nCONSTRAINTS: RESTful standards | Include all response codes\n--rule documentation-swagger-api",
"output": "${module_doc_name}"
}
],
"target_files": [
".workflow/docs/${project_name}/api/${module_dir}/${module_doc_name}"
]
}
}
```
### Level 3: API Overview and Navigation
```json
{
"id": "IMPL-${overview_task_id}",
"title": "Generate API overview and navigation",
"status": "pending",
"depends_on": ["IMPL-001", "...", "IMPL-${last_module_task_id}"],
"meta": {
"type": "swagger-overview",
"agent": "@doc-generator",
"tool": "gemini"
},
"flow_control": {
"pre_analysis": [
{
"step": "load_all_docs",
"command": "bash(find .workflow/docs/${project_name}/api -type f -name '*.md' ! -path '*/{overview_dir}/*' | xargs cat)",
"output_to": "all_module_docs"
}
],
"implementation_approach": [
{
"step": 1,
"title": "Generate API overview",
"cli_prompt": "PURPOSE: Generate API overview document with navigation and quick start guide\nTASK:\n• Create introduction: system features, tech stack, version\n• Write quick start guide: authentication, first request example\n• Build module navigation: categorized links to all modules\n• Document environment configuration: development, staging, production\n• List SDKs and tools: client libraries, Postman collection\nMODE: write\nCONTEXT: @[all_module_docs] @.workflow/docs/${project_name}/api/swagger.yaml\nEXPECTED: Complete API overview in {lang} with navigation links\nCONSTRAINTS: Clear structure | Quick start focus\n--rule development-feature",
"output": "README.md"
}
],
"target_files": [
".workflow/docs/${project_name}/api/{overview_dir}/README.md"
]
}
}
```
### Level 4: Validation Tasks
```json
{
"id": "IMPL-${test_task_id}",
"title": "API endpoint validation tests",
"status": "pending",
"depends_on": ["IMPL-${overview_task_id}"],
"meta": {
"type": "swagger-validation",
"agent": "@test-fix-agent",
"tool": "codex"
},
"context": {
"requirements": [
"Validate accessibility of all endpoints",
"Test various boundary conditions",
"Verify exception handling"
]
},
"flow_control": {
"pre_analysis": [
{
"step": "load_swagger_spec",
"command": "bash(cat .workflow/docs/${project_name}/api/swagger.yaml)",
"output_to": "swagger_spec"
}
],
"implementation_approach": [
{
"step": 1,
"title": "Generate test report",
"cli_prompt": "PURPOSE: Generate comprehensive API test validation report\nTASK:\n• Document test environment configuration\n• Calculate endpoint coverage statistics\n• Report test results: pass/fail counts\n• Document boundary tests: parameter limits, null values, special characters\n• Document exception tests: auth failures, permission denied, resource not found\n• List issues found with recommendations\nMODE: write\nCONTEXT: @[swagger_spec]\nEXPECTED: Complete test report in {lang} with detailed results\nCONSTRAINTS: Include test cases | Clear pass/fail status\n--rule development-tests",
"output": "{test_doc_name}"
}
],
"target_files": [
".workflow/docs/${project_name}/api/{test_dir}/{test_doc_name}"
]
}
}
```
## Language-Specific Directory Mapping
| Component | --lang zh | --lang en |
|-----------|-----------|-----------|
| Overview dir | 概述 | overview |
| Auth doc | 认证说明.md | authentication.md |
| Error doc | 错误码规范.md | error-codes.md |
| Changelog | 版本历史.md | changelog.md |
| Users module | 用户模块 | users |
| Orders module | 订单模块 | orders |
| Products module | 商品模块 | products |
| Test dir | 测试报告 | test-reports |
| API test doc | 接口测试.md | api-tests.md |
| Boundary test doc | 边界测试.md | boundary-tests.md |
## API Documentation Template
### Single Endpoint Format
Each endpoint must include:
```markdown
### Get User Details
**Description**: Retrieve detailed user information by ID, including profile and permissions.
**Endpoint Info**:
| Property | Value |
|----------|-------|
| Method | GET |
| URL | `/api/v1/users/{id}` |
| Version | v1.0.0 |
| Updated | 2025-01-01 |
| Auth | Bearer Token |
| Permission | user / admin |
**Request Headers**:
| Field | Type | Required | Example | Description |
|-------|------|----------|---------|-------------|
| Authorization | string | Yes | `Bearer eyJhbGc...` | JWT Token |
| Content-Type | string | No | `application/json` | Request content type |
**Path Parameters**:
| Field | Type | Required | Example | Description |
|-------|------|----------|---------|-------------|
| id | string | Yes | `usr_123456` | Unique user identifier |
**Query Parameters**:
| Field | Type | Required | Default | Example | Description |
|-------|------|----------|---------|---------|-------------|
| include | string | No | - | `roles,permissions` | Related data to include |
**Success Response** (200 OK):
```json
{
"code": 0,
"message": "success",
"data": {
"id": "usr_123456",
"email": "user@example.com",
"name": "John Doe",
"status": "active",
"roles": ["user"],
"created_at": "2025-01-01T00:00:00Z",
"updated_at": "2025-01-01T00:00:00Z"
},
"timestamp": "2025-01-01T12:00:00Z"
}
```
**Response Fields**:
| Field | Type | Description |
|-------|------|-------------|
| code | integer | Business status code, 0 = success |
| message | string | Response message |
| data.id | string | Unique user identifier |
| data.email | string | User email address |
| data.name | string | User display name |
| data.status | string | User status: active/inactive/suspended |
| data.roles | array | User role list |
| data.created_at | string | Creation timestamp (ISO 8601) |
| data.updated_at | string | Last update timestamp (ISO 8601) |
**Error Responses**:
| Status | Code | Message | Possible Cause |
|--------|------|---------|----------------|
| 401 | AUTH_001 | Invalid or expired token | Token format error or expired |
| 403 | AUTH_003 | Insufficient permissions | No access to this user info |
| 404 | USER_001 | User not found | User ID doesn't exist or deleted |
**Examples**:
```bash
# cURL
curl -X GET "https://api.example.com/api/v1/users/usr_123456" \
-H "Authorization: Bearer eyJhbGc..." \
-H "Content-Type: application/json"
```
```javascript
// JavaScript (fetch)
const response = await fetch('https://api.example.com/api/v1/users/usr_123456', {
method: 'GET',
headers: {
'Authorization': 'Bearer eyJhbGc...',
'Content-Type': 'application/json'
}
});
const data = await response.json();
```
```
## Session Structure
```
.workflow/active/
└── WFS-swagger-{timestamp}/
├── workflow-session.json
├── IMPL_PLAN.md
├── TODO_LIST.md
├── .process/
│ └── swagger-planning-data.json
└── .task/
├── IMPL-001.json # OpenAPI spec
├── IMPL-002.json # Security config
├── IMPL-003.json # Error codes
├── IMPL-004.json # Module 1 API
├── ...
├── IMPL-N+1.json # API overview
└── IMPL-N+2.json # Validation tests
```
## Execution Commands
```bash
# Execute entire workflow
/workflow:execute
# Specify session
/workflow:execute --resume-session="WFS-swagger-yyyymmdd-hhmmss"
# Single task execution
/task:execute IMPL-001
```
## Related Commands
- `/workflow:execute` - Execute documentation tasks
- `/workflow:status` - View task progress
- `/workflow:session:complete` - Mark session complete
- `/memory:docs` - General documentation workflow

View File

@@ -1,310 +0,0 @@
---
name: tech-research-rules
description: "3-phase orchestrator: extract tech stack → Exa research → generate path-conditional rules (auto-loaded by Claude Code)"
argument-hint: "[session-id | tech-stack-name] [--regenerate] [--tool <gemini|qwen>]"
allowed-tools: SlashCommand(*), TodoWrite(*), Bash(*), Read(*), Write(*), Task(*)
---
# Tech Stack Rules Generator
## Overview
**Purpose**: Generate multi-layered, path-conditional rules that Claude Code automatically loads based on file context.
**Output Structure**:
```
.claude/rules/tech/{tech-stack}/
├── core.md # paths: **/*.{ext} - Core principles
├── patterns.md # paths: src/**/*.{ext} - Implementation patterns
├── testing.md # paths: **/*.{test,spec}.{ext} - Testing rules
├── config.md # paths: *.config.* - Configuration rules
├── api.md # paths: **/api/**/* - API rules (backend only)
├── components.md # paths: **/components/**/* - Component rules (frontend only)
└── metadata.json # Generation metadata
```
**Templates Location**: `~/.claude/workflows/cli-templates/prompts/rules/`
---
## Core Rules
1. **Start Immediately**: First action is TodoWrite initialization
2. **Path-Conditional Output**: Every rule file includes `paths` frontmatter
3. **Template-Driven**: Agent reads templates before generating content
4. **Agent Produces Files**: Agent writes all rule files directly
5. **No Manual Loading**: Rules auto-activate when Claude works with matching files
---
## 3-Phase Execution
### Phase 1: Prepare Context & Detect Tech Stack
**Goal**: Detect input mode, extract tech stack info, determine file extensions
**Input Mode Detection**:
```bash
input="$1"
if [[ "$input" == WFS-* ]]; then
MODE="session"
SESSION_ID="$input"
# Read workflow-session.json to extract tech stack
else
MODE="direct"
TECH_STACK_NAME="$input"
fi
```
**Tech Stack Analysis**:
```javascript
// Decompose composite tech stacks
// "typescript-react-nextjs" → ["typescript", "react", "nextjs"]
const TECH_EXTENSIONS = {
"typescript": "{ts,tsx}",
"javascript": "{js,jsx}",
"python": "py",
"rust": "rs",
"go": "go",
"java": "java",
"csharp": "cs",
"ruby": "rb",
"php": "php"
};
const FRAMEWORK_TYPE = {
"react": "frontend",
"vue": "frontend",
"angular": "frontend",
"nextjs": "fullstack",
"nuxt": "fullstack",
"fastapi": "backend",
"express": "backend",
"django": "backend",
"rails": "backend"
};
```
**Check Existing Rules**:
```bash
normalized_name=$(echo "$TECH_STACK_NAME" | tr '[:upper:]' '[:lower:]' | tr ' ' '-')
rules_dir=".claude/rules/tech/${normalized_name}"
existing_count=$(find "${rules_dir}" -name "*.md" 2>/dev/null | wc -l || echo 0)
```
**Skip Decision**:
- If `existing_count > 0` AND no `--regenerate``SKIP_GENERATION = true`
- If `--regenerate` → Delete existing and regenerate
**Output Variables**:
- `TECH_STACK_NAME`: Normalized name
- `PRIMARY_LANG`: Primary language
- `FILE_EXT`: File extension pattern
- `FRAMEWORK_TYPE`: frontend | backend | fullstack | library
- `COMPONENTS`: Array of tech components
- `SKIP_GENERATION`: Boolean
**TodoWrite**: Mark phase 1 completed
---
### Phase 2: Agent Produces Path-Conditional Rules
**Skip Condition**: Skipped if `SKIP_GENERATION = true`
**Goal**: Delegate to agent for Exa research and rule file generation
**Template Files**:
```
~/.claude/workflows/cli-templates/prompts/rules/
├── tech-rules-agent-prompt.txt # Agent instructions
├── rule-core.txt # Core principles template
├── rule-patterns.txt # Implementation patterns template
├── rule-testing.txt # Testing rules template
├── rule-config.txt # Configuration rules template
├── rule-api.txt # API rules template (backend)
└── rule-components.txt # Component rules template (frontend)
```
**Agent Task**:
```javascript
Task({
subagent_type: "general-purpose",
description: `Generate tech stack rules: ${TECH_STACK_NAME}`,
prompt: `
You are generating path-conditional rules for Claude Code.
## Context
- Tech Stack: ${TECH_STACK_NAME}
- Primary Language: ${PRIMARY_LANG}
- File Extensions: ${FILE_EXT}
- Framework Type: ${FRAMEWORK_TYPE}
- Components: ${JSON.stringify(COMPONENTS)}
- Output Directory: .claude/rules/tech/${TECH_STACK_NAME}/
## Instructions
Read the agent prompt template for detailed instructions.
Use --rule rules-tech-rules-agent-prompt to load the template automatically.
## Execution Steps
1. Execute Exa research queries (see agent prompt)
2. Read each rule template
3. Generate rule files following template structure
4. Write files to output directory
5. Write metadata.json
6. Report completion
## Variable Substitutions
Replace in templates:
- {TECH_STACK_NAME} → ${TECH_STACK_NAME}
- {PRIMARY_LANG} → ${PRIMARY_LANG}
- {FILE_EXT} → ${FILE_EXT}
- {FRAMEWORK_TYPE} → ${FRAMEWORK_TYPE}
`
})
```
**Completion Criteria**:
- 4-6 rule files written with proper `paths` frontmatter
- metadata.json written
- Agent reports files created
**TodoWrite**: Mark phase 2 completed
---
### Phase 3: Verify & Report
**Goal**: Verify generated files and provide usage summary
**Steps**:
1. **Verify Files**:
```bash
find ".claude/rules/tech/${TECH_STACK_NAME}" -name "*.md" -type f
```
2. **Validate Frontmatter**:
```bash
head -5 ".claude/rules/tech/${TECH_STACK_NAME}/core.md"
```
3. **Read Metadata**:
```javascript
Read(`.claude/rules/tech/${TECH_STACK_NAME}/metadata.json`)
```
4. **Generate Summary Report**:
```
Tech Stack Rules Generated
Tech Stack: {TECH_STACK_NAME}
Location: .claude/rules/tech/{TECH_STACK_NAME}/
Files Created:
├── core.md → paths: **/*.{ext}
├── patterns.md → paths: src/**/*.{ext}
├── testing.md → paths: **/*.{test,spec}.{ext}
├── config.md → paths: *.config.*
├── api.md → paths: **/api/**/* (if backend)
└── components.md → paths: **/components/**/* (if frontend)
Auto-Loading:
- Rules apply automatically when editing matching files
- No manual loading required
Example Activation:
- Edit src/components/Button.tsx → core.md + patterns.md + components.md
- Edit tests/api.test.ts → core.md + testing.md
- Edit package.json → config.md
```
**TodoWrite**: Mark phase 3 completed
---
## Path Pattern Reference
| Pattern | Matches |
|---------|---------|
| `**/*.ts` | All .ts files |
| `src/**/*` | All files under src/ |
| `*.config.*` | Config files in root |
| `**/*.{ts,tsx}` | .ts and .tsx files |
| Tech Stack | Core Pattern | Test Pattern |
|------------|--------------|--------------|
| TypeScript | `**/*.{ts,tsx}` | `**/*.{test,spec}.{ts,tsx}` |
| Python | `**/*.py` | `**/test_*.py, **/*_test.py` |
| Rust | `**/*.rs` | `**/tests/**/*.rs` |
| Go | `**/*.go` | `**/*_test.go` |
---
## Parameters
```bash
/memory:tech-research [session-id | "tech-stack-name"] [--regenerate]
```
**Arguments**:
- **session-id**: `WFS-*` format - Extract from workflow session
- **tech-stack-name**: Direct input - `"typescript"`, `"typescript-react"`
- **--regenerate**: Force regenerate existing rules
---
## Examples
### Single Language
```bash
/memory:tech-research "typescript"
```
**Output**: `.claude/rules/tech/typescript/` with 4 rule files
### Frontend Stack
```bash
/memory:tech-research "typescript-react"
```
**Output**: `.claude/rules/tech/typescript-react/` with 5 rule files (includes components.md)
### Backend Stack
```bash
/memory:tech-research "python-fastapi"
```
**Output**: `.claude/rules/tech/python-fastapi/` with 5 rule files (includes api.md)
### From Session
```bash
/memory:tech-research WFS-user-auth-20251104
```
**Workflow**: Extract tech stack from session → Generate rules
---
## Comparison: Rules vs SKILL
| Aspect | SKILL Memory | Rules |
|--------|--------------|-------|
| Loading | Manual: `Skill("tech")` | Automatic by path |
| Scope | All files when loaded | Only matching files |
| Granularity | Monolithic packages | Per-file-type |
| Context | Full package | Only relevant rules |
**When to Use**:
- **Rules**: Tech stack conventions per file type
- **SKILL**: Reference docs, APIs, examples for manual lookup

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@@ -0,0 +1,332 @@
---
name: tips
description: Quick note-taking command to capture ideas, snippets, reminders, and insights for later reference
argument-hint: "<note content> [--tag <tag1,tag2>] [--context <context>]"
allowed-tools: mcp__ccw-tools__core_memory(*), Read(*)
examples:
- /memory:tips "Remember to use Redis for rate limiting"
- /memory:tips "Auth pattern: JWT with refresh tokens" --tag architecture,auth
- /memory:tips "Bug: memory leak in WebSocket handler after 24h" --context websocket-service
- /memory:tips "Performance: lazy loading reduced bundle by 40%" --tag performance
---
# Memory Tips Command (/memory:tips)
## 1. Overview
The `memory:tips` command provides **quick note-taking** for capturing:
- Quick ideas and insights
- Code snippets and patterns
- Reminders and follow-ups
- Bug notes and debugging hints
- Performance observations
- Architecture decisions
- Library/tool recommendations
**Core Philosophy**:
- **Speed First**: Minimal friction for capturing thoughts
- **Searchable**: Tagged for easy retrieval
- **Context-Aware**: Optional context linking
- **Lightweight**: No complex session analysis
## 2. Parameters
- `<note content>` (Required): The tip/note content to save
- `--tag <tags>` (Optional): Comma-separated tags for categorization
- `--context <context>` (Optional): Related context (file, module, feature)
**Examples**:
```bash
/memory:tips "Use Zod for runtime validation - better DX than class-validator"
/memory:tips "Redis connection pool: max 10, min 2" --tag config,redis
/memory:tips "Fix needed: race condition in payment processor" --tag bug,payment --context src/payments
```
## 3. Structured Output Format
```markdown
## Tip ID
TIP-YYYYMMDD-HHMMSS
## Timestamp
YYYY-MM-DD HH:MM:SS
## Project Root
[Absolute path to project root, e.g., D:\Claude_dms3]
## Content
[The tip/note content exactly as provided]
## Tags
[Comma-separated tags, or (none)]
## Context
[Optional context linking - file, module, or feature reference]
## Session Link
[WFS-ID if workflow session active, otherwise (none)]
## Auto-Detected Context
[Files/topics from current conversation if relevant]
```
## 4. Field Definitions
| Field | Purpose | Example |
|-------|---------|---------|
| **Tip ID** | Unique identifier with timestamp | TIP-20260128-143052 |
| **Timestamp** | When tip was created | 2026-01-28 14:30:52 |
| **Project Root** | Current project path | D:\Claude_dms3 |
| **Content** | The actual tip/note | "Use Redis for rate limiting" |
| **Tags** | Categorization labels | architecture, auth, performance |
| **Context** | Related code/feature | src/auth/**, payment-module |
| **Session Link** | Link to workflow session | WFS-auth-20260128 |
| **Auto-Detected Context** | Files from conversation | src/api/handler.ts |
## 5. Execution Flow
### Step 1: Parse Arguments
```javascript
const parseTipsCommand = (input) => {
// Extract note content (everything before flags)
const contentMatch = input.match(/^"([^"]+)"|^([^\s-]+)/);
const content = contentMatch ? (contentMatch[1] || contentMatch[2]) : '';
// Extract tags
const tagsMatch = input.match(/--tag\s+([^\s-]+)/);
const tags = tagsMatch ? tagsMatch[1].split(',').map(t => t.trim()) : [];
// Extract context
const contextMatch = input.match(/--context\s+([^\s-]+)/);
const context = contextMatch ? contextMatch[1] : '';
return { content, tags, context };
};
```
### Step 2: Gather Context
```javascript
const gatherTipContext = async () => {
// Get project root
const projectRoot = process.cwd(); // or detect from environment
// Get current session if active
const manifest = await mcp__ccw-tools__session_manager({
operation: "list",
location: "active"
});
const sessionId = manifest.sessions?.[0]?.id || null;
// Auto-detect files from recent conversation
const recentFiles = extractRecentFilesFromConversation(); // Last 5 messages
return {
projectRoot,
sessionId,
autoDetectedContext: recentFiles
};
};
```
### Step 3: Generate Structured Text
```javascript
const generateTipText = (parsed, context) => {
const timestamp = new Date().toISOString().replace('T', ' ').slice(0, 19);
const tipId = `TIP-${new Date().toISOString().slice(0,10).replace(/-/g, '')}-${new Date().toTimeString().slice(0,8).replace(/:/g, '')}`;
return `## Tip ID
${tipId}
## Timestamp
${timestamp}
## Project Root
${context.projectRoot}
## Content
${parsed.content}
## Tags
${parsed.tags.length > 0 ? parsed.tags.join(', ') : '(none)'}
## Context
${parsed.context || '(none)'}
## Session Link
${context.sessionId || '(none)'}
## Auto-Detected Context
${context.autoDetectedContext.length > 0
? context.autoDetectedContext.map(f => `- ${f}`).join('\n')
: '(none)'}`;
};
```
### Step 4: Save to Core Memory
```javascript
mcp__ccw-tools__core_memory({
operation: "import",
text: structuredText
})
```
**Response Format**:
```json
{
"operation": "import",
"id": "CMEM-YYYYMMDD-HHMMSS",
"message": "Created memory: CMEM-YYYYMMDD-HHMMSS"
}
```
### Step 5: Confirm to User
```
✓ Tip saved successfully
ID: CMEM-YYYYMMDD-HHMMSS
Tags: architecture, auth
Context: src/auth/**
To retrieve: /memory:search "auth patterns"
Or via MCP: core_memory(operation="search", query="auth")
```
## 6. Tag Categories (Suggested)
**Technical**:
- `architecture` - Design decisions and patterns
- `performance` - Optimization insights
- `security` - Security considerations
- `bug` - Bug notes and fixes
- `config` - Configuration settings
- `api` - API design patterns
**Development**:
- `testing` - Test strategies and patterns
- `debugging` - Debugging techniques
- `refactoring` - Refactoring notes
- `documentation` - Doc improvements
**Domain Specific**:
- `auth` - Authentication/authorization
- `database` - Database patterns
- `frontend` - UI/UX patterns
- `backend` - Backend logic
- `devops` - Infrastructure and deployment
**Organizational**:
- `reminder` - Follow-up items
- `research` - Research findings
- `idea` - Feature ideas
- `review` - Code review notes
## 7. Search Integration
Tips can be retrieved using:
```bash
# Via command (if /memory:search exists)
/memory:search "rate limiting"
# Via MCP tool
mcp__ccw-tools__core_memory({
operation: "search",
query: "rate limiting",
source_type: "core_memory",
top_k: 10
})
# Via CLI
ccw core-memory search --query "rate limiting" --top-k 10
```
## 8. Quality Checklist
Before saving:
- [ ] Content is clear and actionable
- [ ] Tags are relevant and consistent
- [ ] Context provides enough reference
- [ ] Auto-detected context is accurate
- [ ] Project root is absolute path
- [ ] Timestamp is properly formatted
## 9. Best Practices
### Good Tips Examples
**Specific and Actionable**:
```
"Use connection pooling for Redis: { max: 10, min: 2, acquireTimeoutMillis: 30000 }"
--tag config,redis
```
**With Context**:
```
"Auth middleware must validate both access and refresh tokens"
--tag security,auth --context src/middleware/auth.ts
```
**Problem + Solution**:
```
"Memory leak fixed by unsubscribing event listeners in componentWillUnmount"
--tag bug,react --context src/components/Chat.tsx
```
### Poor Tips Examples
**Too Vague**:
```
"Fix the bug" --tag bug
```
**Too Long** (use /memory:compact instead):
```
"Here's the complete implementation plan for the entire auth system... [3 paragraphs]"
```
**No Context**:
```
"Remember to update this later"
```
## 10. Use Cases
### During Development
```bash
/memory:tips "JWT secret must be 256-bit minimum" --tag security,auth
/memory:tips "Use debounce (300ms) for search input" --tag performance,ux
```
### After Bug Fixes
```bash
/memory:tips "Race condition in payment: lock with Redis SETNX" --tag bug,payment
```
### Code Review Insights
```bash
/memory:tips "Prefer early returns over nested ifs" --tag style,readability
```
### Architecture Decisions
```bash
/memory:tips "Chose PostgreSQL over MongoDB for ACID compliance" --tag architecture,database
```
### Library Recommendations
```bash
/memory:tips "Zod > Yup for TypeScript validation - better type inference" --tag library,typescript
```
## 11. Notes
- **Frequency**: Use liberally - capture all valuable insights
- **Retrieval**: Search by tags, content, or context
- **Lifecycle**: Tips persist across sessions
- **Organization**: Tags enable filtering and categorization
- **Integration**: Can reference tips in later workflows
- **Lightweight**: No complex session analysis required

View File

@@ -1,517 +0,0 @@
---
name: workflow-skill-memory
description: Process WFS-* archived sessions using universal-executor agents with Gemini analysis to generate workflow-progress SKILL package (sessions-timeline, lessons, conflicts)
argument-hint: "session <session-id> | all"
allowed-tools: Task(*), TodoWrite(*), Bash(*), Read(*), Write(*)
---
# Workflow SKILL Memory Generator
## Overview
Generate SKILL package from archived workflow sessions using agent-driven analysis. Supports single-session incremental updates or parallel processing of all sessions.
**Scope**: Only processes WFS-* workflow sessions. Other session types (e.g., doc sessions) are automatically ignored.
## Usage
```bash
/memory:workflow-skill-memory session WFS-<session-id> # Process single WFS session
/memory:workflow-skill-memory all # Process all WFS sessions in parallel
```
## Execution Modes
### Mode 1: Single Session (`session <session-id>`)
**Purpose**: Incremental update - process one archived session and merge into existing SKILL package
**Workflow**:
1. **Validate session**: Check if session exists in `.workflow/.archives/{session-id}/`
2. **Invoke agent**: Call `universal-executor` to analyze session and update SKILL documents
3. **Agent tasks**:
- Read session data from `.workflow/.archives/{session-id}/`
- Extract lessons, conflicts, and outcomes
- Use Gemini for intelligent aggregation (optional)
- Update or create SKILL documents using templates
- Regenerate SKILL.md index
**Command Example**:
```bash
/memory:workflow-skill-memory session WFS-user-auth
```
**Expected Output**:
```
Session WFS-user-auth processed
Updated:
- sessions-timeline.md (1 session added)
- lessons-learned.md (3 lessons merged)
- conflict-patterns.md (1 conflict added)
- SKILL.md (index regenerated)
```
---
### Mode 2: All Sessions (`all`)
**Purpose**: Full regeneration - process all archived sessions in parallel for complete SKILL package
**Workflow**:
1. **List sessions**: Read manifest.json to get all archived session IDs
2. **Parallel invocation**: Launch multiple `universal-executor` agents in parallel (one per session)
3. **Agent coordination**:
- Each agent processes one session independently
- Agents use Gemini for analysis
- Agents collect data into JSON (no direct file writes)
- Final aggregator agent merges results and generates SKILL documents
**Command Example**:
```bash
/memory:workflow-skill-memory all
```
**Expected Output**:
```
All sessions processed in parallel
Sessions: 8 total
Updated:
- sessions-timeline.md (8 sessions)
- lessons-learned.md (24 lessons aggregated)
- conflict-patterns.md (12 conflicts documented)
- SKILL.md (index regenerated)
```
---
## Implementation Flow
### Phase 1: Validation and Setup
**Step 1.1: Parse Command Arguments**
Extract mode and session ID:
```javascript
if (args === "all") {
mode = "all"
} else if (args.startsWith("session ")) {
mode = "session"
session_id = args.replace("session ", "").trim()
} else {
ERROR = "Invalid arguments. Usage: session <session-id> | all"
EXIT
}
```
**Step 1.2: Validate Archive Directory**
```bash
bash(test -d .workflow/.archives && echo "exists" || echo "missing")
```
If missing, report error and exit.
**Step 1.3: Mode-Specific Validation**
**Single Session Mode**:
```bash
# Validate session ID format (must start with WFS-)
if [[ ! "$session_id" =~ ^WFS- ]]; then
ERROR = "Invalid session ID format. Only WFS-* sessions are supported"
EXIT
fi
# Check if session exists
bash(test -d .workflow/.archives/{session_id} && echo "exists" || echo "missing")
```
If missing, report error: "Session {session_id} not found in archives"
**All Sessions Mode**:
```bash
# Read manifest and filter only WFS- sessions
bash(cat .workflow/.archives/manifest.json | jq -r '.archives[].session_id | select(startswith("WFS-"))')
```
Store filtered session IDs in array. Ignore doc sessions and other non-WFS sessions.
**Step 1.4: TodoWrite Initialization**
**Single Session Mode**:
```javascript
TodoWrite({todos: [
{"content": "Validate session existence", "status": "completed", "activeForm": "Validating session"},
{"content": "Invoke agent to process session", "status": "in_progress", "activeForm": "Invoking agent"},
{"content": "Verify SKILL package updated", "status": "pending", "activeForm": "Verifying update"}
]})
```
**All Sessions Mode**:
```javascript
TodoWrite({todos: [
{"content": "Read manifest and list sessions", "status": "completed", "activeForm": "Reading manifest"},
{"content": "Invoke agents in parallel", "status": "in_progress", "activeForm": "Invoking agents"},
{"content": "Verify SKILL package regenerated", "status": "pending", "activeForm": "Verifying regeneration"}
]})
```
---
### Phase 2: Agent Invocation
#### Single Session Mode - Agent Task
Invoke `universal-executor` with session-specific task:
**Agent Prompt Structure**:
```
Task: Process Workflow Session for SKILL Package
Context:
- Session ID: {session_id}
- Session Path: .workflow/.archives/{session_id}/
- Mode: Incremental update
Objectives:
1. Read session data:
- workflow-session.json (metadata)
- IMPL_PLAN.md (implementation summary)
- TODO_LIST.md (if exists)
- manifest.json entry for lessons
2. Extract key information:
- Description, tags, metrics
- Lessons (successes, challenges, watch_patterns)
- Context package path (reference only)
- Key outcomes from IMPL_PLAN
3. Use Gemini for aggregation (optional):
Command pattern:
ccw cli -p "
PURPOSE: Extract lessons and conflicts from workflow session
TASK:
• Analyze IMPL_PLAN and lessons from manifest
• Identify success patterns and challenges
• Extract conflict patterns with resolutions
• Categorize by functional domain
MODE: analysis
CONTEXT: @IMPL_PLAN.md @workflow-session.json
EXPECTED: Structured lessons and conflicts in JSON format
RULES: Template reference from skill-aggregation.txt
" --tool gemini --mode analysis --cd .workflow/.archives/{session_id}
3.5. **Generate SKILL.md Description** (CRITICAL for auto-loading):
Read skill-index.txt template Section: "Description Field Generation"
Execute command to get project root:
```bash
git rev-parse --show-toplevel # Example output: /d/Claude_dms3
```
Apply description format:
```
Progressive workflow development history (located at {project_root}).
Load this SKILL when continuing development, analyzing past implementations,
or learning from workflow history, especially when no relevant context exists in memory.
```
**Validation**:
- [ ] Path uses forward slashes (not backslashes)
- [ ] All three use cases present
- [ ] Trigger optimization phrase included
- [ ] Path is absolute (starts with / or drive letter)
4. Read templates for formatting guidance:
- ~/.claude/workflows/cli-templates/prompts/workflow/skill-sessions-timeline.txt
- ~/.claude/workflows/cli-templates/prompts/workflow/skill-lessons-learned.txt
- ~/.claude/workflows/cli-templates/prompts/workflow/skill-conflict-patterns.txt
- ~/.claude/workflows/cli-templates/prompts/workflow/skill-index.txt
**CRITICAL**: From skill-index.txt, read these sections:
- "Description Field Generation" - Rules for generating description
- "Variable Substitution Guide" - All required variables
- "Generation Instructions" - Step-by-step generation process
- "Validation Checklist" - Final validation steps
5. Update SKILL documents:
- sessions-timeline.md: Append new session, update domain grouping
- lessons-learned.md: Merge lessons into categories, update frequencies
- conflict-patterns.md: Add conflicts, update recurring pattern frequencies
- SKILL.md: Regenerate index with updated counts
**For SKILL.md generation**:
- Follow "Generation Instructions" from skill-index.txt (Steps 1-7)
- Use git command for project_root: `git rev-parse --show-toplevel`
- Apply "Description Field Generation" rules
- Validate using "Validation Checklist"
- Increment version (patch level)
6. Return result JSON:
{
"status": "success",
"session_id": "{session_id}",
"updates": {
"sessions_added": 1,
"lessons_merged": count,
"conflicts_added": count
}
}
```
---
#### All Sessions Mode - Parallel Agent Tasks
**Step 2.1: Launch parallel session analyzers**
Invoke multiple agents in parallel (one message with multiple Task calls):
**Per-Session Agent Prompt**:
```
Task: Extract Session Data for SKILL Package
Context:
- Session ID: {session_id}
- Mode: Parallel analysis (no direct file writes)
Objectives:
1. Read session data (same as single mode)
2. Extract key information (same as single mode)
3. Use Gemini for analysis (same as single mode)
4. Return structured data JSON:
{
"status": "success",
"session_id": "{session_id}",
"data": {
"metadata": {
"description": "...",
"archived_at": "...",
"tags": [...],
"metrics": {...}
},
"lessons": {
"successes": [...],
"challenges": [...],
"watch_patterns": [...]
},
"conflicts": [
{
"type": "architecture|dependencies|testing|performance",
"pattern": "...",
"resolution": "...",
"code_impact": [...]
}
],
"impl_summary": "First 200 chars of IMPL_PLAN",
"context_package_path": "..."
}
}
```
**Step 2.2: Aggregate results**
After all session agents complete, invoke aggregator agent:
**Aggregator Agent Prompt**:
```
Task: Aggregate Session Results and Generate SKILL Package
Context:
- Mode: Full regeneration
- Input: JSON results from {session_count} session agents
Objectives:
1. Aggregate all session data:
- Collect metadata from all sessions
- Merge lessons by category
- Group conflicts by type
- Sort sessions by date
2. Use Gemini for final aggregation:
ccw cli -p "
PURPOSE: Aggregate lessons and conflicts from all workflow sessions
TASK:
• Group successes by functional domain
• Categorize challenges by severity (HIGH/MEDIUM/LOW)
• Identify recurring conflict patterns
• Calculate frequencies and prioritize
MODE: analysis
CONTEXT: [Provide aggregated JSON data]
EXPECTED: Final aggregated structure for SKILL documents
RULES: Template reference from skill-aggregation.txt
" --tool gemini --mode analysis
3. Read templates for formatting (same 4 templates as single mode)
4. Generate all SKILL documents:
- sessions-timeline.md (all sessions, sorted by date)
- lessons-learned.md (aggregated lessons with frequencies)
- conflict-patterns.md (recurring patterns with resolutions)
- SKILL.md (index with progressive loading)
5. Write files to .claude/skills/workflow-progress/
6. Return result JSON:
{
"status": "success",
"sessions_processed": count,
"files_generated": ["SKILL.md", "sessions-timeline.md", ...],
"summary": {
"total_sessions": count,
"functional_domains": [...],
"date_range": "...",
"lessons_count": count,
"conflicts_count": count
}
}
```
---
### Phase 3: Verification
**Step 3.1: Check SKILL Package Files**
```bash
bash(ls -lh .claude/skills/workflow-progress/)
```
Verify all 4 files exist:
- SKILL.md
- sessions-timeline.md
- lessons-learned.md
- conflict-patterns.md
**Step 3.2: TodoWrite Completion**
Mark all tasks as completed.
**Step 3.3: Display Summary**
**Single Session Mode**:
```
Session {session_id} processed successfully
Updated:
- sessions-timeline.md
- lessons-learned.md
- conflict-patterns.md
- SKILL.md
SKILL Location: .claude/skills/workflow-progress/SKILL.md
```
**All Sessions Mode**:
```
All sessions processed in parallel
Sessions: {count} total
Functional Domains: {domain_list}
Date Range: {earliest} - {latest}
Generated:
- sessions-timeline.md ({count} sessions)
- lessons-learned.md ({lessons_count} lessons)
- conflict-patterns.md ({conflicts_count} conflicts)
- SKILL.md (4-level progressive loading)
SKILL Location: .claude/skills/workflow-progress/SKILL.md
Usage:
- Level 0: Quick refresh (~2K tokens)
- Level 1: Recent history (~8K tokens)
- Level 2: Complete analysis (~25K tokens)
- Level 3: Deep dive (~40K tokens)
```
---
## Agent Guidelines
### Agent Capabilities
**universal-executor agents can**:
- Read files from `.workflow/.archives/`
- Execute bash commands
- Call Gemini CLI for intelligent analysis
- Read template files for formatting guidance
- Write SKILL package files (single mode) or return JSON (parallel mode)
- Return structured results
### Gemini Usage Pattern
**When to use Gemini**:
- Aggregating lessons from multiple sources
- Identifying recurring patterns
- Classifying conflicts by type and severity
- Extracting structured data from IMPL_PLAN
**Fallback Strategy**: If Gemini fails or times out, use direct file parsing with structured extraction logic.
---
## Template System
### Template Files
All templates located in: `~/.claude/workflows/cli-templates/prompts/workflow/`
1. **skill-sessions-timeline.txt**: Format for sessions-timeline.md
2. **skill-lessons-learned.txt**: Format for lessons-learned.md
3. **skill-conflict-patterns.txt**: Format for conflict-patterns.md
4. **skill-index.txt**: Format for SKILL.md index
5. **skill-aggregation.txt**: Rules for Gemini aggregation (existing)
### Template Usage in Agent
**Agents read templates to understand**:
- File structure and markdown format
- Data sources (which files to read)
- Update strategy (incremental vs full)
- Formatting rules and conventions
- Aggregation logic (for Gemini)
**Templates are NOT shown in this command documentation** - agents read them directly as needed.
---
## Error Handling
### Validation Errors
- **No archives directory**: "Error: No workflow archives found at .workflow/.archives/"
- **Invalid session ID format**: "Error: Invalid session ID format. Only WFS-* sessions are supported"
- **Session not found**: "Error: Session {session_id} not found in archives"
- **No WFS sessions in manifest**: "Error: No WFS-* workflow sessions found in manifest.json"
### Agent Errors
- If agent fails, report error message from agent result
- If Gemini times out, agents use fallback direct parsing
- If template read fails, agents use inline format
### Recovery
- Single session mode: Can be retried without affecting other sessions
- All sessions mode: If one agent fails, others continue; retry failed sessions individually
## Integration
### Called by `/workflow:session:complete`
Automatically invoked after session archival:
```bash
SlashCommand(command="/memory:workflow-skill-memory session {session_id}")
```
### Manual Invocation
Users can manually process sessions:
```bash
/memory:workflow-skill-memory session WFS-custom-feature # Single session
/memory:workflow-skill-memory all # Full regeneration
```