docs: update workflow initialization documentation and add project metadata schema

This commit is contained in:
catlog22
2025-11-24 21:46:44 +08:00
parent 07775cda30
commit 481a716c09
2 changed files with 406 additions and 489 deletions

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@@ -10,555 +10,151 @@ examples:
# Workflow Init Command (/workflow:init)
## Overview
Initializes `.workflow/project.json` with comprehensive project understanding by leveraging **cli-explore-agent** for intelligent analysis and **memory discovery** for SKILL package indexing.
Initialize `.workflow/project.json` with comprehensive project understanding by delegating analysis to **cli-explore-agent**.
**Key Features**:
- **Intelligent Project Analysis**: Uses cli-explore-agent's Deep Scan mode
- **Technology Stack Detection**: Identifies languages, frameworks, build tools
- **Architecture Overview**: Discovers patterns, layers, key components
- **Memory Discovery**: Scans and indexes available SKILL packages
- **Smart Recommendations**: Suggests memory commands based on project state
- **One-time Initialization**: Skips if project.json exists (unless --regenerate)
**Note**: This command may be called by other workflow commands. Upon completion, return immediately to continue the calling workflow without interrupting the task flow.
## Usage
```bash
/workflow:init # Initialize project state (skip if exists)
/workflow:init --regenerate # Force regeneration of project.json
/workflow:init # Initialize (skip if exists)
/workflow:init --regenerate # Force regeneration
```
## Implementation Flow
## Implementation
### Step 1: Check Existing State
```bash
# Check if project.json already exists
bash(test -f .workflow/project.json && echo "EXISTS" || echo "NOT_FOUND")
```
**If EXISTS and no --regenerate flag**:
**If EXISTS and no --regenerate**: Exit early
```
Project already initialized at .workflow/project.json
Use /workflow:init --regenerate to rebuild project analysis
Use /workflow:status --project to view current state
Use /workflow:init --regenerate to rebuild
Use /workflow:status --project to view state
```
**If NOT_FOUND or --regenerate flag**: Proceed to initialization
### Step 2: Project Discovery
### Step 2: Get Project Metadata
```bash
# Get project name and root
bash(basename "$(git rev-parse --show-toplevel 2>/dev/null || pwd)")
bash(git rev-parse --show-toplevel 2>/dev/null || pwd)
# Create .workflow directory
bash(mkdir -p .workflow)
```
### Step 3: Intelligent Project Analysis
### Step 3: Invoke cli-explore-agent
**Invoke cli-explore-agent** with Deep Scan mode for comprehensive understanding:
**For --regenerate**: Backup and preserve existing data
```bash
bash(cp .workflow/project.json .workflow/project.json.backup)
```
**Delegate analysis to agent**:
```javascript
Task(
subagent_type="cli-explore-agent",
description="Deep project analysis",
prompt=`
Analyze project structure and technology stack for workflow initialization.
Analyze project for workflow initialization and generate .workflow/project.json.
## Analysis Objective
Perform Deep Scan analysis to build comprehensive project understanding for .workflow/project.json initialization.
## Output Schema Reference
~/.claude/workflows/cli-templates/schemas/project-json-schema.json
## Required Analysis
## Task
Generate complete project.json with:
- project_name: ${projectName}
- initialized_at: current ISO timestamp
- overview: {description, technology_stack, architecture, key_components, entry_points, metrics}
- features: ${regenerate ? 'preserve from backup' : '[] (empty)'}
- statistics: ${regenerate ? 'preserve from backup' : '{total_features: 0, total_sessions: 0, last_updated}'}
- memory_resources: {skills, documentation, module_docs, gaps, last_scanned}
- _metadata: {initialized_by: "cli-explore-agent", analysis_timestamp, analysis_mode}
### 1. Technology Stack Detection
- **Primary Languages**: Identify all programming languages with file counts
- **Frameworks**: Detect web frameworks (React, Vue, Express, Django, etc.)
- **Build Tools**: Identify build systems (npm, cargo, maven, gradle, etc.)
- **Test Frameworks**: Find testing tools (jest, pytest, go test, etc.)
## Analysis Requirements
### 2. Project Architecture
- **Architecture Style**: Identify patterns (MVC, microservices, monorepo, etc.)
- **Layer Structure**: Discover architectural layers (presentation, business, data)
- **Design Patterns**: Find common patterns (singleton, factory, repository, etc.)
- **Key Components**: List 5-10 core modules/components with brief descriptions
**Technology Stack**:
- Languages: File counts, mark primary
- Frameworks: From package.json, requirements.txt, go.mod, etc.
- Build tools: npm, cargo, maven, webpack, vite
- Test frameworks: jest, pytest, go test, junit
### 3. Project Metrics
- **Total Files**: Count source code files
- **Lines of Code**: Estimate total LOC
- **Module Count**: Number of top-level modules/packages
- **Complexity**: Overall complexity rating (low/medium/high)
**Architecture**:
- Style: MVC, microservices, layered (from structure & imports)
- Layers: presentation, business-logic, data-access
- Patterns: singleton, factory, repository
- Key components: 5-10 modules {name, path, description, importance}
### 4. Entry Points
- **Main Entry**: Identify primary application entry point(s)
- **CLI Commands**: Discover available commands/scripts
- **API Endpoints**: Find HTTP/REST/GraphQL endpoints (if applicable)
**Metrics**:
- total_files: Source files (exclude tests/configs)
- lines_of_code: Use find + wc -l
- module_count: Use ~/.claude/scripts/get_modules_by_depth.sh
- complexity: low | medium | high
## Execution Mode
Use **Deep Scan** with Dual-Source Strategy:
- Phase 1: Bash structural scan (fast pattern discovery)
- Phase 2: Gemini semantic analysis (design intent, patterns)
- Phase 3: Synthesis (merge findings with attribution)
**Entry Points**:
- main: index.ts, main.py, main.go
- cli_commands: package.json scripts, Makefile targets
- api_endpoints: HTTP/REST routes (if applicable)
## Analysis Scope
- Root directory: ${projectRoot}
- Exclude: node_modules, dist, build, .git, vendor, __pycache__
- Focus: Source code directories (src, lib, pkg, app, etc.)
**Memory Resources**:
- skills: Scan .claude/skills/ → [{name, type, path}]
- documentation: Scan .workflow/docs/ → [{name, path, has_readme, has_architecture}]
- module_docs: Find **/CLAUDE.md (exclude node_modules, .git)
- gaps: Identify missing resources
## Output Format
Return JSON structure for programmatic processing:
## Execution
1. Structural scan: get_modules_by_depth.sh, find, wc -l
2. Semantic analysis: Gemini for patterns/architecture
3. Synthesis: Merge findings
4. ${regenerate ? 'Merge with preserved features/statistics from .workflow/project.json.backup' : ''}
5. Write JSON: Write('.workflow/project.json', jsonContent)
6. Report: Return brief completion summary
\`\`\`json
{
"technology_stack": {
"languages": [
{"name": "TypeScript", "file_count": 150, "primary": true},
{"name": "Python", "file_count": 30, "primary": false}
],
"frameworks": ["React", "Express", "TypeORM"],
"build_tools": ["npm", "webpack"],
"test_frameworks": ["Jest", "Supertest"]
},
"architecture": {
"style": "Layered MVC with Repository Pattern",
"layers": ["presentation", "business-logic", "data-access"],
"patterns": ["MVC", "Repository Pattern", "Dependency Injection"],
"key_components": [
{
"name": "Authentication Module",
"path": "src/auth",
"description": "JWT-based authentication with OAuth2 support",
"importance": "high"
},
{
"name": "User Management",
"path": "src/users",
"description": "User CRUD operations and profile management",
"importance": "high"
}
]
},
"metrics": {
"total_files": 180,
"lines_of_code": 15000,
"module_count": 12,
"complexity": "medium"
},
"entry_points": {
"main": "src/index.ts",
"cli_commands": ["npm start", "npm test", "npm run build"],
"api_endpoints": ["/api/auth", "/api/users", "/api/posts"]
},
"analysis_metadata": {
"timestamp": "2025-01-18T10:30:00Z",
"mode": "deep-scan",
"source": "cli-explore-agent"
}
}
\`\`\`
## Quality Requirements
- ✅ All technology stack items verified (no guessing)
- ✅ Key components include file paths for navigation
- ✅ Architecture style based on actual code patterns, not assumptions
- ✅ Metrics calculated from actual file counts/lines
- ✅ Entry points verified as executable
`
Project root: ${projectRoot}
`
)
```
**Agent Output**: JSON structure with comprehensive project analysis
### Step 4: Display Summary
### Step 4: Build project.json from Analysis
**Data Processing**:
```javascript
// Parse agent analysis output
const analysis = JSON.parse(agentOutput);
const projectJson = JSON.parse(Read('.workflow/project.json'));
// Build complete project.json structure
const projectMeta = {
// Basic metadata
project_name: projectName,
initialized_at: new Date().toISOString(),
// Project overview (from cli-explore-agent)
overview: {
description: generateDescription(analysis), // e.g., "TypeScript web application with React frontend"
technology_stack: analysis.technology_stack,
architecture: {
style: analysis.architecture.style,
layers: analysis.architecture.layers,
patterns: analysis.architecture.patterns
},
key_components: analysis.architecture.key_components,
entry_points: analysis.entry_points,
metrics: analysis.metrics
},
// Feature registry (initially empty, populated by complete)
features: [],
// Statistics
statistics: {
total_features: 0,
total_sessions: 0,
last_updated: new Date().toISOString()
},
// Analysis metadata
_metadata: {
initialized_by: "cli-explore-agent",
analysis_timestamp: analysis.analysis_metadata.timestamp,
analysis_mode: analysis.analysis_metadata.mode
}
};
// Helper: Generate project description
function generateDescription(analysis) {
const primaryLang = analysis.technology_stack.languages.find(l => l.primary);
const frameworks = analysis.technology_stack.frameworks.slice(0, 2).join(', ');
return `${primaryLang.name} project using ${frameworks}`;
}
// Write to .workflow/project.json
Write('.workflow/project.json', JSON.stringify(projectMeta, null, 2));
```
### Step 5: Output Summary
```
console.log(`
✓ Project initialized successfully
## Project Overview
Name: ${projectName}
Description: ${overview.description}
Name: ${projectJson.project_name}
Description: ${projectJson.overview.description}
### Technology Stack
Languages: ${languages.map(l => l.name).join(', ')}
Frameworks: ${frameworks.join(', ')}
Languages: ${projectJson.overview.technology_stack.languages.map(l => l.name).join(', ')}
Frameworks: ${projectJson.overview.technology_stack.frameworks.join(', ')}
### Architecture
Style: ${architecture.style}
Components: ${key_components.length} core modules identified
Style: ${projectJson.overview.architecture.style}
Components: ${projectJson.overview.key_components.length} core modules
### Project Metrics
Files: ${metrics.total_files}
LOC: ${metrics.lines_of_code}
Complexity: ${metrics.complexity}
### Metrics
Files: ${projectJson.overview.metrics.total_files}
LOC: ${projectJson.overview.metrics.lines_of_code}
Complexity: ${projectJson.overview.metrics.complexity}
### Memory Resources
SKILL Packages: ${memory_resources.skills.length}
Documentation: ${memory_resources.documentation.length} project(s)
Module Docs: ${memory_resources.module_docs.length} file(s)
Gaps: ${memory_resources.gaps.join(', ') || 'none'}
## Quick Start
• /workflow:plan "feature description" - Start new workflow
• /workflow:status --project - View project state
SKILL Packages: ${projectJson.memory_resources.skills.length}
Documentation: ${projectJson.memory_resources.documentation.length}
Module Docs: ${projectJson.memory_resources.module_docs.length}
Gaps: ${projectJson.memory_resources.gaps.join(', ') || 'none'}
---
Project state saved to: .workflow/project.json
Memory index updated: ${memory_resources.last_scanned}
Project state: .workflow/project.json
${regenerate ? 'Backup: .workflow/project.json.backup' : ''}
`);
```
## Extended project.json Schema
### Complete Structure
```json
{
"project_name": "claude_dms3",
"initialized_at": "2025-01-18T10:00:00Z",
"overview": {
"description": "TypeScript workflow automation system with AI agent orchestration",
"technology_stack": {
"languages": [
{"name": "TypeScript", "file_count": 150, "primary": true},
{"name": "Bash", "file_count": 30, "primary": false}
],
"frameworks": ["Node.js"],
"build_tools": ["npm"],
"test_frameworks": ["Jest"]
},
"architecture": {
"style": "Agent-based workflow orchestration with modular command system",
"layers": ["command-layer", "agent-orchestration", "cli-integration"],
"patterns": ["Command Pattern", "Agent Pattern", "Template Method"]
},
"key_components": [
{
"name": "Workflow Planning",
"path": ".claude/commands/workflow",
"description": "Multi-phase planning workflow with brainstorming and task generation",
"importance": "high"
},
{
"name": "Agent System",
"path": ".claude/agents",
"description": "Specialized agents for code development, testing, documentation",
"importance": "high"
},
{
"name": "CLI Tool Integration",
"path": ".claude/scripts",
"description": "Gemini, Qwen, Codex wrapper scripts for AI-powered analysis",
"importance": "medium"
}
],
"entry_points": {
"main": ".claude/commands/workflow/plan.md",
"cli_commands": ["/workflow:plan", "/workflow:execute", "/memory:docs"],
"api_endpoints": []
},
"metrics": {
"total_files": 180,
"lines_of_code": 15000,
"module_count": 12,
"complexity": "medium"
}
},
"features": [],
"statistics": {
"total_features": 0,
"total_sessions": 0,
"last_updated": "2025-01-18T10:00:00Z"
},
"memory_resources": {
"skills": [
{"name": "claude_dms3", "type": "project_docs", "path": ".claude/skills/claude_dms3"},
{"name": "workflow-progress", "type": "workflow_progress", "path": ".claude/skills/workflow-progress"}
],
"documentation": [
{
"name": "claude_dms3",
"path": ".workflow/docs/claude_dms3",
"has_readme": true,
"has_architecture": true
}
],
"module_docs": [
".claude/commands/workflow/CLAUDE.md",
".claude/agents/CLAUDE.md"
],
"gaps": ["tech_stack"],
"last_scanned": "2025-01-18T10:05:00Z"
},
"_metadata": {
"initialized_by": "cli-explore-agent",
"analysis_timestamp": "2025-01-18T10:00:00Z",
"analysis_mode": "deep-scan",
"memory_scan_timestamp": "2025-01-18T10:05:00Z"
}
}
```
### Phase 5: Discover Memory Resources
**Goal**: Scan and index available SKILL packages (memory command products) using agent delegation
**Invoke general-purpose agent** to discover and catalog all memory products:
```javascript
Task(
subagent_type="general-purpose",
description="Discover memory resources",
prompt=`
Discover and index all memory command products: SKILL packages, documentation, and CLAUDE.md files.
## Discovery Scope
1. **SKILL Packages** (.claude/skills/) - Generated by /memory:skill-memory, /memory:tech-research, etc.
2. **Documentation** (.workflow/docs/) - Generated by /memory:docs
3. **Module Docs** (**/CLAUDE.md) - Generated by /memory:update-full, /memory:update-related
## Discovery Tasks
### 1. Scan SKILL Packages
- List all directories in .claude/skills/
- For each: extract name, classify type, record path
- Types: workflow-progress | codemap-* | style-* | tech_stacks | project_docs
### 2. Scan Documentation
- List directories in .workflow/docs/
- For each project: name, path, check README.md, ARCHITECTURE.md existence
### 3. Scan CLAUDE.md Files
- Find all **/CLAUDE.md (exclude: node_modules, .git, dist, build)
- Return path list only
### 4. Identify Gaps
- No project SKILL? → "project_skill"
- No documentation? → "documentation"
- Missing tech stack SKILL? → "tech_stack"
- No workflow-progress? → "workflow_history"
- <10% modules have CLAUDE.md? → "module_docs_low_coverage"
### 5. Return JSON:
{
"skills": [
{"name": "claude_dms3", "type": "project_docs", "path": ".claude/skills/claude_dms3"},
{"name": "workflow-progress", "type": "workflow_progress", "path": ".claude/skills/workflow-progress"}
],
"documentation": [
{
"name": "my_project",
"path": ".workflow/docs/my_project",
"has_readme": true,
"has_architecture": true
}
],
"module_docs": [
"src/core/CLAUDE.md",
"lib/utils/CLAUDE.md"
],
"gaps": ["tech_stack", "module_docs_low_coverage"]
}
## Context
- Project tech stack: ${JSON.stringify(analysis.technology_stack)}
- Check .workflow/.archives for session history
- If directories missing, return empty state with recommendations
`
)
```
**Agent Output**: JSON structure with skills, documentation, module_docs, and gaps
**Update project.json**:
```javascript
const memoryDiscovery = JSON.parse(agentOutput);
projectMeta.memory_resources = {
...memoryDiscovery,
last_scanned: new Date().toISOString()
};
Write('.workflow/project.json', JSON.stringify(projectMeta, null, 2));
```
**Output Summary**:
```
Memory Resources Indexed:
- SKILL Packages: ${skills.length}
- Documentation: ${documentation.length} project(s)
- Module Docs: ${module_docs.length} file(s)
- Gaps: ${gaps.join(', ') || 'none'}
```
---
## Regeneration Behavior
When using `--regenerate` flag:
1. **Backup existing file**:
```bash
bash(cp .workflow/project.json .workflow/project.json.backup)
```
2. **Preserve features array**:
```javascript
const existingMeta = JSON.parse(Read('.workflow/project.json'));
const preservedFeatures = existingMeta.features || [];
const preservedStats = existingMeta.statistics || {};
```
3. **Re-run cli-explore-agent analysis**
4. **Re-run memory discovery (Phase 5)**
5. **Merge preserved data with new analysis**:
```javascript
const newProjectMeta = {
...analysisResults,
features: preservedFeatures, // Keep existing features
statistics: preservedStats // Keep statistics
};
```
6. **Output**:
```
✓ Project analysis regenerated
Backup saved: .workflow/project.json.backup
Updated:
- Technology stack analysis
- Architecture overview
- Key components discovery
- Memory resources index
Preserved:
- ${preservedFeatures.length} existing features
- Session statistics
```
## Error Handling
### Agent Failure
```
If cli-explore-agent fails:
1. Fall back to basic initialization
2. Use get_modules_by_depth.sh for structure
3. Create minimal project.json with placeholder overview
4. Log warning: "Project initialized with basic analysis. Run /workflow:init --regenerate for full analysis"
```
### Missing Tools
```
If Gemini CLI unavailable:
1. Agent uses Qwen fallback
2. If both fail, use bash-only analysis
3. Mark in _metadata: "analysis_mode": "bash-fallback"
```
### Invalid Project Root
```
If not in git repo and empty directory:
1. Warn user: "Empty project detected"
2. Create minimal project.json
3. Suggest: "Add code files and run /workflow:init --regenerate"
```
### Memory Discovery Failures
**Missing Directories**:
```
If .claude/skills, .workflow/docs, or CLAUDE.md files not found:
1. Return empty state for that category
2. Mark in gaps.missing array
3. Continue initialization
```
**Metadata Read Failures**:
```
If SKILL.md files are unreadable:
1. Include SKILL with basic info: name (from directory), type (inferred), path
2. Log warning: "SKILL package {name} has invalid metadata"
3. Continue with other SKILLs
```
**Coverage Check Failures**:
```
If unable to determine module doc coverage:
1. Skip adding "module_docs_low_coverage" to gaps
2. Continue with other gap checks
```
**Default Empty State**:
```json
{
"memory_resources": {
"skills": [],
"documentation": [],
"module_docs": [],
"gaps": ["project_skill", "documentation", "tech_stack", "workflow_history", "module_docs"],
"last_scanned": "ISO_TIMESTAMP"
}
}
```
**Agent Failure**: Fall back to basic initialization with placeholder overview
**Missing Tools**: Agent uses Qwen fallback or bash-only
**Empty Project**: Create minimal JSON with all gaps identified

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@@ -0,0 +1,321 @@
{
"$schema": "http://json-schema.org/draft-07/schema#",
"title": "Project Metadata Schema",
"description": "Workflow initialization metadata for project-level context",
"type": "object",
"required": [
"project_name",
"initialized_at",
"overview",
"features",
"statistics",
"memory_resources",
"_metadata"
],
"properties": {
"project_name": {
"type": "string",
"description": "Project name extracted from git repo or directory"
},
"initialized_at": {
"type": "string",
"format": "date-time",
"description": "ISO 8601 timestamp of initialization"
},
"overview": {
"type": "object",
"required": [
"description",
"technology_stack",
"architecture",
"key_components",
"entry_points",
"metrics"
],
"properties": {
"description": {
"type": "string",
"description": "Brief project description (e.g., 'TypeScript web application with React frontend')"
},
"technology_stack": {
"type": "object",
"required": ["languages", "frameworks", "build_tools", "test_frameworks"],
"properties": {
"languages": {
"type": "array",
"items": {
"type": "object",
"required": ["name", "file_count", "primary"],
"properties": {
"name": {
"type": "string",
"description": "Language name (e.g., TypeScript, Python)"
},
"file_count": {
"type": "integer",
"description": "Number of source files in this language"
},
"primary": {
"type": "boolean",
"description": "True if this is the primary language"
}
}
}
},
"frameworks": {
"type": "array",
"items": {"type": "string"},
"description": "Detected frameworks (React, Express, Django, etc.)"
},
"build_tools": {
"type": "array",
"items": {"type": "string"},
"description": "Build tools and package managers (npm, cargo, maven, etc.)"
},
"test_frameworks": {
"type": "array",
"items": {"type": "string"},
"description": "Testing frameworks (jest, pytest, go test, etc.)"
}
}
},
"architecture": {
"type": "object",
"required": ["style", "layers", "patterns"],
"properties": {
"style": {
"type": "string",
"description": "Architecture style (MVC, microservices, layered, etc.)"
},
"layers": {
"type": "array",
"items": {"type": "string"},
"description": "Architectural layers (presentation, business-logic, data-access)"
},
"patterns": {
"type": "array",
"items": {"type": "string"},
"description": "Design patterns (Repository, Factory, Singleton, etc.)"
}
}
},
"key_components": {
"type": "array",
"items": {
"type": "object",
"required": ["name", "path", "description", "importance"],
"properties": {
"name": {
"type": "string",
"description": "Component name"
},
"path": {
"type": "string",
"description": "Relative path to component directory"
},
"description": {
"type": "string",
"description": "Brief description of component functionality"
},
"importance": {
"type": "string",
"enum": ["high", "medium", "low"],
"description": "Component importance level"
}
}
},
"description": "5-10 core modules/components"
},
"entry_points": {
"type": "object",
"required": ["main", "cli_commands", "api_endpoints"],
"properties": {
"main": {
"type": "string",
"description": "Primary application entry point (index.ts, main.py, etc.)"
},
"cli_commands": {
"type": "array",
"items": {"type": "string"},
"description": "Available CLI commands (npm start, make build, etc.)"
},
"api_endpoints": {
"type": "array",
"items": {"type": "string"},
"description": "HTTP/REST/GraphQL endpoints (if applicable)"
}
}
},
"metrics": {
"type": "object",
"required": ["total_files", "lines_of_code", "module_count", "complexity"],
"properties": {
"total_files": {
"type": "integer",
"description": "Total source code files"
},
"lines_of_code": {
"type": "integer",
"description": "Estimated total lines of code"
},
"module_count": {
"type": "integer",
"description": "Number of top-level modules/packages"
},
"complexity": {
"type": "string",
"enum": ["low", "medium", "high"],
"description": "Overall project complexity rating"
}
}
}
}
},
"features": {
"type": "array",
"items": {
"type": "object",
"required": ["session_id", "title", "completed_at", "tags"],
"properties": {
"session_id": {
"type": "string",
"description": "WFS session identifier"
},
"title": {
"type": "string",
"description": "Feature title/description"
},
"completed_at": {
"type": "string",
"format": "date-time",
"description": "ISO 8601 timestamp of completion"
},
"tags": {
"type": "array",
"items": {"type": "string"},
"description": "Feature tags for categorization"
}
}
},
"description": "Completed workflow features (populated by /workflow:session:complete)"
},
"statistics": {
"type": "object",
"required": ["total_features", "total_sessions", "last_updated"],
"properties": {
"total_features": {
"type": "integer",
"description": "Count of completed features"
},
"total_sessions": {
"type": "integer",
"description": "Count of workflow sessions"
},
"last_updated": {
"type": "string",
"format": "date-time",
"description": "ISO 8601 timestamp of last update"
}
}
},
"memory_resources": {
"type": "object",
"required": ["skills", "documentation", "module_docs", "gaps", "last_scanned"],
"properties": {
"skills": {
"type": "array",
"items": {
"type": "object",
"required": ["name", "type", "path"],
"properties": {
"name": {
"type": "string",
"description": "SKILL package name"
},
"type": {
"type": "string",
"enum": ["workflow_progress", "project_docs", "tech_stacks", "codemap", "style"],
"description": "SKILL package type"
},
"path": {
"type": "string",
"description": "Relative path to SKILL package directory"
}
}
},
"description": "SKILL packages generated by /memory:* commands"
},
"documentation": {
"type": "array",
"items": {
"type": "object",
"required": ["name", "path", "has_readme", "has_architecture"],
"properties": {
"name": {
"type": "string",
"description": "Documentation project name"
},
"path": {
"type": "string",
"description": "Path to documentation directory"
},
"has_readme": {
"type": "boolean",
"description": "README.md exists"
},
"has_architecture": {
"type": "boolean",
"description": "ARCHITECTURE.md exists"
}
}
},
"description": "Documentation generated by /memory:docs"
},
"module_docs": {
"type": "array",
"items": {"type": "string"},
"description": "Paths to CLAUDE.md files generated by /memory:update-*"
},
"gaps": {
"type": "array",
"items": {
"type": "string",
"enum": [
"project_skill",
"documentation",
"tech_stack",
"workflow_history",
"module_docs_low_coverage"
]
},
"description": "Missing memory resources"
},
"last_scanned": {
"type": "string",
"format": "date-time",
"description": "ISO 8601 timestamp of last memory scan"
}
}
},
"_metadata": {
"type": "object",
"required": ["initialized_by", "analysis_timestamp", "analysis_mode"],
"properties": {
"initialized_by": {
"type": "string",
"description": "Agent or tool that performed initialization"
},
"analysis_timestamp": {
"type": "string",
"format": "date-time",
"description": "ISO 8601 timestamp of analysis"
},
"analysis_mode": {
"type": "string",
"enum": ["deep-scan", "quick-scan", "bash-fallback"],
"description": "Analysis mode used"
}
}
}
}
}