feat: add DDD scan, sync, and update commands for document indexing

- Implemented `/ddd:scan` command to analyze existing codebases and generate document indices without specifications. This includes phases for project structure analysis, component discovery, feature inference, and requirement extraction.
- Introduced `/ddd:sync` command for post-task synchronization, updating document indices, generating action logs, and refreshing feature/component documentation after development tasks.
- Added `/ddd:update` command for lightweight incremental updates to the document index, allowing for quick impact checks during development and pre-commit validation.
- Created `execute.md` for the coordinator role in the team lifecycle, detailing the spawning of executor team-workers for IMPL tasks.
- Added `useHasHydrated` hook to determine if the Zustand workflow store has been rehydrated from localStorage, improving state management reliability.
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catlog22
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---
name: scan
description: Scan existing codebase to build document index without specs. Analyzes code structure, infers features, discovers components, and reverse-engineers project knowledge graph.
argument-hint: "[-y|--yes] [--from-scratch] [--scope <dir>] \"optional project description\""
allowed-tools: TodoWrite(*), Agent(*), AskUserQuestion(*), Read(*), Grep(*), Glob(*), Bash(*), Edit(*), Write(*), mcp__ace-tool__search_context(*)
---
## Auto Mode
When `--yes` or `-y`: Auto-confirm feature groupings, component naming, skip interactive review.
# DDD Scan Command (/ddd:scan)
## Purpose
For **existing projects without specifications**: analyze codebase to construct the document index by reverse-engineering project structure. This is the code-first entry point — no spec-generator required.
```
Codebase → Components → Features (inferred) → Requirements (inferred) → doc-index.json
```
## When to Use
- Existing project, no spec-generator outputs
- Want to start using doc-driven workflow on a legacy codebase
- Quick project mapping for onboarding or audit
## Prerequisite
- A codebase must exist (src/, lib/, app/, or similar source directories)
- Git repository recommended (for action history seeding)
## Storage Location
```
.workflow/.doc-index/
├── doc-index.json ← Central index (primary output)
├── feature-maps/ ← Inferred feature documentation
│ ├── _index.md
│ └── {feature-slug}.md
├── tech-registry/ ← Discovered component documentation
│ ├── _index.md
│ └── {component-slug}.md
└── action-logs/ ← Git history seeds
├── _index.md
└── {act-hash}.md
```
## Phase 1: Project Structure Analysis
### 1.1 Framework & Stack Detection
```bash
ccw cli -p "PURPOSE: Analyze project structure, tech stack, and architecture for documentation indexing.
TASK:
• Detect language/framework from manifest files (package.json, go.mod, Cargo.toml, requirements.txt, etc.)
• Map directory structure: source dirs, test dirs, config dirs, entry points
• Identify architectural pattern: monolith, microservices, monorepo, library, CLI tool
• Detect key dependencies and their roles (ORM, HTTP framework, auth library, etc.)
• List all major source directories with brief purpose description
MODE: analysis
CONTEXT: @**/*
EXPECTED: JSON with: {
project_name, language, framework, architecture_pattern,
source_dirs: [{ path, purpose, file_count }],
dependencies: [{ name, role }],
entry_points: [{ path, description }]
}
CONSTRAINTS: Prioritize source directories | Ignore node_modules, dist, build, vendor" --tool gemini --mode analysis
```
### 1.2 Merge with project-tech.json
If `.workflow/project-tech.json` exists, merge to reduce redundant analysis.
## Phase 2: Component Discovery
### 2.1 Deep Module Scan
```bash
ccw cli -p "PURPOSE: Discover all significant code components/modules for documentation indexing.
TASK:
• For each source directory, identify distinct modules/components
• For each component extract:
- Name (class name, module name, or logical group)
- Type: service | controller | model | util | hook | route | config | middleware | component
- File paths (primary file + related files)
- Exported symbols (public API: classes, functions, types, constants)
- Internal dependencies: what other modules it imports from within the project
- Responsibility: one-line description of what it does
• Group small utility files under parent module when they share domain
MODE: analysis
CONTEXT: @{source_dirs from Phase 1}
EXPECTED: JSON array: [{ name, type, files, symbols, depends_on, responsibility }]
CONSTRAINTS: Focus on business logic | Min threshold: components with 2+ exports or clear domain purpose | Group utilities under parent domain" --tool gemini --mode analysis
```
### 2.2 Generate Component IDs
For each discovered component:
- ID: `tech-{kebab-case-name}` (e.g., `tech-auth-service`, `tech-user-model`)
- Validate uniqueness, append counter on collision
### 2.3 Build Dependency Graph
From `depends_on` fields, construct internal dependency edges:
```
tech-auth-service → tech-user-model
tech-auth-service → tech-jwt-util
tech-order-controller → tech-auth-service
```
## Phase 3: Feature Inference
**Key step: group components into logical features without formal specs.**
### 3.1 Inference Strategy (priority order)
```
Strategy 1 — Directory grouping:
src/auth/** → feat-auth
src/orders/** → feat-orders
src/payments/** → feat-payments
Strategy 2 — Route/endpoint grouping (web apps):
/api/users/* → feat-user-management
/api/orders/* → feat-order-management
Strategy 3 — Dependency clustering:
Components that heavily import each other → same feature
Strategy 4 — Domain keyword extraction:
Class names + file names → domain terms → feature names
```
### 3.2 Gemini Feature Synthesis
```bash
ccw cli -p "PURPOSE: Infer high-level features from discovered code components. This project has no formal specification.
TASK:
Given these discovered components:
{component list from Phase 2: names, types, files, responsibilities, dependencies}
• Group them into logical features (3-10 features for a typical project)
• For each feature:
- name: human-readable (Chinese OK)
- component_ids: which components belong
- description: what the feature does (inferred from code)
- inferred_requirements: what this feature needs to accomplish (1-3 per feature)
- status: 'implemented' (code complete) or 'partial' (incomplete patterns)
- tags: search keywords
• Identify cross-cutting concerns (logging, auth middleware, error handling) as separate features
MODE: analysis
CONTEXT: {component list JSON}
EXPECTED: JSON: { features: [{ name, description, component_ids, inferred_requirements: [{ id, title }], status, tags }] }
CONSTRAINTS: Every component must belong to at least 1 feature | Prefer fewer broad features over many narrow ones" --tool gemini --mode analysis
```
### 3.3 Interactive Feature Review (unless -y)
Present inferred features to user:
- Allow renaming, merging, splitting
- Allow reassigning components between features
- Confirm final feature list
## Phase 4: Implicit Requirement & Architecture Extraction
### 4.1 Inferred Requirements
For each feature, generate lightweight requirement entries from its components:
```
Feature: feat-auth (User Authentication)
→ IREQ-001: "Users can log in with email and password" (from LoginController)
→ IREQ-002: "JWT tokens for session management" (from AuthMiddleware + jwt dep)
→ IREQ-003: "Password reset via email" (from PasswordResetService)
```
**ID Convention**: `IREQ-NNN` — distinguishes inferred from formal `REQ-NNN`.
### 4.2 Inferred Architecture Decisions
Detect patterns from code + dependencies:
```
Express.js + JWT middleware → IADR-001: "REST API with JWT authentication"
Prisma ORM + PostgreSQL → IADR-002: "PostgreSQL via Prisma ORM"
React + Redux → IADR-003: "React frontend with Redux state"
```
**ID Convention**: `IADR-NNN` — distinguishes inferred from formal `ADR-NNN`.
### 4.3 Glossary Generation
Extract domain terms from:
- Class/function names (CamelCase → terms)
- Key business terms in comments and strings
- Framework-specific terminology
Write to `.workflow/.doc-index/glossary.json`.
## Phase 5: Git History Seeds
```bash
git log --oneline --since="3 months ago" --no-merges --format="%H|%s|%ai" | head -30
```
For each significant commit:
- Match changed files to discovered components
- Create action entry with `type: "historical"`
## Phase 6: Assemble doc-index.json
Write the index with code-first markers:
```json
{
"version": "1.0",
"project": "{project-name}",
"build_path": "code-first",
"spec_session": null,
"last_updated": "ISO8601",
"glossary": [...],
"features": [{
"id": "feat-{slug}",
"name": "Feature Name",
"epicId": null,
"status": "implemented|partial",
"docPath": "feature-maps/{slug}.md",
"requirementIds": ["IREQ-NNN"],
"tags": ["tag"]
}],
"requirements": [{
"id": "IREQ-NNN",
"title": "Inferred requirement",
"source": "inferred",
"priority": "inferred",
"sourcePath": null,
"techComponentIds": ["tech-{slug}"],
"featureId": "feat-{slug}"
}],
"technicalComponents": [{
"id": "tech-{slug}",
"name": "ComponentName",
"type": "service|controller|model|...",
"responsibility": "One-line description",
"adrId": "IADR-NNN|null",
"docPath": "tech-registry/{slug}.md",
"codeLocations": [{ "path": "src/...", "symbols": [...] }],
"dependsOn": ["tech-{other}"],
"featureIds": ["feat-{slug}"],
"actionIds": []
}],
"architectureDecisions": [{
"id": "IADR-NNN",
"title": "Inferred decision",
"source": "inferred",
"sourcePath": null,
"componentIds": ["tech-{slug}"]
}],
"actions": [{
"id": "act-{short-hash}",
"description": "Commit message",
"type": "historical",
"status": "historical",
"affectedComponents": ["tech-{slug}"],
"relatedCommit": "full-hash",
"timestamp": "ISO8601"
}]
}
```
## Phase 7: Generate Documents
### 7.1 Feature Maps
For each feature → `feature-maps/{slug}.md`:
- Frontmatter with id, name, status, inferred requirements, components, tags
- Sections: Overview, Inferred Requirements, Technical Components, Dependencies, Change History
- Mark inferred content: `> Inferred from code analysis`
### 7.2 Tech Registry
For each component → `tech-registry/{slug}.md`:
- Frontmatter with id, name, type, code_locations, depends_on
- Sections: Responsibility, Code Locations, Related Features, Dependencies (in/out)
### 7.3 Index Documents
- `feature-maps/_index.md` — feature table
- `tech-registry/_index.md` — component table
- `action-logs/_index.md` — recent git history table
## Phase 8: Validation & Report
```
Scan Report
Project: {name} ({language}/{framework})
Architecture: {pattern}
Source dirs: {N}
Discovered:
Components: {N} ({by type breakdown})
Features: {N} (inferred)
Requirements: {N} (IREQ, inferred)
Architecture Decisions: {N} (IADR, inferred)
Historical Actions: {N} (from git)
Coverage:
Components → Features: {%}
Dependencies mapped: {%}
Recommendations:
- Run /spec-generator to formalize {N} inferred requirements
- {N} components have unclear responsibility — review tech-registry docs
- Use /ddd:plan to start planning tasks with this index
```
## Flags
| Flag | Effect |
|------|--------|
| `-y, --yes` | Auto-confirm all decisions |
| `--from-scratch` | Delete existing index and rebuild |
| `--scope <dir>` | Limit scan to specific directory (e.g., `--scope src/auth`) |
## Upgrade Path: scan → spec
When a scanned project later runs `spec-generator` + `/ddd:index-build`:
- `/ddd:index-build` detects existing code-first index
- Merges: `IREQ-NNN``REQ-NNN`, `IADR-NNN``ADR-NNN` where content overlaps
- Updates `build_path` to `"spec-first"`
- Preserves all `tech-*` and `feat-*` entries (updates links only)
## Integration Points
- **Input from**: Codebase, git history, `project-tech.json`
- **Output to**: `ddd:plan`, `ddd:sync`, `ddd:update`, `ddd:index-build` (upgrade)
- **Standalone**: Can be used independently on any project