# Creative Studio - Comprehensive Implementation Plan

**Platform**: 灵感工坊 (Creative Studio) - AI 创作平台
**Version**: 2.0
**Date**: 2024-01-24
**Status**: Active Development

---

## Executive Summary

This document provides a comprehensive implementation plan for the Creative Studio platform, based on the complete platform specification document. The platform follows a **Skill-centric architecture** where Agents provide fixed workflow frameworks and Skills provide configurable behavioral guidance.

### Current Implementation Status

| Component | Status | Completion |
|-----------|--------|------------|
| **Backend Framework** | ✅ Implemented | 90% |
| **Skills CRUD** | ✅ Implemented | 95% |
| **Agents Viewing** | ✅ Implemented | 80% |
| **Projects CRUD** | ⚠️ Partial | 60% |
| **Memory System** | ❌ Missing | 0% |
| **Review System** | ❌ Missing | 0% |
| **Execution Monitoring** | ⚠️ Basic | 40% |
| **Frontend Pages** | ⚠️ Partial | 50% |
| **Skill Marketplace** | ❌ Missing | 0% |

---

## Architecture Overview

### Core Design Principles

1. **"Agent 固定，Skill 可配"** - Platform maintains Agent framework, users configure Skills
2. **"Skill 指导行为"** - Skill behavior guides are integrated into prompts to guide LLM behavior
3. **"全局上下文 + 记忆系统"** - Global context + memory system ensures multi-episode consistency
4. **"全自动 + 人工审核"** - Full automatic creation with human review

### System Hierarchy

```
Series Project (剧集项目)
    ├── Uses Agent (固定工作流模板)
    │       └── Calls Skills (可配置能力单元)
    │
    ├── Global Context (全局上下文)
    │   ├── World Setting (世界观)
    │   ├── Character Profiles (人物小传)
    │   ├── Scene Settings (场景设定)
    │   └── Overall Outline (整体大纲)
    │
    ├── Memory System (记忆系统)
    │   ├── Event Timeline (事件时间线)
    │   ├── Pending Threads (待收线问题)
    │   ├── Foreshadowing (伏笔追踪)
    │   └── Character States (人物状态)
    │
    └── Episodes (子项目)
        ├── EP01, EP02, ...
        └── Each episode: Structure → Outline → Content → Review → Memory Update
```

---

## Phase 1: Core Foundation (Current - Week 1-2)

### 1.1 Backend Infrastructure ✅ (90% Complete)

**Status**: Implemented
**Location**: `C:\Users\Wolfycz\huijing\creative_studio\backend\`

#### Implemented Components:

- **FastAPI Application** (`app/main.py`)
  - CORS configuration
  - Lifespan management
  - Route registration
  - Health checks

- **Skill Management** (`app/core/skills/skill_manager.py`)
  - Load and parse SKILL.md files
  - Extract behavior guides
  - Cache management
  - Builtin vs User Skills separation
  - CRUD operations for user Skills

- **Data Models** (`app/models/`)
  - `skill.py`: Skill, SkillTool, SkillConfig
  - `project.py`: SeriesProject, Episode, GlobalContext, Memory

- **LLM Integration** (`app/core/llm/glm_client.py`)
  - GLM-4.7 integration
  - `chat_with_skill()` method for Skill-guided generation

- **Series Creation Agent** (`app/core/agents/series_creation_agent.py`)
  - Fixed workflow implementation
  - 5-stage execution: Structure → Outline → Dialogue → Review → Memory
  - Context building
  - Basic retry logic

#### Remaining Tasks:

- [ ] Enhance error handling and logging
- [ ] Add API rate limiting
- [ ] Implement request/response validation
- [ ] Add API versioning strategy
- [ ] Create comprehensive test suite

**API Endpoints Implemented**:

| Endpoint | Method | Status |
|----------|--------|--------|
| `/api/v1/skills/` | GET | ✅ |
| `/api/v1/skills/{id}` | GET | ✅ |
| `/api/v1/skills/` | POST | ✅ |
| `/api/v1/skills/{id}` | PUT | ✅ |
| `/api/v1/skills/{id}` | DELETE | ✅ |
| `/api/v1/skills/{id}/test` | POST | ✅ |
| `/api/v1/projects/` | GET | ✅ |
| `/api/v1/projects/` | POST | ✅ |
| `/api/v1/projects/{id}` | GET | ✅ |
| `/api/v1/projects/{id}/execute` | POST | ✅ |
| `/api/v1/projects/{id}/execute-batch` | POST | ✅ |

---

### 1.2 Frontend Infrastructure ⚠️ (50% Complete)

**Status**: Partially Implemented
**Location**: `C:\Users\Wolfycz\huijing\creative_studio\frontend\`

#### Implemented Pages:

1. **Skill Management** (`src/pages/SkillManagement.tsx`) ✅
   - Skills listing with filtering
   - Builtin vs User Skills distinction
   - Create, Edit, Delete operations
   - Skill testing modal
   - Detail drawer with behavior guide view
   - Search and category filtering
   - Grid/List view toggle

2. **Agent Management** (`src/pages/AgentManagement.tsx`) ✅
   - Read-only Agent viewing
   - Workflow visualization
   - Skill bindings display

3. **Project List** (`src/pages/ProjectList.tsx`) ✅
   - Project listing
   - Status indicators

4. **Project Create** (`src/pages/ProjectCreate.tsx`) ⚠️
   - Basic form
   - Needs enhancement for global context

5. **Execution Monitor** (`src/pages/ExecutionMonitor.tsx`) ⚠️
   - Basic monitoring
   - Needs real-time updates

#### Missing Frontend Components:

- [ ] Global Context Editor
- [ ] Memory System Viewer
- [ ] Review System UI
- [ ] Episode Detail View
- [ ] Skill Configuration Interface
- [ ] Batch Execution Controls
- [ ] Quality Report Viewer
- [ ] Skill Marketplace

---

## Phase 2: Memory System Implementation (Week 3-4)

### 2.1 Backend - Memory System

**Priority**: HIGH
**Complexity**: Medium

#### Data Models to Implement:

```python
# Event Timeline
class TimelineEvent(BaseModel):
    episode: int
    event: str
    timestamp: datetime
    characters_involved: List[str] = []
    importance: str = "medium"  # low, medium, high

# Pending Threads (Foreshadowing)
class PendingThread(BaseModel):
    id: str
    description: str
    introduced_at: int
    importance: str  # high, medium, low
    resolved: bool = False
    resolved_at: Optional[int] = None
    reminder_episode: Optional[int] = None
    status: str = "pending"  # pending,跟进中,已收线

# Character State History
class CharacterStateChange(BaseModel):
    episode: int
    state: str
    change: str
    emotional_impact: Optional[str] = None

# Enhanced Memory System
class EnhancedMemory(BaseModel):
    eventTimeline: List[TimelineEvent] = []
    pendingThreads: List[PendingThread] = []
    characterStates: Dict[str, List[CharacterStateChange]] = {}
    foreshadowing: List[ForeshadowingEvent] = []
    relationships: Dict[str, Dict[str, str]] = {}  # character relationships
```

#### API Endpoints to Create:

| Endpoint | Method | Description |
|----------|--------|-------------|
| `/api/v1/projects/{id}/memory` | GET | Get project memory |
| `/api/v1/projects/{id}/memory/timeline` | GET | Get event timeline |
| `/api/v1/projects/{id}/memory/threads` | GET | Get pending threads |
| `/api/v1/projects/{id}/memory/threads` | POST | Add new thread |
| `/api/v1/projects/{id}/memory/threads/{thread_id}` | PUT | Update thread |
| `/api/v1/projects/{id}/memory/characters` | GET | Get character states |
| `/api/v1/projects/{id}/memory/resolve-thread` | POST | Mark thread as resolved |

#### Memory Manager Implementation:

```python
# app/core/memory/memory_manager.py

class MemoryManager:
    """Manage project memory system"""

    async def extract_events_from_episode(
        self,
        episode_content: str,
        episode_number: int
    ) -> List[TimelineEvent]:
        """Extract key events from completed episode"""
        # Use LLM to identify and extract events
        pass

    async def detect_foreshadowing(
        self,
        episode_content: str,
        episode_number: int
    ) -> List[ForeshadowingEvent]:
        """Detect new foreshadowing in episode"""
        pass

    async def update_character_states(
        self,
        episode_content: str,
        episode_number: int,
        characters: List[str]
    ) -> Dict[str, CharacterStateChange]:
        """Track character state changes"""
        pass

    async def check_consistency(
        self,
        episode_content: str,
        memory: Memory
    ) -> List[ConsistencyIssue]:
        """Check episode consistency with memory"""
        pass

    async def suggest_thread_resolution(
        self,
        thread: PendingThread,
        current_episode: int
    ) -> ResolutionSuggestion:
        """Suggest how to resolve pending threads"""
        pass
```

### 2.2 Frontend - Memory System UI

**Components to Build:**

1. **Memory System Viewer Page** (`src/pages/MemorySystem.tsx`)

```typescript
interface MemorySystemProps {
  projectId: string;
}

// Features:
// - Tabbed interface: Timeline | Threads | Characters | Foreshadowing
// - Timeline: Chronological event list with episode markers
// - Threads: Cards showing pending threads with urgency indicators
// - Characters: State history for each character
// - Visual relationship graph
```

2. **Timeline Component**

```typescript
// Features:
// - Vertical timeline visualization
// - Episode markers
// - Event cards with character avatars
// - Importance color-coding
// - Filter by character/episode/importance
// - Click to view details
```

3. **Pending Threads Component**

```typescript
// Features:
// - Thread cards with:
//   - Description
//   - Introduced episode
//   - Importance level (High/Medium/Low)
//   - Status (Pending/In Progress/Resolved)
//   - Suggested resolution episode
// - Manual add/edit thread
// - Mark as resolved
// - Set reminder episode
// - Filter by status/importance
```

4. **Character States Component**

```typescript
// Features:
// - Character list with current states
// - State history timeline per character
// - State change indicators
// - Relationship visualization
// - Emotional state tracking
```

---

## Phase 3: Review System Implementation (Week 5-6)

### 3.1 Backend - Review System

**Priority**: HIGH
**Complexity**: High

#### Review Configuration Model:

```python
class ReviewConfig(BaseModel):
    """Review configuration - customizable by users"""

    # Enabled review Skills
    enabled_review_skills: List[str] = [
        "consistency_checker",
        "dialogue_quality_checker",
        "plot_logic_checker"
    ]

    # Overall strictness
    overall_strictness: str = "medium"  # loose, medium, strict

    # Dimension-specific settings
    dimension_settings: Dict[str, DimensionConfig] = {}

    # Custom rules
    custom_rules: List[CustomRule] = []

    # Presets
    preset_name: Optional[str] = None

class DimensionConfig(BaseModel):
    enabled: bool = True
    strictness: float = 0.5  # 0.0 to 1.0
    custom_rules: List[CustomRule] = []

class CustomRule(BaseModel):
    id: str
    name: str
    description: str
    trigger_condition: str
    severity: str  # low, medium, high
    enabled: bool = True
```

#### Review Result Model:

```python
class ReviewResult(BaseModel):
    episode_id: str
    episode_number: int

    # Overall score
    overall_score: float
    passed: bool

    # Dimension scores
    dimension_scores: Dict[str, float] = {}

    # Issues found
    issues: List[ReviewIssue] = []

    # New foreshadowing detected
    new_foreshadowing: List[ForeshadowingEvent] = []

    # Resolved threads
    resolved_threads: List[str] = []

class ReviewIssue(BaseModel):
    id: str
    type: str
    dimension: str
    severity: str  # low, medium, high
    location: Location
    description: str
    original_text: Optional[str] = None
    suggestion: str
    auto_fix_available: bool = False

class Location(BaseModel):
    episode: int
    scene: int
    line: Optional[int] = None
```

#### Review Manager Implementation:

```python
# app/core/review/review_manager.py

class ReviewManager:
    """Manage review process"""

    async def review_episode(
        self,
        episode: Episode,
        project: SeriesProject,
        config: ReviewConfig
    ) -> ReviewResult:
        """Execute full review process"""

        # Run each enabled review Skill
        dimension_results = []
        for skill_id in config.enabled_review_skills:
            result = await self._run_review_skill(
                skill_id, episode, project, config
            )
            dimension_results.append(result)

        # Aggregate results
        review_result = self._aggregate_results(dimension_results)

        # Check custom rules
        custom_issues = await self._check_custom_rules(
            episode, config.custom_rules
        )
        review_result.issues.extend(custom_issues)

        # Determine pass/fail
        threshold = config.dimension_settings.get("threshold", 85)
        review_result.passed = review_result.overall_score >= threshold

        return review_result

    async def _run_review_skill(
        self,
        skill_id: str,
        episode: Episode,
        project: SeriesProject,
        config: ReviewConfig
    ) -> DimensionResult:
        """Run a single review Skill"""
        skill = await skill_manager.load_skill(skill_id)

        # Build review prompt
        prompt = self._build_review_prompt(
            skill, episode, project, config
        )

        # Execute with Skill behavior guide
        response = await glm_client.chat_with_skill(
            skill_behavior=skill.behavior_guide,
            user_input=prompt,
            context={
                "episode_content": episode.content,
                "global_context": project.globalContext,
                "memory": project.memory
            },
            temperature=0.3
        )

        # Parse response
        return self._parse_review_response(response, skill_id)

    def _aggregate_results(
        self,
        dimension_results: List[DimensionResult]
    ) -> ReviewResult:
        """Aggregate dimension results into overall score"""
        # Weighted average based on dimension settings
        pass
```

#### API Endpoints:

| Endpoint | Method | Description |
|----------|--------|-------------|
| `/api/v1/projects/{id}/review-config` | GET | Get review config |
| `/api/v1/projects/{id}/review-config` | PUT | Update review config |
| `/api/v1/projects/{id}/review-presets` | GET | List preset configs |
| `/api/v1/projects/{id}/episodes/{ep_num}/review` | POST | Run review |
| `/api/v1/review/dimensions` | GET | List available dimensions |
| `/api/v1/review/custom-rules` | POST | Add custom rule |
| `/api/v1/review/custom-rules/{id}` | DELETE | Delete custom rule |

### 3.2 Frontend - Review System UI

**Components to Build:**

1. **Review Configuration Page** (`src/pages/ReviewConfig.tsx`)

```typescript
// Features:
// - Dimension selection with toggles
// - Strictness sliders per dimension
// - Custom rules builder
// - Preset selection (Draft/Standard/Strict)
// - Save/load presets
// - Preview configuration impact
```

2. **Dimension Configuration Component**

```typescript
// Features:
// - Enable/disable dimension
// - Strictness slider (0-100)
// - Weight adjustment
// - Custom rules for dimension
// - Examples of what's checked
```

3. **Custom Rule Builder**

```typescript
// Features:
// - Rule name and description
// - Trigger condition builder (natural language)
// - Severity selector
// - Test rule with sample content
// - Rule templates
```

4. **Review Results Viewer** (`src/pages/ReviewResults.tsx`)

```typescript
// Features:
// - Overall score display with gauge
// - Dimension score breakdown (bar chart)
// - Issues list grouped by severity
// - Issue detail cards:
//   - Location link
//   - Original text
//   - Suggestion
//   - Auto-fix button (if available)
//   - Ignore option
// - Accept/Reject decisions
// - Export report
```

5. **Review Dashboard**

```typescript
// Features:
// - Batch review summary
// - Pass/fail statistics
// - Common issues
// - Trend analysis
// - Quality metrics over time
```

---

## Phase 4: Advanced Execution Features (Week 7-8)

### 4.1 Backend - Enhanced Execution

**Priority**: MEDIUM
**Complexity**: High

#### Features to Implement:

1. **Batch Execution Mode**

```python
# app/core/execution/batch_executor.py

class BatchExecutor:
    """Execute episodes in batches with user review between"""

    async def execute_batch(
        self,
        project: SeriesProject,
        start_episode: int,
        end_episode: int,
        batch_config: BatchConfig
    ) -> BatchResult:
        """Execute a batch of episodes"""

        results = []
        for ep_num in range(start_episode, end_episode + 1):
            # Execute episode
            episode = await agent.execute_episode(
                project, ep_num
            )

            # Run review
            review = await review_manager.review_episode(
                episode, project, project.review_config
            )

            # Check if meets quality threshold
            if review.overall_score < batch_config.quality_threshold:
                # Auto-retry or mark for review
                if episode.retry_count < batch_config.max_retries:
                    episode = await self._retry_episode(
                        project, ep_num, review
                    )
                else:
                    episode.status = "needs-review"

            results.append(episode)

        # Wait for user approval before next batch
        return BatchResult(
            episodes=results,
            needs_review=[ep for ep in results if ep.status == "needs-review"],
            batch_summary=self._generate_summary(results)
        )
```

2. **Real-time Progress Streaming**

```python
# Use WebSocket or Server-Sent Events for real-time updates

@app.websocket("/ws/projects/{project_id}/execute")
async def execute_episode_stream(
    websocket: WebSocket,
    project_id: str,
    episode_number: int
):
    """Stream execution progress in real-time"""

    await websocket.accept()

    # Send stage updates
    for stage in agent.execution_stages:
        await websocket.send_json({
            "type": "stage_start",
            "stage": stage.name,
            "message": f"Starting {stage.display_name}..."
        })

        result = await stage.execute()

        await websocket.send_json({
            "type": "stage_complete",
            "stage": stage.name,
            "result": result
        })

    await websocket.send_json({
        "type": "episode_complete",
        "episode": episode_result
    })
```

3. **Auto-retry with Feedback**

```python
class RetryManager:
    """Manage automatic retry logic"""

    async def should_retry(
        self,
        episode: Episode,
        review: ReviewResult
    ) -> bool:
        """Determine if episode should be retried"""

        config = episode.project.autoRetryConfig

        # Check retry count
        if episode.retry_count >= config.maxRetries:
            return False

        # Check score threshold
        if review.overall_score >= config.qualityThreshold:
            return False

        # Check if issues are fixable
        fixable_issues = [
            issue for issue in review.issues
            if issue.auto_fix_available or issue.severity != "high"
        ]

        return len(fixable_issues) > 0

    async def retry_episode(
        self,
        episode: Episode,
        review: ReviewResult
    ) -> Episode:
        """Retry episode generation with review feedback"""

        # Build retry context
        retry_context = {
            "attempt": episode.retry_count + 1,
            "previous_result": episode.content,
            "review_feedback": self._build_feedback(review.issues),
            "suggestions": [issue.suggestion for issue in review.issues]
        }

        # Re-execute with feedback
        new_episode = await agent.execute_episode(
            episode.project,
            episode.number,
            retry_context=retry_context
        )

        new_episode.retry_count = episode.retry_count + 1
        return new_episode
```

#### API Endpoints:

| Endpoint | Method | Description |
|----------|--------|-------------|
| `/api/v1/projects/{id}/execute-batch` | POST | Execute batch |
| `/api/v1/projects/{id}/execute-auto` | POST | Full auto execution |
| `/api/v1/projects/{id}/execution-status` | GET | Get execution status |
| `/api/v1/projects/{id}/stop-execution` | POST | Stop execution |
| `/ws/projects/{id}/execute` | WebSocket | Real-time execution stream |

### 4.2 Frontend - Enhanced Execution UI

**Components to Build:**

1. **Batch Execution Config** (`src/pages/BatchExecution.tsx`)

```typescript
// Features:
// - Batch size selector
// - Episode range picker
// - Per-episode configuration:
//   - Duration target
//   - Style preset
//   - Focus areas
// - Quality threshold setting
// - Auto-retry configuration
// - Preview batch plan
```

2. **Real-time Execution Monitor** (Enhanced)

```typescript
// Features:
// - Live progress bar
// - Current stage display
// - Real-time content preview (streaming)
// - Stage-by-stage logs
// - Pause/Resume/Stop controls
// - Time estimation
// - Quality metrics live update
```

3. **Batch Review Dashboard**

```typescript
// Features:
// - Batch completion summary
// - Episode cards with status
// - Quality score comparison
// - Issues overview
// - Batch approval decision:
//   - Accept all
//   - Review issues
//   - Retry failed
//   - Regenerate batch
// - Next batch configuration
```

4. **Quality Report Viewer** (`src/pages/QualityReport.tsx`)

```typescript
// Features:
// - Overall quality metrics
// - Dimension score charts
// - Trend analysis across episodes
// - Issue statistics
// - Comparison to thresholds
// - Improvement suggestions
// - Export to PDF/Excel
```

---

## Phase 5: Skill Marketplace (Week 9-10)

### 5.1 Backend - Marketplace

**Priority**: MEDIUM
**Complexity**: Medium

#### Data Models:

```python
class MarketplaceSkill(BaseModel):
    """Skill in marketplace"""

    # Base skill data
    skill: Skill

    # Marketplace-specific
    author_id: str
    author_name: str
    published_at: datetime
    downloads: int = 0
    rating: float = 0.0
    rating_count: int = 0

    # Categorization
    category: str
    tags: List[str]

    # Usage stats
    usage_count: int = 0
    success_rate: float = 0.0

    # Versioning
    version: str
    changelog: List[str] = []
    parent_skill_id: Optional[str] = None  # If forked

class SkillReview(BaseModel):
    skill_id: str
    user_id: str
    rating: int  # 1-5
    comment: str
    created_at: datetime
    usage_context: Optional[str] = None
```

#### Marketplace Manager:

```python
# app/core/marketplace/marketplace_manager.py

class MarketplaceManager:
    """Manage Skill marketplace"""

    async def publish_skill(
        self,
        skill_id: str,
        user_id: str,
        marketplace_data: MarketplaceMetadata
    ) -> MarketplaceSkill:
        """Publish user skill to marketplace"""

        # Validate skill
        skill = await skill_manager.load_skill(skill_id)
        if not skill or skill.type != "user":
            raise ValueError("Only user skills can be published")

        # Create marketplace listing
        marketplace_skill = MarketplaceSkill(
            skill=skill,
            author_id=user_id,
            **marketplace_data.dict()
        )

        # Save to marketplace storage
        await self.marketplace_repo.create(marketplace_skill)

        return marketplace_skill

    async def fork_skill(
        self,
        original_skill_id: str,
        user_id: str,
        modifications: SkillUpdate
    ) -> Skill:
        """Create a fork of existing skill"""

        original = await self.get_marketplace_skill(original_skill_id)

        # Create new user skill
        new_skill_id = f"{original_skill_id}-fork-{uuid.uuid4().hex[:8]}"
        new_skill = await skill_manager.create_user_skill(
            SkillCreate(
                id=new_skill_id,
                name=f"{original.skill.name} (Fork)",
                content=original.skill.behavior_guide,
                category=original.category,
                tags=original.tags
            )
        )

        # Track fork relationship
        new_skill.parent_skill_id = original_skill_id

        return new_skill

    async def rate_skill(
        self,
        skill_id: str,
        user_id: str,
        rating: int,
        comment: str
    ) -> SkillReview:
        """Rate and review a skill"""
        pass

    async def get_recommendations(
        self,
        project_type: str,
        user_history: List[str]
    ) -> List[MarketplaceSkill]:
        """Get recommended skills based on context"""
        pass
```

#### API Endpoints:

| Endpoint | Method | Description |
|----------|--------|-------------|
| `/api/v1/marketplace/skills` | GET | Browse marketplace |
| `/api/v1/marketplace/skills/{id}` | GET | Get skill details |
| `/api/v1/marketplace/skills/{id}/install` | POST | Install skill |
| `/api/v1/marketplace/skills/publish` | POST | Publish skill |
| `/api/v1/marketplace/skills/{id}/fork` | POST | Fork skill |
| `/api/v1/marketplace/skills/{id}/rate` | POST | Rate skill |
| `/api/v1/marketplace/skills/{id}/reviews` | GET | Get reviews |
| `/api/v1/marketplace/recommendations` | GET | Get recommendations |
| `/api/v1/marketplace/categories` | GET | Get categories |

### 5.2 Frontend - Marketplace UI

**Components to Build:**

1. **Marketplace Home** (`src/pages/Marketplace.tsx`)

```typescript
// Features:
// - Search bar with filters
// - Category browsing
// - Featured skills carousel
// - Popular skills grid
// - New arrivals
// - User's custom skills section
// - Skill cards with:
//   - Name, description
//   - Rating, downloads
//   - Author, category
//   - Install/Fork buttons
```

2. **Skill Detail Page** (`src/pages/MarketplaceSkillDetail.tsx`)

```typescript
// Features:
// - Full skill description
// - Behavior guide preview
// - Configuration parameters
// - Usage examples
// - Reviews section
// - Rating distribution
// - Related skills
// - Version history
// - Install/Fork actions
```

3. **Skill Publisher** (`src/pages/PublishSkill.tsx`)

```typescript
// Features:
// - Skill selection
// - Marketplace metadata:
//   - Display name
//   - Description
//   - Category, tags
//   - Screenshots
//   - Examples
// - Version notes
// - Pricing (if applicable)
// - Preview listing
// - Publish action
```

4. **My Skills Dashboard**

```typescript
// Features:
// - Published skills list
// - Stats: downloads, ratings, usage
// - Fork management
// - Review responses
// - Version management
// - Skill analytics
```

---

## Phase 6: Advanced Features (Week 11-12)

### 6.1 Global Context Editor

**Backend**:
- Enhanced CRUD for GlobalContext
- Version history
- Conflict detection
- Template system

**Frontend**:
- Rich text editors for each section
- Visual character relationship editor
- Scene builder with previews
- Import/export templates
- Version comparison

### 6.2 Skill Configuration Interface

**Backend**:
- Parameter schema validation
- Configuration templates
- Preset management

**Frontend**:
- Visual parameter editors:
  - Sliders for numeric values
  - Selects for options
  - Toggles for booleans
  - Rich text for guides
- Real-time preview
- Configuration save/load
- Preset application

### 6.3 Export System

**Backend**:
- Multi-format export:
  - Markdown
  - PDF
  - Word (DOCX)
  - Final Draft
  - Custom templates

**Frontend**:
- Export configuration
- Template selection
- Format options
- Preview before export
- Batch export

### 6.4 Analytics Dashboard

**Backend**:
- Usage metrics collection
- Performance tracking
- Quality analytics
- Storage optimization

**Frontend**:
- Usage statistics
- Creation speed charts
- Quality trends
- Storage usage
- API rate limits

---

## Data Models Summary

### Core Models Status

| Model | Status | Fields | Completeness |
|-------|--------|--------|--------------|
| **Skill** | ✅ | 15 fields | 95% |
| **SkillTool** | ✅ | 4 fields | 100% |
| **SkillConfig** | ✅ | 3 fields | 90% |
| **SeriesProject** | ⚠️ | 12 fields | 70% |
| **GlobalContext** | ⚠️ | 5 fields | 60% |
| **CharacterProfile** | ⚠️ | 7 fields | 70% |
| **SceneSetting** | ⚠️ | 3 fields | 80% |
| **Memory** | ❌ | 4 fields | 0% |
| **Episode** | ⚠️ | 12 fields | 70% |
| **EpisodeIssue** | ✅ | 4 fields | 100% |
| **ReviewConfig** | ❌ | TBD | 0% |
| **ReviewResult** | ❌ | TBD | 0% |
| **MarketplaceSkill** | ❌ | TBD | 0% |

---

## API Endpoints Summary

### Implemented (13 endpoints)

```
Skills:
✅ GET    /api/v1/skills/
✅ GET    /api/v1/skills/{id}
✅ POST   /api/v1/skills/
✅ PUT    /api/v1/skills/{id}
✅ DELETE /api/v1/skills/{id}
✅ POST   /api/v1/skills/{id}/test
✅ GET    /api/v1/skills/categories/list

Projects:
✅ GET    /api/v1/projects/
✅ POST   /api/v1/projects/
✅ GET    /api/v1/projects/{id}
✅ PUT    /api/v1/projects/{id}
✅ DELETE /api/v1/projects/{id}
✅ GET    /api/v1/projects/{id}/episodes
✅ GET    /api/v1/projects/{id}/episodes/{ep_num}
✅ POST   /api/v1/projects/{id}/execute
✅ POST   /api/v1/projects/{id}/execute-batch
✅ GET    /api/v1/projects/{id}/memory
```

### To Implement (40+ endpoints)

```
Memory System:
❌ GET    /api/v1/projects/{id}/memory/timeline
❌ POST   /api/v1/projects/{id}/memory/threads
❌ PUT    /api/v1/projects/{id}/memory/threads/{thread_id}
❌ POST   /api/v1/projects/{id}/memory/resolve-thread
❌ GET    /api/v1/projects/{id}/memory/characters

Review System:
❌ GET    /api/v1/projects/{id}/review-config
❌ PUT    /api/v1/projects/{id}/review-config
❌ GET    /api/v1/projects/{id}/review-presets
❌ POST   /api/v1/projects/{id}/episodes/{ep_num}/review
❌ GET    /api/v1/review/dimensions
❌ POST   /api/v1/review/custom-rules
❌ DELETE /api/v1/review/custom-rules/{id}

Execution:
❌ POST   /api/v1/projects/{id}/execute-auto
❌ GET    /api/v1/projects/{id}/execution-status
❌ POST   /api/v1/projects/{id}/stop-execution
❌ WS     /ws/projects/{id}/execute

Marketplace:
❌ GET    /api/v1/marketplace/skills
❌ GET    /api/v1/marketplace/skills/{id}
❌ POST   /api/v1/marketplace/skills/{id}/install
❌ POST   /api/v1/marketplace/skills/publish
❌ POST   /api/v1/marketplace/skills/{id}/fork
❌ POST   /api/v1/marketplace/skills/{id}/rate
❌ GET    /api/v1/marketplace/skills/{id}/reviews
❌ GET    /api/v1/marketplace/recommendations
❌ GET    /api/v1/marketplace/categories

Export:
❌ POST   /api/v1/projects/{id}/export
❌ GET    /api/v1/projects/{id}/export/{export_id}

Analytics:
❌ GET    /api/v1/analytics/usage
❌ GET    /api/v1/analytics/performance
❌ GET    /api/v1/analytics/quality
```

---

## Frontend Components Summary

### Implemented (4 pages)

- ✅ SkillManagement - Complete
- ✅ AgentManagement - Read-only
- ✅ ProjectList - Basic
- ⚠️ ProjectCreate - Basic
- ⚠️ ExecutionMonitor - Basic
- ✅ HomePage - Basic

### To Build (15+ components)

**Core Pages:**
- ❌ GlobalContextEditor
- ❌ MemorySystemViewer
- ❌ ReviewConfig
- ❌ ReviewResults
- ❌ EpisodeDetail
- ❌ BatchExecution
- ❌ QualityReport
- ❌ Marketplace
- ❌ MarketplaceSkillDetail
- ❌ PublishSkill
- ❌ MySkills
- ❌ ExportPage
- ❌ AnalyticsDashboard
- ❌ Settings

**Shared Components:**
- ❌ TimelineViewer
- ❌ ThreadTracker
- ❌ CharacterStateViewer
- ❌ RelationshipGraph
- ❌ DimensionConfig
- ❌ CustomRuleBuilder
- ❌ RealTimeMonitor
- ❌ QualityGauge
- ❌ SkillCard
- ❌ EpisodeCard

---

## Implementation Priority Matrix

### High Priority (Must Have)

| Feature | Complexity | Impact | Timeline |
|---------|-----------|--------|----------|
| Memory System | Medium | High | Week 3-4 |
| Review System | High | High | Week 5-6 |
| Enhanced Execution | Medium | High | Week 7-8 |
| Global Context Editor | Medium | High | Week 6 |
| Episode Detail View | Low | High | Week 5 |

### Medium Priority (Should Have)

| Feature | Complexity | Impact | Timeline |
|---------|-----------|--------|----------|
| Skill Marketplace | Medium | Medium | Week 9-10 |
| Batch Execution UI | Medium | Medium | Week 8 |
| Quality Reports | Low | Medium | Week 8 |
| Export System | Medium | Medium | Week 11 |
| Analytics | Low | Medium | Week 12 |

### Low Priority (Nice to Have)

| Feature | Complexity | Impact | Timeline |
|---------|-----------|--------|----------|
| Skill Recommendations | High | Low | Week 10 |
| Custom Themes | Low | Low | Week 12 |
| Team Collaboration | High | Low | Post-MVP |
| API Platform | High | Low | Post-MVP |

---

## Technical Debt & Refactoring

### Current Issues

1. **Memory System**: Not implemented - placeholder only
2. **Review System**: Basic consistency check only
3. **Data Persistence**: In-memory only, needs database
4. **Error Handling**: Basic, needs comprehensive coverage
5. **Testing**: No test coverage
6. **Documentation**: Incomplete
7. **Frontend State Management**: Basic, needs optimization

### Refactoring Priorities

1. **Week 3-4**: Add database persistence (PostgreSQL/MongoDB)
2. **Week 5-6**: Implement comprehensive error handling
3. **Week 7-8**: Add unit and integration tests
4. **Week 9-10**: Performance optimization
5. **Week 11-12**: Security audit and hardening

---

## Development Guidelines

### Backend Development

1. **Follow FastAPI best practices**
   - Use async/await throughout
   - Implement proper dependency injection
   - Use Pydantic for validation
   - Add comprehensive error handling

2. **Code Organization**
   ```
   backend/
   ├── app/
   │   ├── api/v1/          # API routes
   │   ├── core/            # Core business logic
   │   │   ├── agents/      # Agent implementations
   │   │   ├── skills/      # Skill management
   │   │   ├── memory/      # Memory system
   │   │   ├── review/      # Review system
   │   │   └── execution/   # Execution engine
   │   ├── models/          # Pydantic models
   │   ├── db/              # Database repositories
   │   └── utils/           # Utilities
   └── tests/               # Test suite
   ```

3. **API Design Principles**
   - RESTful conventions
   - Consistent response formats
   - Proper HTTP status codes
   - Comprehensive OpenAPI docs

### Frontend Development

1. **Follow React best practices**
   - Functional components with hooks
   - TypeScript for type safety
   - Ant Design for UI components
   - Proper state management

2. **Code Organization**
   ```
   frontend/
   ├── src/
   │   ├── pages/           # Page components
   │   ├── components/      # Reusable components
   │   ├── services/        # API services
   │   ├── stores/          # State management
   │   ├── types/           # TypeScript types
   │   └── utils/           # Utilities
   └── tests/               # Test suite
   ```

3. **UI/UX Principles**
   - Responsive design
   - Loading states
   - Error handling
   - User feedback
   - Accessibility

---

## Testing Strategy

### Backend Testing

1. **Unit Tests** (Target: 80% coverage)
   - Model validation
   - Business logic
   - Utility functions

2. **Integration Tests**
   - API endpoints
   - Database operations
   - External service calls

3. **End-to-End Tests**
   - Complete workflows
   - Multi-step operations
   - Error scenarios

### Frontend Testing

1. **Component Tests**
   - Individual components
   - User interactions
   - State changes

2. **Integration Tests**
   - Page flows
   - API integration
   - State management

3. **E2E Tests**
   - User journeys
   - Critical paths
   - Cross-browser testing

---

## Deployment Strategy

### Development Environment

- Backend: FastAPI with uvicorn
- Frontend: Vite dev server
- Database: SQLite (local), PostgreSQL (staging)
- Hot reload enabled

### Staging Environment

- Docker containerization
- PostgreSQL database
- Redis for caching
- Load testing

### Production Environment

- Kubernetes deployment
- Horizontal scaling
- Database replication
- CDN for static assets
- Monitoring and logging

---

## Success Metrics

### Technical Metrics

- API Response Time: < 500ms (p95)
- Frontend Load Time: < 2s
- Test Coverage: > 80%
- Uptime: > 99.9%
- Error Rate: < 0.1%

### User Metrics

- Project Creation Success: > 95%
- Episode Generation Quality: > 85%
- User Satisfaction: > 4.5/5
- Daily Active Users: Track growth
- Feature Adoption: Track usage

---

## Risk Assessment

### High Risk Items

1. **LLM API Stability**
   - Mitigation: Implement retry logic, fallback models
   - Priority: High

2. **Data Consistency**
   - Mitigation: Comprehensive review system
   - Priority: High

3. **Performance at Scale**
   - Mitigation: Caching, async processing
   - Priority: Medium

4. **User Experience Complexity**
   - Mitigation: Intuitive UI, onboarding
   - Priority: Medium

### Medium Risk Items

1. **Third-party Dependencies**
   - Mitigation: Version pinning, regular updates
   - Priority: Medium

2. **Security Vulnerabilities**
   - Mitigation: Regular audits, penetration testing
   - Priority: High

---

## Next Steps (Immediate Actions)

### Week 1-2: Foundation
- [ ] Set up PostgreSQL database
- [ ] Implement data persistence layer
- [ ] Add comprehensive error handling
- [ ] Set up testing framework
- [ ] Create development documentation

### Week 3-4: Memory System
- [ ] Implement MemoryManager
- [ ] Create memory API endpoints
- [ ] Build MemorySystemViewer UI
- [ ] Add memory extraction from episodes
- [ ] Test memory consistency

### Week 5-6: Review System
- [ ] Implement ReviewManager
- [ ] Create review API endpoints
- [ ] Build ReviewConfig UI
- [ ] Build ReviewResults UI
- [ ] Add custom rule builder
- [ ] Test review accuracy

---

## Conclusion

This implementation plan provides a comprehensive roadmap for building the Creative Studio platform. The key focus areas are:

1. **Memory System**: Ensure multi-episode consistency
2. **Review System**: Maintain quality standards
3. **Enhanced Execution**: Provide flexible creation modes
4. **Skill Marketplace**: Enable skill sharing
5. **User Experience**: Intuitive, powerful interface

The current implementation has a solid foundation with Skills CRUD, basic Agent framework, and project management. The next phases focus on adding the missing critical features while maintaining code quality and user experience.

**Estimated Total Timeline**: 12 weeks for full MVP
**Team Size**: 2-3 developers recommended
**Budget**: Consider API costs, infrastructure, and development resources

---

**Document Version**: 1.0
**Last Updated**: 2024-01-24
**Next Review**: 2024-02-01