> ## Documentation Index
> Fetch the complete documentation index at: https://docs.haus25.live/llms.txt
> Use this file to discover all available pages before exploring further.

# Planner Scope

> AI-powered event optimization with specialized agents for titles, descriptions, pricing, scheduling, and banner generation.

The Planner scope provides foundational event optimization services through specialized AI agents. As the entry-level curation service at 3% fee, it focuses on core event enhancement without promotional overhead.

## Core Services

### Event Optimization

**Title Enhancement**: Gemini Flash-powered creative title generation based on category research, trending keywords, and engagement optimization patterns.

**Description Refinement**: Compelling event descriptions that balance informativeness with excitement, incorporating audience targeting and category-specific language.

**Pricing Strategy**: Data-driven ticket and reserve price optimization considering community engagement, category standards, and creator goals.

**Schedule Optimization**: Intelligent timing recommendations based on audience activity patterns, category trends, and optimal engagement windows.

**Visual Content**: AI-generated banner creation using Google Imagen with DALL-E fallback, incorporating event themes and visual appeal optimization.

## Specialized Agents

### Title Agent

**Model**: Gemini 2.5 Flash Lite
**Purpose**: Creative title generation with engagement optimization
**Input**: Event data, category research, trending keywords
**Output**: Enhanced title with alternatives and reasoning

### Description Agent

**Model**: Gemini 2.5 Flash Lite\
**Purpose**: Compelling description creation with audience targeting
**Input**: Event data, category insights, user history
**Output**: Optimized description with target audience analysis

### Pricing Agent

**Model**: Gemini 2.0 Flash Exp
**Purpose**: Numerical optimization for ticket and reserve pricing
**Input**: Event data, market research, category pricing patterns
**Output**: Recommended pricing with participation optimization rationale

### Schedule Agent

**Model**: Gemini 2.0 Flash Exp
**Purpose**: Data-driven timing optimization
**Input**: Event data, audience patterns, category timing analysis
**Output**: Optimal date/time recommendations with timezone considerations

### Banner Agent

**Model**: Google Imagen (primary), DALL-E (fallback)
**Purpose**: Visual content generation with brand consistency
**Input**: Event data, style preferences, category aesthetics
**Output**: AI-generated banner with color palette and alternative versions

## Technical Implementation

### Supervisor Coordination

The PlannerSupervisor coordinates all specialized agents through two-phase execution:

**Phase 1**: Shared context preparation across RAG, Research, Memory, and Blockchain agents
**Phase 2**: Parallel execution of specialized agents with shared research data

### Cost Optimization

**Shared Research**: Single category research call shared across all agents (35% token reduction)
**Model Selection**: Cost-effective model assignment based on task complexity
**Context Filtering**: Agent-specific data extraction to minimize token usage

### Performance Metrics

**Token Usage**: \~3,700 tokens per event
**Estimated Cost**: \$0.065 per optimization
**Processing Time**: 15-30 seconds for complete plan generation
**Success Rate**: 95%+ successful optimizations

## Agent Interactions

### Context Sharing

All specialized agents receive:

* Category research insights (trends, pricing, audience)
* User history context (previous events, preferences)
* Market intelligence (current opportunities, timing)

### Output Integration

Agent outputs are structured into cohesive plan:

* Unified reasoning across recommendations
* Consistent tone and messaging
* Integrated visual and textual elements

## Quality Assurance

### Fallback Mechanisms

Each agent includes graceful degradation:

* **Title Agent**: Falls back to enhanced original title
* **Description Agent**: Provides structured improvement suggestions
* **Pricing Agent**: Uses category averages with safety margins
* **Schedule Agent**: Recommends popular time slots for category
* **Banner Agent**: Falls back to DALL-E if Imagen unavailable

### Validation

All outputs undergo validation:

* Content appropriateness checking
* Length and format compliance
* Brand guideline adherence
* Technical specification validation

## User Experience

### Input Requirements

Minimal user input required:

* Basic event details (title, description, category)
* Duration and rough timing preferences
* Any specific requirements or constraints

### Output Delivery

Comprehensive plan including:

* Enhanced event metadata
* Reasoning for each recommendation
* Alternative options where applicable
* Implementation guidance

### Iteration Support

Users can refine any aspect:

* Provide feedback on specific elements
* Request alternative approaches
* Adjust parameters and regenerate

## Integration Points

### EventFactory Integration

Optimized data flows directly to event creation:

* Enhanced metadata ready for smart contract deployment
* Optimized pricing for TicketKiosk configuration
* Banner assets uploaded to IPFS storage

### Curation Contract

Plan acceptance triggers:

* Curation contract deployment for selected scope
* Fee structure activation (3% for Planner)
* Proxy permissions for ongoing optimization

## Performance Analytics

### Success Metrics

* **Engagement Improvement**: 40% average increase in event interest
* **Pricing Optimization**: 25% improvement in participation rates
* **Title Effectiveness**: 60% higher click-through rates
* **Description Quality**: 50% reduction in user questions

### Cost Efficiency

* **Traditional Copywriting**: \$200-500 per event
* **Planner Scope**: \$0.065 per optimization
* **Time Savings**: 95% reduction in optimization time
* **Quality Consistency**: 100% professional standard output

## Related Documentation

* [Curation Scopes](/curation/scopes/curation-scopes) - Overview of all service levels
* [Shared Agents](/curation/shared-agents) - Foundation agents used by Planner
* [System Overview](/curation/system-overview) - Technical architecture context