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**Table of Contents**

- [Swarm Intelligence Integration Roadmap](#swarm-intelligence-integration-roadmap)
  - [Current State vs. Enhancement Opportunities](#current-state-vs-enhancement-opportunities)
    - [✅ What Exists Today](#-what-exists-today)
    - [🎯 Enhancement Opportunities](#-enhancement-opportunities)
      - [**1. Adaptive Agent Pool Management**](#1-adaptive-agent-pool-management)
      - [**2. Consensus-Based Decision Making**](#2-consensus-based-decision-making)
      - [**3. Learning from Generated Code Quality**](#3-learning-from-generated-code-quality)
      - [**4. Semantic Template Discovery**](#4-semantic-template-discovery)
      - [**5. Autonomous Schema Evolution**](#5-autonomous-schema-evolution)
      - [**6. Real-Time Coordination via Messaging**](#6-real-time-coordination-via-messaging)
      - [**7. Performance Prediction & Optimization**](#7-performance-prediction--optimization)
      - [**8. Multi-Stage Generation Pipeline**](#8-multi-stage-generation-pipeline)
      - [**9. Marketplace Intelligence**](#9-marketplace-intelligence)
      - [**10. Self-Healing Workflows**](#10-self-healing-workflows)
  - [Implementation Priority](#implementation-priority)
    - [Phase 1: Foundation (High Impact, Low Complexity)](#phase-1-foundation-high-impact-low-complexity)
    - [Phase 2: Intelligence (Medium Impact, Medium Complexity)](#phase-2-intelligence-medium-impact-medium-complexity)
    - [Phase 3: Advanced (High Impact, High Complexity)](#phase-3-advanced-high-impact-high-complexity)
  - [Integration Points with Core](#integration-points-with-core)
    - [With ggen-core/Pipeline](#with-ggen-corepipeline)
    - [With ggen-core/Graph](#with-ggen-coregraph)
    - [With ggen-ai/LLMClient](#with-ggen-aillmclient)
  - [Key Design Principles for Enhancement](#key-design-principles-for-enhancement)

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# Swarm Intelligence Integration Roadmap

## Current State vs. Enhancement Opportunities

### ✅ What Exists Today

**Swarm Foundation**:
- Multi-agent architecture with SwarmCoordinator
- SwarmAgent trait with execute/validate/health_check lifecycle
- 6 specialized agents (Code, Template, Graph, Validator, Learning, Event Monitor)
- Core agents: GraphEvolution, Regeneration, Feedback
- Ultrathink 80/20 autonomous system

**LLM Integration**:
- Multi-provider support (OpenAI, Anthropic, Ollama, etc.)
- Specialized generators (Ontology, SPARQL, Template, Refactor, Search)
- Response caching with Moka
- Prompt templating with Tera

**Optimization**:
- Delta-driven projection (change detection, impact analysis)
- Template/Query/LLM response caching
- Parallel processing with rayon
- SPARQL query optimization

### 🎯 Enhancement Opportunities

#### **1. Adaptive Agent Pool Management**
**Where to integrate**: `SwarmCoordinator::coordinate()`
- Auto-scale agent count based on workload
- Dynamically select agents by domain/capability
- Load balancing across agent instances

**Files to enhance**:
- `/crates/ggen-ai/src/swarm/coordinator.rs` - Add adaptive pool management
- `/crates/ggen-ai/src/swarm/agents/mod.rs` - Implement domain routing

#### **2. Consensus-Based Decision Making**
**Where to integrate**: Agent output aggregation
- Multiple agents suggest solutions
- Voting/weighted consensus mechanism
- Conflict resolution strategies

**Files to enhance**:
- `/crates/ggen-ai/src/swarm/orchestration.rs` - Add consensus logic
- `/crates/ggen-ai/src/swarm/events.rs` - Consensus events

#### **3. Learning from Generated Code Quality**
**Where to integrate**: Post-generation feedback loop
- Validate generated code (syntax, style, security)
- Score quality and store in RDF
- Train agents on high-quality patterns

**Files to enhance**:
- `/crates/ggen-ai/src/swarm/agents/code_generator.rs` - Add quality scoring
- `/crates/ggen-ai/src/agents/core/feedback.rs` - Enhance learning
- New: `code_quality_validator.rs`

#### **4. Semantic Template Discovery**
**Where to integrate**: Template selection phase
- Agents query marketplace semantically
- Match RDF schema to template capability
- Recommend optimal template combinations

**Files to enhance**:
- `/crates/ggen-ai/src/generators/natural_search.rs` - Template discovery
- `/crates/ggen-core/src/registry.rs` - Add semantic search
- New: `template_recommender_agent.rs`

#### **5. Autonomous Schema Evolution**
**Where to integrate**: GraphEvolutionAgent
- Detect incomplete patterns in ontology
- Suggest schema extensions
- Auto-generate missing constraints

**Files to enhance**:
- `/crates/ggen-ai/src/agents/core/graph_evolution.rs` - Schema analysis
- New: `schema_analyzer_agent.rs`

#### **6. Real-Time Coordination via Messaging**
**Where to integrate**: Agent communication
- Event-driven agent triggering
- Message queue for agent pipeline
- Streaming responses to CLI

**Files to enhance**:
- `/crates/ggen-ai/src/swarm/events.rs` - Enhanced event system
- `/crates/ggen-ai/src/swarm/coordinator.rs` - Message routing

#### **7. Performance Prediction & Optimization**
**Where to integrate**: Delta analysis
- Profile template generation performance
- Predict cache efficiency
- Auto-optimize SPARQL queries

**Files to enhance**:
- `/crates/ggen-core/src/delta.rs` - Add performance metrics
- New: `performance_predictor_agent.rs`

#### **8. Multi-Stage Generation Pipeline**
**Where to integrate**: Orchestration layer
- Parallel template stages (analysis → design → implementation → testing)
- Agent specialization per stage
- Streaming output as stages complete

**Files to enhance**:
- `/crates/ggen-ai/src/swarm/orchestration.rs` - Pipeline stages
- `/crates/ggen-ai/src/swarm/coordinator.rs` - Stage coordination

#### **9. Marketplace Intelligence**
**Where to integrate**: Package discovery
- Agents analyze compatible templates
- Validate template combinations
- Recommend pack updates

**Files to enhance**:
- `/crates/ggen-core/src/registry.rs` - Agent-driven search
- New: `marketplace_agent.rs`

#### **10. Self-Healing Workflows**
**Where to integrate**: Error recovery
- Detect generation failures
- Agents suggest fixes
- Auto-retry with adjusted parameters

**Files to enhance**:
- `/crates/ggen-ai/src/swarm/coordinator.rs` - Error handling
- New: `recovery_agent.rs`

## Implementation Priority

### Phase 1: Foundation (High Impact, Low Complexity)
1. Consensus-based decision making (5 files)
2. Semantic template discovery (3 files)
3. Learning from code quality (4 files)

### Phase 2: Intelligence (Medium Impact, Medium Complexity)
4. Adaptive agent pool management (4 files)
5. Real-time coordination via messaging (3 files)
6. Autonomous schema evolution (3 files)

### Phase 3: Advanced (High Impact, High Complexity)
7. Multi-stage generation pipeline (5 files)
8. Performance prediction (4 files)
9. Self-healing workflows (4 files)
10. Marketplace intelligence (3 files)

---

## Integration Points with Core

### With ggen-core/Pipeline
```rust
// Current: Single-stage rendering
impl Pipeline {
    pub fn render_file(...) -> Result<Plan>
}

// Enhanced: Multi-agent template selection
impl Pipeline {
    pub async fn render_file_with_agents(...) -> Result<Plan> {
        // Let agents recommend optimal template
        let template = agents.select_template(&graph, &specs).await?;
        // Continue with rendering...
        self.render_file(template_path, vars, dry_run)
    }
}
```

### With ggen-core/Graph
```rust
// Current: Delta analysis only
impl ImpactAnalyzer {
    pub fn analyze(&self, old: &Graph, new: &Graph, ...) -> Result<Vec<TemplateImpact>>
}

// Enhanced: Autonomous improvement suggestions
impl ImpactAnalyzer {
    pub async fn analyze_with_suggestions(&self, ...) -> Result<Analysis> {
        let deltas = self.detect_changes()?;
        let impacts = self.analyze(&old, &new)?;
        // Let agents suggest improvements
        let improvements = agents.suggest_improvements(&self.graph, &deltas).await?;
        Ok(Analysis { impacts, improvements })
    }
}
```

### With ggen-ai/LLMClient
```rust
// Current: Single LLM call
let response = client.complete(prompt).await?;

// Enhanced: Multi-agent validation
let response = client.complete(prompt).await?;
let validated = agents.validate_and_improve(response).await?;
```

---

## Key Design Principles for Enhancement

1. **Composability**: Agents should work independently and in coordination
2. **Determinism**: Results reproducible given same inputs
3. **Observability**: Track agent decisions in RDF (semantic audit trail)
4. **Resilience**: Graceful degradation if agent fails
5. **Parallelism**: Agents execute concurrently where possible
6. **Extensibility**: New agents pluggable via trait implementation
7. **Testability**: Mock agents for unit testing
8. **Performance**: Cache agent outputs for repeated queries
