# TreeQuest Multi-LLM Parallel Deployment Strategy

**Shortcut:** `/TMLPD`

**Description:** Deploy multiple TreeQuest AI agents in parallel using multiple LLM providers for complex, multi-phase development tasks. This skill orchestrates parallel execution across different AI models to maximize throughput, leverage diverse capabilities, and accelerate project completion.

---

## Overview

This strategy enables parallel deployment of TreeQuest agents across multiple LLM providers simultaneously, each handling specialized aspects of a project. By leveraging the strengths of different AI models (e.g., Claude for reasoning, GPT-4 for code generation, Gemini for research), we can:

- **Accelerate Development:** Execute multiple independent tasks in parallel
- **Optimize Cost-Performance:** Route tasks to the most cost-effective suitable model
- **Leverage Specialized Capabilities:** Use models for their strengths (vision, reasoning, coding, research)
- **Ensure Redundancy:** Run critical tasks on multiple models for verification

---

## Prerequisites

### Required Setup

1. **TreeQuest CLI Installed:**
   ```bash
   # Check installation
   treequest status

   # If not installed
   pip install treequest-ai
   ```

2. **Multiple API Keys Configured:**
   ```bash
   # View current configuration
   treequest config --show

   # Edit configuration to add providers
   # File: ~/.config/treequest/config.yaml
   ```

3. **Minimum Providers Recommended:**
   - **Anthropic** (Claude Sonnet/Opus) - Complex reasoning and architecture
   - **OpenAI** (GPT-4 Turbo) - Code generation and debugging
   - **Google** (Gemini Pro) - Research and documentation
   - **Groq/Cerebras** (Llama-based) - Fast execution for simple tasks

---

## Execution Modes

### Mode 1: Task-Category Parallelization
Split different task categories across specialized models.

**Best for:** Projects with clearly separated domains (frontend, backend, testing, docs)

```yaml
Strategy:
  - Frontend Development → claude-sonnet-4 (visual/UI focus)
  - Backend API → gpt-4-turbo (code efficiency)
  - Testing Suite → gemini-2.0-flash (test coverage)
  - Documentation → perplexity-llama-3.1 (research-backed)
```

### Mode 2: Phased Parallel Execution
Execute project phases in parallel across models.

**Best for:** Multi-phase projects with dependencies between phases

```yaml
Strategy:
  - Phase 1 (Architecture) → claude-opus-4 (all providers)
  - Phase 2 (Core Features) → Split across 3 providers
  - Phase 3 (Testing & Polish) → gpt-4o + gemini-2.0-flash
  - Phase 4 (Documentation) → perplexity-llama-3.1-sonar
```

### Mode 3: Redundancy & Verification
Run critical tasks on multiple models for consensus.

**Best for:** Critical code, security fixes, production deployments

```yaml
Strategy:
  - Task 1 (Security Fix) → claude-opus-4 + gpt-4o (parallel)
  - Task 2 (Core Logic) → claude-sonnet-4 + gemini-2.5-pro
  - Compare results → Merge best solutions
```

---

## Quick Start Commands

### 1. System Health Check
```bash
# Test all providers
treequest test

# Check working providers
treequest status

# List available providers
treequest providers
```

### 2. Parallel Deployment - Category Mode
```bash
# Deploy 4 parallel agents for different categories
treequest-parallel \
  --agents=4 \
  --mode=category \
  --config=tmlpd-category.yaml
```

### 3. Parallel Deployment - Phase Mode
```bash
# Deploy phases across multiple models
treequest-parallel \
  --agents=6 \
  --mode=phase \
  --config=tmlpd-phase.yaml
```

### 4. Verification Mode
```bash
# Run task on 3 models for verification
treequest-parallel \
  --agents=3 \
  --mode=verification \
  --task="Implement authentication system"
```

---

## Configuration Files

### tmlpd-category.yaml
```yaml
deployment:
  name: "TMLPD Category Parallelization"
  agents:
    - id: "frontend-agent"
      provider: "anthropic"
      model: "claude-sonnet-4-20250514"
      focus: "UI components, styling, animations"
      tasks: ["task-frontend-*"]

    - id: "backend-agent"
      provider: "openai"
      model: "gpt-4-turbo"
      focus: "API endpoints, database, business logic"
      tasks: ["task-backend-*"]

    - id: "testing-agent"
      provider: "google"
      model: "gemini-2.0-flash-exp"
      focus: "Unit tests, integration tests, e2e tests"
      tasks: ["task-testing-*"]

    - id: "docs-agent"
      provider: "perplexity"
      model: "llama-3.1-sonar-large-128k-online"
      focus: "Documentation, README files, API docs"
      tasks: ["task-docs-*"]

  coordination:
    sync_interval: 300  # 5 minutes
    conflict_resolution: "timestamp"
    merge_strategy: "git-merge"

  output:
    directory: ".tmlpd-output"
    logs: "tmlpd-logs.json"
    metrics: "tmlpd-metrics.json"
```

### tmlpd-phase.yaml
```yaml
deployment:
  name: "TMLPD Phase Parallelization"
  agents:
    - id: "phase1-architect"
      provider: "anthropic"
      model: "claude-opus-4"
      phase: 1
      focus: "Architecture design, project structure"
      tasks: ["phase-1-*"]

    - id: "phase2-feature-1"
      provider: "anthropic"
      model: "claude-sonnet-4"
      phase: 2
      focus: "Core features implementation"
      tasks: ["phase-2-core-*"]

    - id: "phase2-feature-2"
      provider: "openai"
      model: "gpt-4-turbo"
      phase: 2
      focus: "Secondary features implementation"
      tasks: ["phase-2-secondary-*"]

    - id: "phase3-testing"
      provider: "google"
      model: "gemini-2.5-pro"
      phase: 3
      focus: "Comprehensive testing suite"
      tasks: ["phase-3-*"]

    - id: "phase4-deployment"
      provider: "anthropic"
      model: "claude-sonnet-4"
      phase: 4
      focus: "Deployment preparation, CI/CD"
      tasks: ["phase-4-*"]

    - id: "phase4-documentation"
      provider: "perplexity"
      model: "llama-3.1-sonar-large-128k-online"
      phase: 4
      focus: "Final documentation, user guides"
      tasks: ["phase-4-docs-*"]

  coordination:
    phase_gating: true
    wait_for_dependencies: true
    sync_interval: 180

  output:
    directory: ".tmlpd-phases"
    logs: "phase-logs.json"
```

---

## Implementation Workflow

### Step 1: Pre-Deployment Analysis
```bash
# Analyze project complexity and task count
cd /path/to/project

# If using TaskMaster
task-master analyze-complexity --research

# Get task count
task-master list --status=pending | wc -l
```

### Step 2: Create Deployment Plan
```bash
# Generate deployment config based on project
cat > .tmlpd-plan.yaml << EOF
deployment:
  project_name: "brain-spark-analysis"
  total_tasks: 25
  parallel_strategy: "category"
  agents_required: 4
  estimated_duration: "45 minutes"
EOF
```

### Step 3: Deploy Parallel Agents
```bash
# Launch parallel deployment
treequest-parallel \
  --config=.tmlpd-plan.yaml \
  --background \
  --monitor
```

### Step 4: Monitor Execution
```bash
# Real-time monitoring
watch -n 10 'treequest status'

# View agent logs
tail -f .tmlpd-output/tmlpd-logs.json

# Check progress
treequest-parallel --status
```

### Step 5: Merge & Validate
```bash
# Merge all agent outputs
treequest-parallel --merge

# Run validation
treequest-parallel --validate

# Generate completion report
treequest-parallel --report > completion-report.md
```

---

## Advanced Features

### Dynamic Load Balancing
```yaml
coordination:
  load_balancing: "dynamic"
  rebalance_interval: 120  # 2 minutes
  overload_threshold: 3     # tasks pending
  strategy: "work-stealing"
```

### Cost Optimization
```yaml
cost_optimization:
  enabled: true
  budget_limit: 50.00  # USD
  prefer_cached: true
  fallback_models:
    - provider: "groq"
      model: "llama-3.3-70b-versatile"
      cost_multiplier: 0.1
```

### Error Recovery
```yaml
error_handling:
  retry_policy: "exponential_backoff"
  max_retries: 3
  fallback_on_failure: true
  checkpoint_interval: 600  # 10 minutes
```

---

## Integration with Brain Spark Project

### Example: Brain Spark Mobile App Enhancement
```bash
cd ~/brain-spark-analysis-project

# Deploy for UI enhancement tasks
treequest-parallel \
  --agents=5 \
  --mode=category \
  --tasks="task-ui-*,task-accessibility-*,task-i18n-*" \
  --providers="anthropic,openai,google,groq,cerebras" \
  --background

# Monitor progress
treequest-parallel --monitor --refresh=30
```

### TaskMaster Integration
```bash
# Combine with TaskMaster for project management
task-master parse-prd .taskmaster/docs/ui_enhancement_prd.txt
task-master expand --all --research

# Deploy TreeQuest agents on expanded tasks
treequest-parallel \
  --source=taskmaster \
  --agents=4 \
  --config=.tmlpd-brainspark.yaml
```

---

## Performance Benchmarks

### Expected Performance Gains

| Scenario | Sequential Time | Parallel Time (4 agents) | Speedup |
|----------|----------------|--------------------------|---------|
| 25 tasks, mixed complexity | 120 min | 35 min | **3.4x** |
| 50 tasks, research-heavy | 240 min | 65 min | **3.7x** |
| 100 tasks, full-stack dev | 480 min | 120 min | **4.0x** |

### Cost Optimization

**Optimal Provider Selection:**
- Simple tasks (tests, docs) → Groq/Cerebras (10x cheaper)
- Complex reasoning → Claude Sonnet (balanced cost/performance)
- Critical architecture → Claude Opus (quality over cost)
- Research tasks → Perplexity Sonar (web access included)

---

## Troubleshooting

### Issue: Agent Failure
```bash
# Check failed agent logs
treequest-parallel --logs --agent=frontend-agent

# Restart failed agent
treequest-parallel --restart-agent=frontend-agent

# Resume from checkpoint
treequest-parallel --resume-checkpoint
```

### Issue: Resource Exhaustion
```bash
# Reduce agent count
treequest-parallel --config=.tmlpd-plan.yaml --agents=2

# Enable rate limiting
treequest-parallel --rate-limit=5  # requests per minute
```

### Issue: Merge Conflicts
```bash
# Auto-resolve with timestamp strategy
treequest-parallel --merge-conflicts --strategy=timestamp

# Manual resolution
treequest-parallel --merge-conflicts --strategy=manual
```

---

## Best Practices

1. **Start Small:** Begin with 2-3 agents, scale up based on success
2. **Monitor Closely:** Use real-time monitoring in first deployments
3. **Set Budgets:** Always configure cost limits to prevent overruns
4. **Use Checkpoints:** Enable checkpointing for long-running tasks
5. **Validate Outputs:** Always run validation after parallel execution
6. **Document Strategy:** Keep deployment configs in version control
7. **Profile First:** Run test deployment to measure actual throughput

---

## Example Commands for Brain Spark

### Quick 4-Agent Deployment
```bash
cd ~/brain-spark-analysis-project

# Deploy for pending testing tasks
treequest-parallel \
  --agents=4 \
  --mode=category \
  --filter="status=pending,category=testing" \
  --providers="anthropic,openai,google,groq" \
  --output=.tmlpd-output \
  --background

# Check progress
treequest-parallel --status
```

### Research & Documentation Sprint
```bash
# Deploy research-focused agents
treequest-parallel \
  --agents=3 \
  --mode=specialized \
  --focus="research,documentation,analysis" \
  --providers="perplexity,google,anthropic" \
  --budget=30.00 \
  --timeout=3600
```

---

## Monitoring & Metrics

### Real-Time Dashboard
```bash
# Launch monitoring dashboard
treequest-parallel --dashboard

# View metrics
treequest-parallel --metrics

# Export performance data
treequest-parallel --export-metrics > metrics-$(date +%s).json
```

### Key Metrics Tracked
- **Tasks Completed:** Total tasks finished per agent
- **Average Latency:** Response time per provider
- **Cost Accumulation:** Running cost total
- **Error Rate:** Failed task percentage
- **Throughput:** Tasks per minute per agent

---

## Exit Strategy

### Graceful Shutdown
```bash
# Stop all agents gracefully
treequest-parallel --shutdown --graceful

# Force shutdown (emergency)
treequest-parallel --shutdown --force

# Save partial progress
treequest-parallel --save-checkpoint
```

### Resume Operations
```bash
# Resume from last checkpoint
treequest-parallel --resume

# Resume specific agent
treequest-parallel --resume-agent=frontend-agent
```

---

## Configuration Templates

Copy these templates to your project for quick deployment:

```bash
# Copy category template
cp ~/.claude/skills/tmlpd-category.yaml ~/brain-spark-analysis-project/

# Copy phase template
cp ~/.claude/skills/tmlpd-phase.yaml ~/brain-spark-analysis-project/

# Copy monitoring config
cp ~/.claude/skills/tmlpd-monitoring.yaml ~/brain-spark-analysis-project/
```

---

## Support & Resources

- **TreeQuest Docs:** https://github.com/treequest-ai/treequest
- **Issue Tracker:** https://github.com/treequest-ai/issues
- **Config Examples:** `~/.config/treequest/examples/`
- **Logs:** `~/.treequest/logs/`

---

**Version:** 1.0.0
**Last Updated:** 2026-01-01
**Maintained By:** TreeQuest AI Community
