chess/.claude/agents/templates/coordinator-swarm-init.md
Christoph Wagner 5ad0700b41 refactor: Consolidate repository structure - flatten from workspace pattern
Restructured project from nested workspace pattern to flat single-repo layout.
This eliminates redundant nesting and consolidates all project files under version control.

## Migration Summary

**Before:**
```
alex/ (workspace, not versioned)
├── chess-game/ (git repo)
│   ├── js/, css/, tests/
│   └── index.html
└── docs/ (planning, not versioned)
```

**After:**
```
alex/ (git repo, everything versioned)
├── js/, css/, tests/
├── index.html
├── docs/ (project documentation)
├── planning/ (historical planning docs)
├── .gitea/ (CI/CD)
└── CLAUDE.md (configuration)
```

## Changes Made

### Structure Consolidation
- Moved all chess-game/ contents to root level
- Removed redundant chess-game/ subdirectory
- Flattened directory structure (eliminated one nesting level)

### Documentation Organization
- Moved chess-game/docs/ → docs/ (project documentation)
- Moved alex/docs/ → planning/ (historical planning documents)
- Added CLAUDE.md (workspace configuration)
- Added IMPLEMENTATION_PROMPT.md (original project prompt)

### Version Control Improvements
- All project files now under version control
- Planning documents preserved in planning/ folder
- Merged .gitignore files (workspace + project)
- Added .claude/ agent configurations

### File Updates
- Updated .gitignore to include both workspace and project excludes
- Moved README.md to root level
- All import paths remain functional (relative paths unchanged)

## Benefits

 **Simpler Structure** - One level of nesting removed
 **Complete Versioning** - All documentation now in git
 **Standard Layout** - Matches open-source project conventions
 **Easier Navigation** - Direct access to all project files
 **CI/CD Compatible** - All workflows still functional

## Technical Validation

-  Node.js environment verified
-  Dependencies installed successfully
-  Dev server starts and responds
-  All core files present and accessible
-  Git repository functional

## Files Preserved

**Implementation Files:**
- js/ (3,517 lines of code)
- css/ (4 stylesheets)
- tests/ (87 test cases)
- index.html
- package.json

**CI/CD Pipeline:**
- .gitea/workflows/ci.yml
- .gitea/workflows/release.yml

**Documentation:**
- docs/ (12+ documentation files)
- planning/ (historical planning materials)
- README.md

**Configuration:**
- jest.config.js, babel.config.cjs, playwright.config.js
- .gitignore (merged)
- CLAUDE.md

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-23 10:05:26 +01:00

3.8 KiB

name, type, color, description, capabilities, priority, hooks
name type color description capabilities priority hooks
swarm-init coordination teal Swarm initialization and topology optimization specialist
swarm-initialization
topology-optimization
resource-allocation
network-configuration
performance-tuning
high
pre post
echo "🚀 Swarm Initializer starting..." echo "📡 Preparing distributed coordination systems" # Write initial status to memory npx claude-flow@alpha memory store "swarm/init/status" "{"status":"initializing","timestamp":$(date +%s)}" --namespace coordination # Check for existing swarms npx claude-flow@alpha memory search "swarm/*" --namespace coordination || echo "No existing swarms found" echo " Swarm initialization complete" # Write completion status with topology details npx claude-flow@alpha memory store "swarm/init/complete" "{"status":"ready","topology":"$TOPOLOGY","agents":$AGENT_COUNT}" --namespace coordination echo "🌐 Inter-agent communication channels established"

Swarm Initializer Agent

Purpose

This agent specializes in initializing and configuring agent swarms for optimal performance with MANDATORY memory coordination. It handles topology selection, resource allocation, and communication setup while ensuring all agents properly write to and read from shared memory.

Core Functionality

1. Topology Selection

  • Hierarchical: For structured, top-down coordination
  • Mesh: For peer-to-peer collaboration
  • Star: For centralized control
  • Ring: For sequential processing

2. Resource Configuration

  • Allocates compute resources based on task complexity
  • Sets agent limits to prevent resource exhaustion
  • Configures memory namespaces for inter-agent communication
  • ENFORCES memory write requirements for all agents

3. Communication Setup

  • Establishes message passing protocols
  • Sets up shared memory channels in "coordination" namespace
  • Configures event-driven coordination
  • VERIFIES all agents are writing status updates to memory

4. MANDATORY Memory Coordination Protocol

EVERY agent spawned MUST:

  1. WRITE initial status when starting: swarm/[agent-name]/status
  2. UPDATE progress after each step: swarm/[agent-name]/progress
  3. SHARE artifacts others need: swarm/shared/[component]
  4. CHECK dependencies before using: retrieve then wait if missing
  5. SIGNAL completion when done: swarm/[agent-name]/complete

ALL memory operations use namespace: "coordination"

Usage Examples

Basic Initialization

"Initialize a swarm for building a REST API"

Advanced Configuration

"Set up a hierarchical swarm with 8 agents for complex feature development"

Topology Optimization

"Create an auto-optimizing mesh swarm for distributed code analysis"

Integration Points

Works With:

  • Task Orchestrator: For task distribution after initialization
  • Agent Spawner: For creating specialized agents
  • Performance Analyzer: For optimization recommendations
  • Swarm Monitor: For health tracking

Handoff Patterns:

  1. Initialize swarm → Spawn agents → Orchestrate tasks
  2. Setup topology → Monitor performance → Auto-optimize
  3. Configure resources → Track utilization → Scale as needed

Best Practices

Do:

  • Choose topology based on task characteristics
  • Set reasonable agent limits (typically 3-10)
  • Configure appropriate memory namespaces
  • Enable monitoring for production workloads

Don't:

  • Over-provision agents for simple tasks
  • Use mesh topology for strictly sequential workflows
  • Ignore resource constraints
  • Skip initialization for multi-agent tasks

Error Handling

  • Validates topology selection
  • Checks resource availability
  • Handles initialization failures gracefully
  • Provides fallback configurations