Claude Code Configuration - SPARC Development Environment

🚨 CRITICAL: CONCURRENT EXECUTION & FILE MANAGEMENT

ABSOLUTE RULES:

1. ALL operations MUST be concurrent/parallel in a single message
2. NEVER save working files, text/mds and tests to the root folder
3. ALWAYS organize files in appropriate subdirectories
4. USE CLAUDE CODE'S TASK TOOL for spawning agents concurrently, not just MCP

⚡ GOLDEN RULE: "1 MESSAGE = ALL RELATED OPERATIONS"

MANDATORY PATTERNS:

• TodoWrite: ALWAYS batch ALL todos in ONE call (5-10+ todos minimum)
• Task tool (Claude Code): ALWAYS spawn ALL agents in ONE message with full instructions
• File operations: ALWAYS batch ALL reads/writes/edits in ONE message
• Bash commands: ALWAYS batch ALL terminal operations in ONE message
• Memory operations: ALWAYS batch ALL memory store/retrieve in ONE message

🎯 CRITICAL: Claude Code Task Tool for Agent Execution

Claude Code's Task tool is the PRIMARY way to spawn agents:

// ✅ CORRECT: Use Claude Code's Task tool for parallel agent execution
[Single Message]:
  Task("Research agent", "Analyze requirements and patterns...", "researcher")
  Task("Coder agent", "Implement core features...", "coder")
  Task("Tester agent", "Create comprehensive tests...", "tester")
  Task("Reviewer agent", "Review code quality...", "reviewer")
  Task("Architect agent", "Design system architecture...", "system-architect")

MCP tools are ONLY for coordination setup:

• mcp__fidgetflo__swarm_init - Initialize coordination topology
• mcp__fidgetflo__agent_spawn - Define agent types for coordination
• mcp__fidgetflo__task_orchestrate - Orchestrate high-level workflows

📁 File Organization Rules

NEVER save to root folder. Use these directories:

• /src - Source code files
• /tests - Test files
• /docs - Documentation and markdown files
• /config - Configuration files
• /scripts - Utility scripts
• /examples - Example code

Project Overview

This project uses SPARC (Specification, Pseudocode, Architecture, Refinement, Completion) methodology with FidgetFlo orchestration for systematic Test-Driven Development.

SPARC Commands

Core Commands

• npx fidgetflo sparc modes - List available modes
• npx fidgetflo sparc run <mode> "<task>" - Execute specific mode
• npx fidgetflo sparc tdd "<feature>" - Run complete TDD workflow
• npx fidgetflo sparc info <mode> - Get mode details

Batchtools Commands

• npx fidgetflo sparc batch <modes> "<task>" - Parallel execution
• npx fidgetflo sparc pipeline "<task>" - Full pipeline processing
• npx fidgetflo sparc concurrent <mode> "<tasks-file>" - Multi-task processing

Build Commands

• npm run build - Build project
• npm run test - Run tests
• npm run lint - Linting
• npm run typecheck - Type checking

SPARC Workflow Phases

1. Specification - Requirements analysis (sparc run spec-pseudocode)
2. Pseudocode - Algorithm design (sparc run spec-pseudocode)
3. Architecture - System design (sparc run architect)
4. Refinement - TDD implementation (sparc tdd)
5. Completion - Integration (sparc run integration)

Code Style & Best Practices

• Modular Design: Files under 500 lines
• Environment Safety: Never hardcode secrets
• Test-First: Write tests before implementation
• Clean Architecture: Separate concerns
• Documentation: Keep updated

🚀 Available Agents (54 Total)

Core Development

coder, reviewer, tester, planner, researcher

Swarm Coordination

hierarchical-coordinator, mesh-coordinator, adaptive-coordinator, collective-intelligence-coordinator, swarm-memory-manager

Consensus & Distributed

byzantine-coordinator, raft-manager, gossip-coordinator, consensus-builder, crdt-synchronizer, quorum-manager, security-manager

Performance & Optimization

perf-analyzer, performance-benchmarker, task-orchestrator, memory-coordinator, smart-agent

GitHub & Repository

github-modes, pr-manager, code-review-swarm, issue-tracker, release-manager, workflow-automation, project-board-sync, repo-architect, multi-repo-swarm

SPARC Methodology

sparc-coord, sparc-coder, specification, pseudocode, architecture, refinement

Specialized Development

backend-dev, mobile-dev, ml-developer, cicd-engineer, api-docs, system-architect, code-analyzer, base-template-generator

Testing & Validation

tdd-london-swarm, production-validator

Migration & Planning

migration-planner, swarm-init

🎯 Claude Code vs MCP Tools

Claude Code Handles ALL EXECUTION:

• Task tool: Spawn and run agents concurrently for actual work
• File operations (Read, Write, Edit, MultiEdit, Glob, Grep)
• Code generation and programming
• Bash commands and system operations
• Implementation work
• Project navigation and analysis
• TodoWrite and task management
• Git operations
• Package management
• Testing and debugging

MCP Tools ONLY COORDINATE:

• Swarm initialization (topology setup)
• Agent type definitions (coordination patterns)
• Task orchestration (high-level planning)
• Memory management
• Neural features
• Performance tracking
• GitHub integration

KEY: MCP coordinates the strategy, Claude Code's Task tool executes with real agents.

🤖 AUTOMATIC SWARM ORCHESTRATION

Claude Code MUST automatically invoke swarm orchestration for complex tasks.

🚨 CRITICAL: MCP + Task Tool in SAME Message

When user says "spawn swarm" or requests complex work, Claude Code MUST in ONE message:

1. Call MCP tools to initialize coordination
2. IMMEDIATELY call Task tool to spawn REAL working agents
3. Both MCP and Task calls must be in the SAME response

MCP alone does NOT execute work - Task tool agents do the actual work!

Auto-Start Swarm Protocol

When Claude Code detects a complex task (multi-file, new feature, or refactoring), it MUST:

// 🚨 ALL OF THIS IN ONE SINGLE MESSAGE - MCP + Task + TodoWrite together!
[Single Message - Complete Swarm Spawn]:

  // MCP: Initialize coordination topology
  mcp__fidgetflo__swarm_init { topology: "hierarchical-mesh", maxAgents: 15, strategy: "adaptive" }
  mcp__fidgetflo__agent_spawn { type: "coordinator", name: "queen" }
  mcp__fidgetflo__task_orchestrate { task: "[user's task]", strategy: "adaptive", priority: "high" }
  mcp__fidgetflo__memory_usage { action: "store", namespace: "swarm", key: "session", value: "..." }

  // Task Tool: Spawn REAL working agents (THIS IS REQUIRED!)
  Task("Coordinator", "Orchestrate the swarm, manage agent coordination...", "hierarchical-coordinator")
  Task("Architect", "Design system architecture, document decisions...", "system-architect")
  Task("Researcher", "Analyze requirements, research patterns...", "researcher")
  Task("Coder", "Implement core features following architecture...", "coder")
  Task("Tester", "Create comprehensive test suite...", "tester")
  Task("Reviewer", "Review code quality and security...", "reviewer")

  // TodoWrite: Track all tasks
  TodoWrite { todos: [
    {content: "Initialize swarm coordination", status: "completed", activeForm: "Initializing"},
    {content: "Research requirements", status: "in_progress", activeForm: "Researching"},
    {content: "Design architecture", status: "in_progress", activeForm: "Designing"},
    {content: "Implement solution", status: "pending", activeForm: "Implementing"},
    {content: "Write tests", status: "pending", activeForm: "Testing"},
    {content: "Review code", status: "pending", activeForm: "Reviewing"}
  ]}

❌ WRONG - MCP only (no actual work happens):

// This ONLY sets up coordination - no agents actually work!
mcp__fidgetflo__swarm_init { ... }
mcp__fidgetflo__agent_spawn { ... }
// Missing Task tool calls = nothing executes!

✅ CORRECT - MCP + Task tool together:

// Same message: coordination + execution
mcp__fidgetflo__swarm_init { ... }
Task("Agent1", "Do actual work...", "agent-type")
Task("Agent2", "Do actual work...", "agent-type")

Agent Routing by Task Type

Task Complexity Detection

Auto-invoke swarm when:

• Task involves 3+ files
• Task is a new feature or module
• Task requires architectural decisions
• Task involves multiple concerns (API + DB + UI)
• User requests "comprehensive" or "full" implementation

Skip swarm for:

• Single file edits
• Simple bug fixes (1-2 line changes)
• Documentation updates
• Configuration changes

Settings Configuration

Claude Code should ensure proper settings via hooks:

# Auto-configure on session start
npx fidgetflo@alpha hooks session-start --auto-configure
npx fidgetflo@alpha memory store --key "session/config" --value '{"topology":"hierarchical-mesh","maxAgents":15}'

Swarm Lifecycle Management

Session Start (automatic):

[Auto-Init on Complex Task]:
  // Check task complexity
  mcp__fidgetflo__features_detect { component: "task-analyzer" }

  // Initialize if complex
  mcp__fidgetflo__swarm_init { topology: "hierarchical-mesh" }
  mcp__fidgetflo__memory_usage { action: "store", key: "session/active", value: "true" }

  // Spawn initial agents
  Task("Coordinator", "Manage swarm coordination...", "hierarchical-coordinator")

Task Execution (automatic):

[During Task - Memory Coordination]:
  // Store decisions in shared memory
  mcp__fidgetflo__memory_usage { action: "store", key: "task/decisions", value: "[decisions]" }

  // Track progress
  mcp__fidgetflo__task_status { taskId: "[current-task]" }

  // Neural learning from patterns
  mcp__fidgetflo__neural_patterns { action: "learn", operation: "[what was done]", outcome: "[result]" }

Session End (automatic):

[Auto-Cleanup]:
  // Persist learnings
  mcp__fidgetflo__memory_persist { sessionId: "[session-id]" }

  // Export metrics
  mcp__fidgetflo__swarm_status { verbose: true }

  // Train neural patterns
  mcp__fidgetflo__neural_train { pattern_type: "coordination", training_data: "[session-summary]" }

🚀 Quick Setup

# Add MCP servers (FidgetFlo required, others optional)
claude mcp add fidgetflo npx fidgetflo@alpha mcp start
claude mcp add ruv-swarm npx ruv-swarm mcp start  # Optional: Enhanced coordination
claude mcp add flow-nexus npx flow-nexus@latest mcp start  # Optional: Cloud features

MCP Tool Categories

Coordination

swarm_init, agent_spawn, task_orchestrate

Monitoring

swarm_status, agent_list, agent_metrics, task_status, task_results

Memory & Neural

memory_usage, neural_status, neural_train, neural_patterns

GitHub Integration

github_swarm, repo_analyze, pr_enhance, issue_triage, code_review

System

benchmark_run, features_detect, swarm_monitor

Flow-Nexus MCP Tools (Optional Advanced Features)

Flow-Nexus extends MCP capabilities with 70+ cloud-based orchestration tools:

Key MCP Tool Categories:

• Swarm & Agents: swarm_init, swarm_scale, agent_spawn, task_orchestrate
• Sandboxes: sandbox_create, sandbox_execute, sandbox_upload (cloud execution)
• Templates: template_list, template_deploy (pre-built project templates)
• Neural AI: neural_train, neural_patterns, seraphina_chat (AI assistant)
• GitHub: github_repo_analyze, github_pr_manage (repository management)
• Real-time: execution_stream_subscribe, realtime_subscribe (live monitoring)
• Storage: storage_upload, storage_list (cloud file management)

Authentication Required:

• Register: mcp__flow-nexus__user_register or npx flow-nexus@latest register
• Login: mcp__flow-nexus__user_login or npx flow-nexus@latest login
• Access 70+ specialized MCP tools for advanced orchestration

🚀 Agent Execution Flow with Claude Code

The Correct Pattern:

1. Optional: Use MCP tools to set up coordination topology
2. REQUIRED: Use Claude Code's Task tool to spawn agents that do actual work
3. REQUIRED: Each agent runs hooks for coordination
4. REQUIRED: Batch all operations in single messages

Example Full-Stack Development:

// Single message with all agent spawning via Claude Code's Task tool
[Parallel Agent Execution]:
  Task("Backend Developer", "Build REST API with Express. Use hooks for coordination.", "backend-dev")
  Task("Frontend Developer", "Create React UI. Coordinate with backend via memory.", "coder")
  Task("Database Architect", "Design PostgreSQL schema. Store schema in memory.", "code-analyzer")
  Task("Test Engineer", "Write Jest tests. Check memory for API contracts.", "tester")
  Task("DevOps Engineer", "Setup Docker and CI/CD. Document in memory.", "cicd-engineer")
  Task("Security Auditor", "Review authentication. Report findings via hooks.", "reviewer")
  
  // All todos batched together
  TodoWrite { todos: [...8-10 todos...] }
  
  // All file operations together
  Write "backend/server.js"
  Write "frontend/App.jsx"
  Write "database/schema.sql"

📋 Agent Coordination Protocol

Every Agent Spawned via Task Tool MUST:

1️⃣ BEFORE Work:

npx fidgetflo@alpha hooks pre-task --description "[task]"
npx fidgetflo@alpha hooks session-restore --session-id "swarm-[id]"

2️⃣ DURING Work:

npx fidgetflo@alpha hooks post-edit --file "[file]" --memory-key "swarm/[agent]/[step]"
npx fidgetflo@alpha hooks notify --message "[what was done]"

3️⃣ AFTER Work:

npx fidgetflo@alpha hooks post-task --task-id "[task]"
npx fidgetflo@alpha hooks session-end --export-metrics true

🎯 Concurrent Execution Examples

✅ CORRECT WORKFLOW: MCP Coordinates, Claude Code Executes

// Step 1: MCP tools set up coordination (optional, for complex tasks)
[Single Message - Coordination Setup]:
  mcp__fidgetflo__swarm_init { topology: "mesh", maxAgents: 6 }
  mcp__fidgetflo__agent_spawn { type: "researcher" }
  mcp__fidgetflo__agent_spawn { type: "coder" }
  mcp__fidgetflo__agent_spawn { type: "tester" }

// Step 2: Claude Code Task tool spawns ACTUAL agents that do the work
[Single Message - Parallel Agent Execution]:
  // Claude Code's Task tool spawns real agents concurrently
  Task("Research agent", "Analyze API requirements and best practices. Check memory for prior decisions.", "researcher")
  Task("Coder agent", "Implement REST endpoints with authentication. Coordinate via hooks.", "coder")
  Task("Database agent", "Design and implement database schema. Store decisions in memory.", "code-analyzer")
  Task("Tester agent", "Create comprehensive test suite with 90% coverage.", "tester")
  Task("Reviewer agent", "Review code quality and security. Document findings.", "reviewer")
  
  // Batch ALL todos in ONE call
  TodoWrite { todos: [
    {id: "1", content: "Research API patterns", status: "in_progress", priority: "high"},
    {id: "2", content: "Design database schema", status: "in_progress", priority: "high"},
    {id: "3", content: "Implement authentication", status: "pending", priority: "high"},
    {id: "4", content: "Build REST endpoints", status: "pending", priority: "high"},
    {id: "5", content: "Write unit tests", status: "pending", priority: "medium"},
    {id: "6", content: "Integration tests", status: "pending", priority: "medium"},
    {id: "7", content: "API documentation", status: "pending", priority: "low"},
    {id: "8", content: "Performance optimization", status: "pending", priority: "low"}
  ]}
  
  // Parallel file operations
  Bash "mkdir -p app/{src,tests,docs,config}"
  Write "app/package.json"
  Write "app/src/server.js"
  Write "app/tests/server.test.js"
  Write "app/docs/API.md"

❌ WRONG (Multiple Messages):

Message 1: mcp__fidgetflo__swarm_init
Message 2: Task("agent 1")
Message 3: TodoWrite { todos: [single todo] }
Message 4: Write "file.js"
// This breaks parallel coordination!

Performance Benefits

• 84.8% SWE-Bench solve rate
• 32.3% token reduction
• 2.8-4.4x speed improvement
• 27+ neural models

Hooks Integration

Pre-Operation

• Auto-assign agents by file type
• Validate commands for safety
• Prepare resources automatically
• Optimize topology by complexity
• Cache searches

Post-Operation

• Auto-format code
• Train neural patterns
• Update memory
• Analyze performance
• Track token usage

Session Management

• Generate summaries
• Persist state
• Track metrics
• Restore context
• Export workflows

Advanced Features (v2.0.0)

• 🚀 Automatic Topology Selection
• ⚡ Parallel Execution (2.8-4.4x speed)
• 🧠 Neural Training
• 📊 Bottleneck Analysis
• 🤖 Smart Auto-Spawning
• 🛡️ Self-Healing Workflows
• 💾 Cross-Session Memory
• 🔗 GitHub Integration

Integration Tips

1. Start with basic swarm init
2. Scale agents gradually
3. Use memory for context
4. Monitor progress regularly
5. Train patterns from success
6. Enable hooks automation
7. Use GitHub tools first

Support

• Documentation: https://github.com/ruvnet/claude-flow
• Issues: https://github.com/ruvnet/claude-flow/issues
• Flow-Nexus Platform: https://flow-nexus.ruv.io (registration required for cloud features)

Remember: FidgetFlo coordinates, Claude Code creates!

important-instruction-reminders

Do what has been asked; nothing more, nothing less. NEVER create files unless they're absolutely necessary for achieving your goal. ALWAYS prefer editing an existing file to creating a new one. NEVER proactively create documentation files (*.md) or README files. Only create documentation files if explicitly requested by the User. Never save working files, text/mds and tests to the root folder.