claw-conductor

name	claw-conductor
description	Always-on autonomous development orchestrator with intelligent triage. Auto-detects Discord channels, routes to project workspaces, triages simple vs development requests, decomposes complex tasks, routes to optimal AI models, executes in parallel, and consolidates results.
version	2.1.0

Claw Conductor v2.1

Your always-on development assistant - handles everything from quick questions to full project builds.

Claw Conductor is an intelligent orchestration layer that:

• 🎯 Always-On: Handles every message automatically (no need to invoke)
• 🤖 Smart Triage: Detects simple questions vs development tasks
• 💬 Discord-Aware: Auto-maps channels to project workspaces
• 🔀 Multi-Model: Routes tasks to optimal AI based on capabilities
• ⚡ Parallel Execution: Builds complete projects efficiently

🚀 How It Works

Automatic Flow:

1. Message arrives in Discord channel (e.g., #scientific-calculator)
2. Claw-conductor detects channel → maps to /root/projects/scientific-calculator
3. Triages request: Simple question or development task?
4. If Simple: Quick response from fast model with project context
5. If Development: Full orchestration - decompose, route, execute, consolidate

You never need to explicitly invoke it - it handles everything automatically!

🎯 Usage Examples

Simple Questions (fast response):

User: What files are in this project?
Conductor: 📋 Simple response mode
          [Lists files from /root/projects/scientific-calculator]

User: How does the calculator work?
Conductor: 📋 Simple response mode
          [Explains architecture with project context]

Development Tasks (full orchestration):

User: Build a scientific calculator with trig functions
Conductor: 🔧 Development mode - full orchestration
          [Decomposes into tasks, routes to models, executes in parallel]

User: Fix the bug in the calculation logic
Conductor: 🔧 Development mode - full orchestration
          [Analyzes code, creates fix, tests, commits]

User Overrides:

User: !simple Build a calculator
Conductor: 📋 Simple response mode
          [Gives advice/explanation instead of building]

User: !dev What files exist?
Conductor: 🔧 Development mode - full orchestration
          [Treats as development task - maybe creates file listing tool]

🚀 Skill Invocation (For OpenClaw Agent)

NEW: Always-On Mode (Recommended)

Configure this skill as the default handler for Discord channels in "Active Projects" category:

# In OpenClaw agent configuration
from orchestrator import Orchestrator

orchestrator = Orchestrator()

# Handle ALL messages through conductor
result = orchestrator.handle_message(
    request=user_message,
    channel_id=discord_channel_id,
    channel_name=discord_channel_name
)

Legacy: Explicit Invocation

When this skill is invoked with a development request, execute the following:

1. Extract the request from the user's message (everything after "use claw-conductor to")

2. Determine project name from the request or generate one from keywords

3. Execute the orchestrator using Python:

   cd ~/.openclaw/skills/claw-conductor/scripts
   python3 -c "
   from orchestrator import Orchestrator
   import sys
   
   orchestrator = Orchestrator()
   
   request = '''[USER'S REQUEST HERE]'''
   project_name = '[PROJECT-NAME]'  # e.g., 'calculator-app', 'todo-app', 'blog-site'
   
   # Get GitHub user from config
   github_user = orchestrator.config.get('github_user')
   
   result = orchestrator.execute_request(
       request=request,
       project_name=project_name,
       github_user=github_user
   )
   
   # Report results back to Discord
   if result['success']:
       print(f\"✅ Project '{project_name}' completed successfully!\")
       print(f\"📦 {result['tasks_completed']} tasks completed\")
       if github_user:
           print(f\"🔗 GitHub: https://github.com/{github_user}/{project_name}\")
       print(f\"📁 Workspace: {result.get('workspace', '/root/projects/' + project_name)}\")
   else:
       print(f\"❌ Project failed: {result.get('error', 'Unknown error')}\")
       sys.exit(1)
   "
   

4. Report progress to Discord during execution:

   • Announce task decomposition results
   • Report task routing decisions
   • Update on parallel execution progress
   • Share final results with GitHub link

Example Invocation: User says: @OpenClaw use claw-conductor to build a calculator app

You execute:

• Request: "build a calculator app"
• Project name: "calculator-app"
• Run orchestrator with these parameters

---

What's New in v2.1

🤖 AI-Powered Decomposition: Intelligently analyzes complex requests using your best AI model (auto-selected or configured) 🎯 Full Orchestration: Decomposes complex requests → Routes subtasks → Executes in parallel → Consolidates results ⚡ Parallel Execution: Up to 5 tasks running concurrently across multiple projects 📁 Project Management: Automatic workspace creation, git initialization, and GitHub integration 🔗 Dependency-Aware: Respects task dependencies and file conflicts 📦 Auto-Consolidation: Merges results, runs tests, commits to git, pushes to GitHub

---

Quick Start

Installation

In OpenClaw:

cd ~/.openclaw/skills
git clone https://github.com/johnsonfarmsus/claw-conductor.git
cd claw-conductor
./scripts/setup.sh

First-Time Setup

./scripts/setup.sh

This creates your personalized agent-registry.json with:

• Your AI model configurations
• Cost tracking (free vs paid)
• Capability ratings per model
• Routing preferences

Usage

Simple request:

@OpenClaw use claw-conductor to build a calculator app

Complex request:

@OpenClaw use claw-conductor to build a towing dispatch system with:
- Customer portal for requesting service
- Driver dashboard for accepting jobs
- Admin panel for managing users
- Real-time location tracking
- Payment integration

---

How It Works

Complete Workflow

Discord Request
    ↓
1. Task Decomposition
   • Analyzes request complexity
   • Breaks into independent subtasks
   • Assigns category & complexity to each
   • Builds dependency graph
    ↓
2. Intelligent Routing
   • Scores each model for each task (0-100)
   • Routes to best match based on capabilities
   • Considers cost optimization
    ↓
3. Project Initialization
   • Creates /root/projects/{name}/
   • Initializes git repository
   • Creates GitHub repo (if configured)
   • Sets up workspace
    ↓
4. Parallel Execution
   • Spawns up to 5 tasks simultaneously
   • Respects dependencies (database before auth)
   • Avoids file conflicts (same files sequential)
   • Reports progress to Discord
    ↓
5. Result Consolidation
   • Merges all task outputs
   • Resolves file conflicts
   • Runs tests (if present)
   • Commits to git
   • Pushes to GitHub
    ↓
Discord Completion Report

Example: Dispatch System

Request:

Build a towing dispatch system with customer portal,
driver dashboard, admin panel, and real-time tracking

Decomposition:

Task 1: Database schema (database-operations, complexity: 4)
Task 2: Authentication system (security-fixes, complexity: 4)
Task 3: Customer portal UI (frontend-development, complexity: 3)
Task 4: Driver dashboard UI (frontend-development, complexity: 3)
Task 5: Admin panel UI (frontend-development, complexity: 3)
Task 6: REST API endpoints (api-development, complexity: 3)
Task 7: Real-time tracking (performance-optimization, complexity: 5)
Task 8: Unit tests (unit-test-generation, complexity: 2)

Routing:

Task 1 → Mistral Devstral (score: 92, best for database)
Task 2 → Mistral Devstral (score: 88, security expert)
Task 3 → Mistral Devstral (score: 95, frontend expert)
Task 4 → Mistral Devstral (score: 95, frontend expert)
Task 5 → Mistral Devstral (score: 95, frontend expert)
Task 6 → Llama 3.3 70B (score: 87, API specialist)
Task 7 → Mistral Devstral (score: 78, fallback - needs Claude ideally)
Task 8 → Llama 3.3 70B (score: 95, test generation expert)

Execution:

Parallel execution plan:
Worker 1: Task 1 (Database) → Mistral
Worker 2: Task 3 (Customer UI) → Devstral
Worker 3: Task 4 (Driver UI) → Devstral
Worker 4: Task 5 (Admin UI) → Devstral
Worker 5: Task 6 (API) → Llama

After Task 1 completes:
Worker 1: Task 2 (Auth - depends on DB) → Mistral

After all code complete:
Worker 1: Task 8 (Tests) → Llama

Result:

✅ All 8 tasks completed in 47 minutes
📦 Committed to git with 8 changes
🔗 Pushed to GitHub repository
🎉 Project ready for deployment

---

Scoring Algorithm

Each model is scored 0-100 for each task:

score = (
    (rating / 5.0) * 50 +              # Model capability (0-50 pts)
    (1 - complexity/5.0) * 40 +        # Complexity fit (0-40 pts)
    (experience / 100) * 10 +          # Experience (0-10 pts)
    cost_factor * 10                   # Cost (0-10 pts)
)

Hard Ceiling: Models cannot handle tasks above their max_complexity rating.

Scoring Example

Task: Backend API development (complexity: 4)

Model	Capability	Complexity Fit	Experience	Cost	Total
Mistral Devstral	4★ (40pts)	Can handle 4 (40pts)	0 (0pts)	Free (10pts)	90/100
Llama 3.3 70B	4★ (40pts)	Can handle 4 (40pts)	2 tasks (2pts)	Free (10pts)	92/100 ✅
Perplexity	N/A	Cannot handle backend	-	-	0/100

Winner: Llama 3.3 70B (higher experience)

---

Configuration

Agent Registry Structure

config/agent-registry.json:

{
  "version": "1.0.0",
  "user_config": {
    "cost_tracking_enabled": true,
    "prefer_free_when_equal": true,
    "max_parallel_tasks": 5,
    "default_complexity_if_unknown": 3,
    "fallback": {
      "enabled": true,
      "retry_delay_seconds": 2,
      "track_failures": true,
      "penalize_failures": true,
      "failure_penalty_points": 5
    }
  },
  "agents": {
    "mistral-devstral-2512" 
       
       
       
       
       
         
         
         
      
       
         
           
           
           
        
         
           
           
           
        
      
    
  

Fallback Strategy

Conservative fallback (user-configurable):

1. Try primary model (attempt 1)
2. Try primary model (attempt 2)
3. If both fail → Try first runner-up (attempt 3)
4. Try first runner-up (attempt 4)
5. If all fail → Give up, report to Discord

Why conservative? Prevents cascading through irrelevant models that may not have capability for the task.

---

Task Categories (23 Standard)

• code-generation-new-features
• bug-detection-fixes
• multi-file-refactoring
• unit-test-generation
• debugging-complex-issues
• api-development
• security-vulnerability-detection
• security-fixes
• documentation-generation
• code-review
• frontend-development
• backend-development
• database-operations
• codebase-exploration
• dependency-management
• legacy-modernization
• error-correction
• performance-optimization
• test-coverage-analysis
• algorithm-implementation
• boilerplate-generation

---

Advanced Features

Multi-Project Support

Handle concurrent requests across different projects:

Project A: Dispatch System (3 tasks running)
Project B: Calculator App (2 tasks running)
────────────────────────────────────────────
Total: 5 concurrent tasks (at global limit)

File Conflict Detection

Tasks touching the same files run sequentially:

Task 1: Modify src/api/users.js → Running
Task 2: Modify src/api/users.js → Queued (waits for Task 1)
Task 3: Modify src/ui/dashboard.js → Running (independent)

Dependency-Aware Scheduling

Task 1: Database schema → No deps, starts immediately
Task 2: Auth system → Depends on Task 1, waits
Task 3: Frontend UI → Depends on Task 2, waits
Task 4: Tests → Depends on all, runs last

Auto-Consolidation

After all tasks complete:

1. Check git status for conflicts
2. Run tests (pytest, npm test, etc.)
3. Commit with conventional commit message
4. Push to GitHub (if configured)
5. Report to Discord

---

Examples

Simple Calculator

@OpenClaw use claw-conductor to build a calculator with:
- Basic operations (add, subtract, multiply, divide)
- Clean UI
- Unit tests

Result:

• 3 tasks (UI, logic, tests)
• Completed in ~8 minutes
• Pushed to GitHub

Towing Dispatch System

@OpenClaw use claw-conductor to build a dispatch system with:
- Customer portal
- Driver dashboard
- Admin panel
- Real-time tracking
- Payment integration

Result:

• 8 tasks across 3 models
• Completed in ~45 minutes
• Full working application

API with Documentation

@OpenClaw use claw-conductor to create a REST API for a blog with:
- CRUD operations for posts
- Authentication
- Swagger documentation
- Integration tests

Result:

• 5 tasks (schema, auth, endpoints, docs, tests)
• Completed in ~20 minutes
• API-first design

---

Troubleshooting

Task Decomposition Issues

Problem: Request not decomposed correctly Solution: Be specific in request. Include keywords: "database", "API", "frontend", "tests"

Model Selection Issues

Problem: Wrong model chosen for task Solution: Adjust capability ratings in agent-registry.json

Execution Failures

Problem: Task fails with error Solution: Fallback tries primary 2x, runner-up 2x. Check error logs in .claw-conductor/execution-log.json

Git Conflicts

Problem: Consolidation fails due to conflicts Solution: Currently requires manual resolution. Future: AI-powered conflict resolution

---

Roadmap

• Task decomposition (v2.0)
• Parallel execution (v2.0)
• Multi-project support (v2.0)
• Auto-consolidation (v2.0)
• AI-powered decomposition (v2.1)
• Discord progress updates (v2.1)
• Conflict resolution with AI (v2.2)
• Real-time task streaming (v2.2)
• Web dashboard (v3.0)

---

License

GNU AGPL v3 - See LICENSE file

Copyleft license requiring server-side source availability.

---

Contributing

See CONTRIBUTING.md for guidelines.

Published on ClawHub.ai: https://clawhub.ai/skills/claw-conductor

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Built with ❤️ by the Claw Conductor team