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:
- Message arrives in Discord channel (e.g., #scientific-calculator)
- Claw-conductor detects channel → maps to
/root/projects/scientific-calculator - Triages request: Simple question or development task?
- If Simple: Quick response from fast model with project context
- 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:
Extract the request from the user's message (everything after "use claw-conductor to")
Determine project name from the request or generate one from keywords
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) "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": {
"model_id": "mistral/devstral-2512",
"provider": "mistral",
"context_window": 256000,
"enabled": true,
"user_cost": {
"type": "free-tier",
"input_cost_per_million": 0,
"output_cost_per_million": 0
},
"capabilities": {
"frontend-development": {
"rating": 5,
"max_complexity": 5,
"notes": "Expert - near-parity with Claude"
},
"multi-file-refactoring": {
"rating": 5,
"max_complexity": 5,
"notes": "Expert - designed for 50+ file changes"
}
}
}
}
}
Fallback Strategy
Conservative fallback (user-configurable):
- Try primary model (attempt 1)
- Try primary model (attempt 2)
- If both fail → Try first runner-up (attempt 3)
- Try first runner-up (attempt 4)
- 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:
- Check git status for conflicts
- Run tests (pytest, npm test, etc.)
- Commit with conventional commit message
- Push to GitHub (if configured)
- 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
Built with ❤️ by the Claw Conductor team