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Claw Conductor

Always-on autonomous development orchestrator.

Rating
4.7 (496 reviews)
Downloads
11,519 downloads
Version
1.0.0

Overview

Always-on autonomous development orchestrator.

Complete Documentation

View Source →

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):

text
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):

text
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:

text
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:

python
# 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:
bash
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:

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

First-Time Setup

bash
./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:

text
@OpenClaw use claw-conductor to build a calculator app

Complex request:

text
@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

text
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:

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

Decomposition:

text
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:

text
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:

text
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:

text
✅ 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:

python
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)

ModelCapabilityComplexity FitExperienceCostTotal
Mistral Devstral4★ (40pts)Can handle 4 (40pts)0 (0pts)Free (10pts)90/100
Llama 3.3 70B4★ (40pts)Can handle 4 (40pts)2 tasks (2pts)Free (10pts)92/100
PerplexityN/ACannot handle backend--0/100
Winner: Llama 3.3 70B (higher experience)


Configuration

Agent Registry Structure

config/agent-registry.json:

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:

text
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:

text
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

text
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

text
@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

text
@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

text
@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

  • [x] Task decomposition (v2.0)
  • [x] Parallel execution (v2.0)
  • [x] Multi-project support (v2.0)
  • [x] 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

Installation

Terminal bash

openclaw install claw-conductor
    
Copied!

💻Code Examples

**Simple Questions** (fast response):

simple-questions-fast-response.txt
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):

development-tasks-full-orchestration.txt
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-overrides.txt
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]

)

.txt
**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:

In OpenClaw:

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

./scripts/setup.sh

scriptssetupsh.txt
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:**

- Payment integration

--payment-integration.txt
---

## How It Works

### Complete Workflow

Discord Completion Report

discord-completion-report.txt
### Example: Dispatch System

**Request:**

🎉 Project ready for deployment

-project-ready-for-deployment.txt
---

## Scoring Algorithm

Each model is scored 0-100 for each task:

)

.txt
**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`:

Tags

#productivity_and-tasks

Quick Info

Category Development
Model Claude 3.5
Complexity One-Click
Author johnsonfarmsus
Last Updated 3/10/2026
🚀
Optimized for
Claude 3.5
🧠

Ready to Install?

Get started with this skill in seconds

openclaw install claw-conductor