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LM Orchestra

Claude Code License: MIT Agents Plugins

LM Orchestra is an intelligent multi-agent orchestration system for Claude Code that automatically selects, coordinates, and manages specialized AI agents to deliver complete solutions for complex software development tasks.

Overview

When you give LM Orchestra a task, it:

  1. Analyzes your request to understand requirements and capabilities needed
  2. Plans the optimal sequence of specialized agents to invoke
  3. Executes the workflow with intelligent parallel/sequential coordination
  4. Validates outputs against domain-specific quality gates
  5. Synthesizes coherent, production-ready deliverables
User Request: "Build a FastAPI authentication service with JWT and OAuth2"
                                    ↓
                            ┌─────────────┐
                            │ task-router │ → Analyzes intent & extracts capabilities
                            └──────┬──────┘
                                   ↓
                           ┌──────────────┐
                           │ agent-planner│ → Selects agents & creates execution plan
                           └──────┬───────┘
                                  ↓
                         [User Approval Gate]
                                  ↓
                        ┌──────────────────┐
                        │workflow-executor │ → Spawns & coordinates agents
                        └────────┬─────────┘
                                 ↓
                        ┌────────────────┐
                        │output-validator│ → Applies quality gates
                        └───────┬────────┘
                                ↓
                    [Pass] → Final Deliverable
                    [Fail] → Refinement Loop (max 2x)

Features

  • 108+ Specialized Agents across 23 domains (backend, frontend, security, DevOps, ML, etc.)
  • 72 Focused Plugins with minimal token footprint (avg 3.4 components/plugin)
  • 129+ Skills providing domain-specific knowledge on demand
  • Intelligent Routing - Maps natural language to capabilities to agents
  • Quality Gates - Domain-specific validation (code, security, architecture, testing)
  • Refinement Loops - Automatic retry with targeted instructions on failures
  • Parallel Execution - Identifies opportunities to run independent agents simultaneously
  • User Approval - Full visibility and control before execution begins

Quick Start

Prerequisites

  • Claude Code CLI installed
  • Python 3.8+ (for registry scripts)

Installation

  1. Clone the repository with submodules

    git clone --recursive https://github.com/yourusername/lmorchestra.git
    cd lmorchestra

    If you already cloned without --recursive, initialize the submodule:

    git submodule update --init --recursive
  2. Install the Meta-Orchestrator plugin

    cd meta-orchestrator
    claude plugin install .
  3. Install the Agents ecosystem (optional, for full capabilities)

    cd ../agents
    claude plugin install .

Usage

Option 1: Shell Alias (Recommended)

Add these aliases to your shell configuration (~/.bashrc, ~/.zshrc, etc.):

# Full orchestration pipeline
orchestrate() {
  claude "/meta-orchestrator:orchestrate $*" \
    --allowedTools "Bash,Read,Write,Edit,Grep,Glob,WebFetch,WebSearch,Task" \
    --plugin-dir /path/to/lmorchestra/meta-orchestrator
}

# Preview execution plan only
plan() {
  claude "/meta-orchestrator:plan $*" \
    --allowedTools "Bash,Read,Grep,Glob,Task" \
    --plugin-dir /path/to/lmorchestra/meta-orchestrator
}

# Validate existing code
validate() {
  claude "/meta-orchestrator:validate $*" \
    --allowedTools "Bash,Read,Grep,Glob" \
    --plugin-dir /path/to/lmorchestra/meta-orchestrator
}

Then run directly from your terminal:

orchestrate "Build a FastAPI CRUD API for inventory management with PostgreSQL"
plan "Migrate Django monolith to microservices"
validate --path src/ --gates security

Option 2: Within Claude Code Session

Start Claude Code with the plugin directory:

claude --plugin-dir /path/to/lmorchestra/meta-orchestrator

Then use the commands:

/orchestrate "Build a FastAPI CRUD API for inventory management with PostgreSQL"
/plan "Create a real-time collaborative editor with WebSocket support"
/validate --path src/api/ --gates security,testing --severity high

Option 3: One-liner

Run a single orchestration task:

claude "/meta-orchestrator:orchestrate Build a user auth system with JWT" \
  --allowedTools "Bash,Read,Write,Edit,Grep,Glob,WebFetch,WebSearch,Task" \
  --plugin-dir /path/to/lmorchestra/meta-orchestrator

Commands

Command Description Example
/orchestrate Full pipeline: analyze → plan → execute → validate → deliver /orchestrate "Build user auth with JWT"
/plan Preview execution plan without running /plan "Migrate Django to FastAPI"
/validate Run quality gates on existing code /validate --path src/ --gates security

Architecture

Components

lmorchestra/
├── agents/                    # Git submodule → github.com/1fc0nfig/agents
│   ├── plugins/               # 72 specialized plugin directories
│   │   ├── backend-development/
│   │   ├── frontend-mobile-development/
│   │   ├── kubernetes-operations/
│   │   ├── python-development/
│   │   ├── security-scanning/
│   │   └── ... (67 more)
│   └── docs/
│
├── meta-orchestrator/         # Orchestration layer
│   ├── agents/                # 5 orchestration agents
│   ├── commands/              # 3 user-facing commands
│   ├── skills/                # 3 knowledge skills
│   ├── registry/              # Generated agent/capability indexes
│   └── scripts/               # Registry build tools
│
└── README.md                  # This file

Orchestration Agents

Agent Model Purpose
task-router Sonnet Analyzes user intent and extracts required capabilities
agent-planner Opus Creates optimal multi-agent execution plans
workflow-executor Opus Coordinates agent invocation and context passing
output-validator Sonnet Applies domain-specific quality gates
result-synthesizer Sonnet Merges multi-agent outputs into unified deliverables

Knowledge Skills

Skill Purpose
agent-registry Complete knowledge of all 108+ agents and selection criteria
capability-mapping Maps keywords → capabilities → agents
quality-gates Domain-specific validation criteria by deliverable type

Agent Ecosystem

The agents are organized into 23 categories:

Category Plugins Example Agents
Backend 4 backend-architect, fastapi-pro, graphql-architect
Frontend 4 frontend-developer, react-pro, mobile-developer
Infrastructure 5 cloud-architect, kubernetes-operator, terraform-pro
Security 4 security-auditor, threat-modeling-expert, compliance-checker
Data & ML 6 database-architect, ml-engineer, llm-app-builder
Quality 3 code-reviewer, test-automator, performance-engineer
DevOps 4 cicd-architect, deployment-specialist, observability-expert
Languages 7 python-pro, typescript-pro, rust-pro, go-pro
Documentation 3 api-documenter, c4-architect, technical-writer
... ... ...

See agents/README.md for the complete catalog.

Example Workflows

Building a REST API

/orchestrate "Build a FastAPI REST API for user management with PostgreSQL"

Generated Plan:

  1. database-architect → Design schema for users table
  2. backend-architect → Define API contract and endpoints
  3. fastapi-pro → Implement the API
  4. test-automator → Generate tests (parallel)
  5. security-auditor → Security review (parallel with tests)

Full-Stack Feature

/orchestrate "Create a dashboard with React frontend, FastAPI backend, and PostgreSQL"

Generated Plan:

  1. database-architect → Schema design
  2. backend-architect + frontend-developer → API & UI design (parallel)
  3. fastapi-pro → Backend implementation
  4. react-pro → Frontend implementation (parallel with backend)
  5. test-automator → E2E tests
  6. security-auditor → Final security review

Security Audit

/orchestrate "Perform a comprehensive security audit of our authentication system"

Generated Plan:

  1. security-auditor → OWASP vulnerability scan
  2. threat-modeling-expert → Threat analysis
  3. backend-security-coder → Generate fix recommendations
  4. result-synthesizer → Produce security report

Registry

The registry indexes all agents, skills, and capabilities for intelligent selection:

registry/
├── agents.json        # 108+ agents with capabilities, triggers, paths
├── capabilities.json  # Capability-to-agent reverse mappings
├── skills.json        # 129+ skills indexed
└── plugins.json       # 72 plugins with components

Rebuild Registry

When the agents repository is updated:

cd meta-orchestrator
python scripts/build-registry.py --source ../agents --output ./registry
python scripts/validate-registry.py --registry ./registry

Quality Gates

The output-validator applies these domain-specific checks:

Gate Checks
Code Quality Syntax validity, error handling, type safety, documentation
Security Input validation, auth patterns, injection prevention, OWASP compliance
Architecture Separation of concerns, design patterns, dependency management
Testing Test coverage, edge cases, mocking patterns
Database Schema design, indexing, migration safety, query performance

Issues are categorized by severity (critical/high/medium/low) with specific remediation instructions.

Model Configuration

LM Orchestra uses a cost-optimized three-tier model strategy:

Tier Model Use Case Cost
Heavy Opus 4.5 Complex planning, critical decisions $5/$25 per 1M tokens
Balanced Sonnet 4.5 Routing, validation, synthesis $3/$15 per 1M tokens
Fast Haiku 4.5 Simple operations, quick checks $1/$5 per 1M tokens

Configuration

The plugin can be configured via .claude-plugin/marketplace.json:

{
  "metadata": {
    "model_recommendations": {
      "task-router": "sonnet",
      "agent-planner": "opus",
      "workflow-executor": "opus",
      "output-validator": "sonnet",
      "result-synthesizer": "sonnet"
    }
  }
}

Contributing

We welcome contributions! See CONTRIBUTING.md for guidelines.

Development Setup

  1. Clone the repository
  2. Create a Python virtual environment:
    python -m venv venv
    source venv/bin/activate  # or `venv\Scripts\activate` on Windows
  3. Make your changes
  4. Test with /orchestrate commands
  5. Submit a pull request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

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