claude-code-agents-orchestra

🥈Silver

Claude Code Orchestra transforms Claude Code into a coordinated team of 40+ specialized AI agents. It enables operations teams to automate complex workflows by orchestrating agents to work together like a world-class engineering organization. Connects to existing Claude Code workflows and integrates with tools like GitHub, Jira, and CI/CD pipelines.

3280Updated 1w ago

Intermediate30min to implementautomation

Saves ~480 min per use

Quick InstallView Source

git clone https://github.com/0ldh/claude-code-agents-orchestra.git

Works with:

Claude

Overview

About This Skill

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/0ldh/claude-code-agents-orchestra

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

Act as a Claude Code Orchestra conductor. Coordinate 40+ specialized AI agents to automate a complex workflow for [COMPANY] in the [INDUSTRY] sector. The workflow should integrate with [TOOLS] and process [DATA]. Provide a step-by-step plan for orchestrating the agents, including their roles, responsibilities, and interactions.

Example Output

# Claude Code Orchestra Workflow Plan

## Workflow Overview

**Company:** GreenTech Solutions
**Industry:** Renewable Energy
**Tools:** GitHub, Jira, CI/CD Pipeline (GitLab)
**Data:** Solar panel performance metrics, weather data, maintenance logs

## Agent Roles and Responsibilities

1. **Data Ingestion Agent**: Collects and validates data from solar panel sensors, weather APIs, and maintenance logs.
2. **Data Processing Agent**: Cleans, transforms, and aggregates the data for analysis.
3. **Analysis Agent**: Performs predictive maintenance analysis and identifies potential issues.
4. **Reporting Agent**: Generates reports and visualizations for stakeholders.
5. **Integration Agent**: Updates Jira tickets, creates GitHub issues, and triggers CI/CD pipelines for automated fixes.

## Workflow Steps

1. **Data Collection**: The Data Ingestion Agent collects data from various sources and validates its integrity.
2. **Data Processing**: The Data Processing Agent cleans and transforms the data, making it ready for analysis.
3. **Analysis**: The Analysis Agent runs predictive models to identify potential maintenance issues.
4. **Reporting**: The Reporting Agent generates a comprehensive report with visualizations and insights.
5. **Integration**: The Integration Agent updates Jira tickets, creates GitHub issues, and triggers the CI/CD pipeline for automated fixes.

## Expected Outcomes

- Improved predictive maintenance capabilities
- Reduced downtime for solar panels
- Automated issue tracking and resolution
- Enhanced data-driven decision-making