Maestro is an agent orchestration command center for automating workflows. Operations teams use it to manage and coordinate AI agents, improving efficiency and reducing manual intervention. It connects to Claude and other generative AI tools, streamlining complex tasks.
git clone https://github.com/pedramamini/Maestro.gitMaestro is an advanced AI automation skill designed for orchestrating multiple AI agents within a cohesive framework. By acting as a command center, it allows users to manage and coordinate various AI tasks seamlessly, enhancing overall productivity. This skill is particularly beneficial for developers and product managers looking to streamline their workflows by integrating different AI functionalities into a single orchestration point. The key benefits of Maestro include improved efficiency in managing AI agents and the ability to automate complex workflows. Although specific time savings are not quantified, the orchestration capability significantly reduces the manual effort involved in coordinating multiple AI tasks. This translates to faster project completion times and the ability to focus on higher-level strategic initiatives rather than getting bogged down in the minutiae of task management. Maestro is ideal for intermediate users, making it suitable for developers and AI practitioners who have a foundational understanding of AI automation. It can be particularly useful in departments focused on product development, where agile methodologies are employed, and rapid iteration is essential. For instance, a product manager could use Maestro to automate the deployment of updates across various AI agents, ensuring consistency and reducing the risk of errors. Implementing Maestro requires approximately 30 minutes, making it accessible for teams looking to enhance their AI-first workflows without extensive setup time. As organizations increasingly adopt AI automation, integrating Maestro into existing processes will enable teams to leverage AI agents more effectively, ultimately driving innovation and efficiency in their projects.
Automate the generation of detailed specification documents and execute them with Auto Run.
Manage multiple AI agents in parallel to streamline project workflows and reduce development time.
Utilize Git worktrees to run isolated AI agents on different branches without conflicts.
Coordinate discussions among multiple AI agents for cross-project architecture and decision-making.
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/pedramamini/MaestroCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Create an orchestration plan for [PROJECT NAME] that involves [TASKS] across [AGENTS/TEAMS]. Specify the timeline for each task and any dependencies that need to be considered. Additionally, outline a communication strategy to ensure all stakeholders are aligned throughout the process.
For the project 'Website Redesign', the orchestration plan includes the following tasks: 'Content Creation', 'Design Mockups', and 'User Testing'. The timeline is as follows: Content Creation (Week 1-2), Design Mockups (Week 3-4), and User Testing (Week 5). Dependencies include the completion of Content Creation before starting Design Mockups. The communication strategy involves weekly check-ins via Slack, with a shared Google Drive folder for all project documents to ensure transparency and alignment among the design team, content writers, and stakeholders.
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