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Ai Agent Orchestrator

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monkey1sai·vlatest·agents

Orchestrates complex multi-agent workflows, automating tasks and optimizing outcomes across diverse AI tools and systems.

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This skill no longer installs under the name ai-agent-orchestrator. monkey1sai/openai-cli is deleted or private, so it cannot be installed from.

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monkey1sai

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About this skill

What it does

The ai-agent-orchestrator skill allows you to chain together multiple AI agents, passing their outputs as inputs to subsequent agents. This enables complex workflows and tasks that require sequential processing or collaboration between different specialized agents. It facilitates the creation of more sophisticated automated processes than a single agent could handle alone.

When to use it

  • Automated report generation: Combine an agent for data extraction, another for analysis, and a third for writing a final report.
  • Complex research tasks: Use one agent to find relevant articles, another to summarize them, and a third to synthesize the information into a cohesive overview.
  • Multi-step creative processes: Chain agents together for brainstorming, outlining, drafting, and editing content.
  • Personalized customer service workflows: Route inquiries through different specialized agents based on the nature of the request.

Key capabilities

  • Agent chaining: Define an order in which agents execute.
  • Output passing: Automatically pass the output from one agent as input to the next.
  • Workflow definition: Specify the sequence and dependencies between agents.

Example prompts

  • "Orchestrate Agent A to extract data, then Agent B to analyze it, and finally Agent C to create a presentation."
  • "Chain together an agent for brainstorming ideas with one for refining them, and another for creating marketing copy."
  • “Run the research agent first, followed by the summarization agent.”

Tips & gotchas

The effectiveness of this skill depends on the quality and compatibility of the individual agents being chained. Ensure that the output format of one agent is suitable as input for the next to avoid errors or unexpected behavior.