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    Multi-Agent Orchestration Patterns Library

    2

    Produces a full system design: agent roles and interfaces, inter-agent contracts, routing logic, error escalation paths, and a production hardening checklist.

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    Multi-Agent Orchestration Patterns Library

    Multi-Agent Orchestration Patterns Library

    Example session with this skill installed

    I need to build a system that takes a 10-page PDF, extracts technical specs, writes a 500-word summary, and then checks the summary against the original for accuracy using different agents.

    • Read your context and instructions
    • Compiled the multi-agent orchestration patterns

    I recommend a Sequential Pipeline with a Verification Gate:

    1. Extractor Agent (Haiku): Structured JSON extraction.
    2. Writer Agent (Sonnet): Markdown summary.
    3. Reviewer Agent (Opus): Fact-check against PDF.
      Would you like the YAML config for this orchestration?

    Connects securely to your tools. The creator never sees your data.

    About this skill

    Designing a multi-agent system without a pattern library is like wiring a circuit board freehand. This skill knows every orchestration topology — sequential chains, parallel fan-out, hierarchical delegation, map-reduce pipelines, critic-actor loops — and selects the right one for your exact workflow. Produces a full system design: agent roles and interfaces, inter-agent contracts, routing logic, error escalation paths, and a production hardening checklist. Specify what you're building and your stack. Skip the architectural mistakes that kill multi-agent projects before they reach production.

    • Cannot execute Python or JS code directly: provides design and config files only.
    • Complex state management (Redis/Kafka) requires manual infrastructure setup.

    How to use

    1. 1

      Connect your agent to the Agensi MCP

      Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup

    2. 2

      Sign in to Agensi

      Your agent shows a sign-in link. Sign in and click Allow.

    3. 3

      Ask for what you need

      Your agent loads this skill and uses it on your task. It always asks before any payment.

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    Listed4 months ago
    Updated12 days ago

    What's inside

    Frequently Asked Questions

    This skill eliminates "architectural debt" by providing pre-validated blueprints for agent communication. It solves common issues like circular loops, message bottlenecks, and failure handling by selecting the mathematically best topology for your specific use case.

    It is framework-agnostic and works with any modern stack, including LangGraph, AutoGen, CrewAI, or custom Python/TypeScript implementations. You simply specify your tech stack during the design phase, and the skill adapts the architecture accordingly.

    You receive a comprehensive system design package including topological diagrams, agent role definitions, routing logic specifications, inter-agent data contracts, and a production-readiness checklist.

    No complex installation is required; this is a logic and design-based skill that integrates directly into your AI development workflow. Once activated, it guides you through the process of architecting your multi-agent system from scratch or optimizing an existing one.

    Yes, the library includes specialized "Error Paths" and "Critic-Actor" loops designed to handle edge cases. It provides specific logic for how agents should escalate failures or retry tasks when a downstream agent returns an invalid response.