Multi Agent Guardrails Workflow

    2

    Design deterministic Mesh Flow guardrail topologies and verifier contracts for complex multi-agent AI systems.

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    Works with the AI Agents you already use

    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIMuseMuseDotsDots+21 more

    multi-agent-guardrails-workflow

    Example session with this skill installed

    Design a high-risk workflow for a CRM update agent. Include human approval gates, record match verifiers, and export the project.yaml and compliance report.

    • Read your context and instructions
    • Compiled the multi-agent-guardrails-workflow

    [GUARDRAIL POLICY: HIGH RISK]

    • Tool: CRM_Write
    • Gate: Human Approval Required
    • Verifier: Record_Match_Contract
    • Failure Path: Redact_And_Escalate

    Generated: project.yaml (Ready for Mesh Flow)
    Generated: verifier_contracts.json
    Generated: compliance_report.md

    project.yaml

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

    About this skill

    Explicit Multi-Agent Governance Designer

    Moving from a single prompt to a complex multi-agent system introduces significant operational risk. This skill solves the "black box" orchestration problem by transforming your high-level system requirements into a deterministic, production-ready Mesh Flow guardrail topology.

    Instead of relying on LLMs to "behave" via prompting, this tool generates hard-coded safety architectures. It classifies your agents' authority, defines strictly typed verifier contracts, and maps out explicit recovery paths for when agents fail. It bridges the gap between a whiteboard architectural concept and a deployable execution plan.

    What it does

    • Risk Classification: Automatically categorizes actions into observe-only, tool-write, or irreversible categories.
    • Topology Generation: Emits a project.yaml identifying exactly where hard gates and human-in-the-loop approvals must occur.
    • Contract Definition: Scripts technical verifier contracts that define pass/fail evidence requirements for every high-risk step.
    • Artifact Production: Delivers structured JSON for integrations, Markdown for compliance reviews, and YAML for Mesh Flow runners.

    Why use this skill

    Prompting an AI to "follow safety rules" is unreliable. This skill provides a deterministic framework that forces your agents through a structured DAG (Directed Acyclic Graph) where safety is handled by the orchestration layer, not just the model's instructions. It is essential for teams working in high-stakes environments like FinTech, Healthcare, or CRM automation where data integrity is non-negotiable.

    • Designer ONLY: Does not perform real-time verification or runtime monitoring.
    • Requires manual schema validation for custom multi-agent frameworks outside of Mesh Flow.

    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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    Listed6 months ago

    What's inside

    Frequently Asked Questions

    This skill provides a deterministic orchestration layer that enforces safety via hard-coded gates and verifier contracts, ensuring agents follow a specific execution path rather than relying on unreliable system prompts.

    The skill is platform-agnostic and generates structured assets like project.yaml and JSON, making it compatible with any multi-agent framework that supports DAG-based orchestration or Mesh Flow runners.

    You will receive a complete governance package including a risk classification report, technical verifier contracts, a production-ready project.yaml topology, and compliance documentation in Markdown.

    Setup is straightforward; you provide your high-level system requirements and agent roles, and the skill automatically maps out the required topology and safety gates for your specific environment.

    Yes, the generated workflow includes explicit recovery paths and human-in-the-loop (HITL) approval gates for actions categorized as high-risk or irreversible.

    New in Agents & Orchestration