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    agent-handoff-orchestrator (for hermes agent / openclaw)

    agent-handoff-orchestrator (for hermes agent / openclaw)

    by Roy Yuen

    Generate high-fidelity, structured handoff packets for seamless multi-agent collaboration and session persistence.

    Updated May 2026
    0 installs

    Free

    One-time purchase · Own forever

    ⚡ Also available via Agensi MCP — your AI agent can load this skill on demand via MCP. Learn more →

    Included in download

    • Downloadable skill package
    • Instant install

    See it in action

    ## Mission
    Implement JWT validation in the auth middleware.
    
    ## Current State
    - Verified: User service returns 401 on missing tokens.
    - Assumption: The RSA public key is in /etc/secrets/pub.pem.
    
    ## Boundaries
    - In scope: middleware/auth.js
    - Do not touch: Any database connection logic.

    Screenshots

    About This Skill

    What it does

    The Agent Handoff Orchestrator is a specialized skill designed to solve the "context collapse" problem in multi-agent workflows and long-running sessions. It generates high-density, structured handoff packets that allow work to move seamlessly between AI agents, human operators, or future sessions without losing progress or requiring rediscovery of facts.

    Why use this skill

    Standard LLM prompts often lead to "drift" when tasks are delegated. This skill enforces a rigorous engineering standard for state transfer by defining clear authority boundaries, separating verified facts from assumptions, and establishing strict return contracts. It ensures that the receiver—whether it's a coder, reviewer, or QA agent—can begin productive work in under one minute with zero ambiguity.

    Supported Workflows

    • AI-to-AI delegation (Implementation, Research, Security)
    • AI-to-Human escalation (Approvals, Risky decisions)
    • Session-to-Session persistence (Context compression)
    • Failure Recovery (Root cause analysis and repair handoffs)

    The output is a structured Markdown packet optimized for LLM comprehension, featuring explicit mission statements, scope constraints, and observable success criteria.

    📖 Learn more: Best DevOps & Deployment Skills for Claude Code →

    Use Cases

    • Compress long session context into a concise "next-step" packet for later.
    • Delegate a specific bug fix to a sub-agent with strict file boundaries.
    • Format a decision request for a human operator including risks and options.
    • Generate a repair mission after a tool failure to isolate the root cause.

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