Agent handoff lite

    2

    Standardize agent-to-agent task transfers using a structured HANDOFF.md protocol to prevent context loss.

    Free

    11 installs5.0 (1 review)

    Works with the AI Agents you already use

    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIMuseMuseDotsDots+22 more

    Agent handoff lite

    Example session with this skill installed

    I've finished researching the competitor pricing for the new API tier. Generate a handoff for the copywriter agent who will draft the landing page. Data is in research_notes.json.

    • Read your context and instructions
    • Compiled the agent handoff lite

    I have generated the handoff document for the copywriter agent and stored it in the workspace.

    HANDOFF.md

    FieldDetails
    taskDraft landing page copy for the new "Pro Tier" API subscription.
    statuspartial
    output/docs/research/pricing_v2.json, /drafts/feature_list.md
    sourceshttps://stripe.com/pricing, https://aws.amazon.com/api-gateway/pricing, internal://product-spec-2024.pdf
    next ownerCopywriter Agent
    do-not-assumeDo not assume the 15% annual discount is final; verify with the finance-bot before finalizing the CTA.

    Next steps

    1. Copywriter agent should initialize by reading /docs/research/pricing_v2.json.
    2. Confirm the current promotional period dates in the project dashboard.
    3. Draft the H1 and H2 headers using the competitive advantages identified in the feature list.
    HANDOFF.md

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

    About this skill

    The problem

    Context loss during agent-to-agent transfers wastes tokens and leads to hallucinations. Important details like source URLs and specific roadblocks often disappear when switching between specialized agents.

    What it does

    • Standardizes handoffs using a strict HANDOFF.md schema.
    • Explicitly tracks source URLs and file paths to prevent data drift.
    • Defines clear ownership transitions with actionable next steps.
    • Lists "do-not-assume" constraints to force the next agent to re-verify volatile data.

    Why this beats prompting it yourself

    General prompts often result in chat history dumps that exceed context windows or miss critical status flags. This skill enforces a structured protocol that ensures the next agent has exactly what they need to resume without human intervention.

    Use cases

    • Moving a task from a research agent to a technical writing agent.
    • Passing a debug log from a diagnostic agent to a PR-authoring agent.
    • Handing off qualified leads from a scraper to an outreach specialist.
    • Updating project state between agents in a long-running CI/CD pipeline.

    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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    11 people have installed this skill.

    Trust & safety

    Security scanned

    Verified clean 1 month ago

    • Free to download with an account

    Listed1 month ago

    What's inside

    Frequently Asked Questions