Host Shared Task Queue

    2

    Async task delegation for AI agents via shared folders—perfect for cross-OS and remote worker coordination.

    $9

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    0 installsSecurity scanned

    Works with the AI tools you already use

    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIMuseMuseOpenClawOpenClaw+21 more

    host-shared-task-queue

    Example session with this skill installed

    Run the video render for project_v1 on the Windows host using the render-queue and tell me when it's finished.

    • Read your context and instructions
    • Compiled the host-shared-task-queue

    UUID: 8f2b-4e1a...
    Waiting for result from 'render-queue'...
    Done!

    {
  "status": "success",
  "output_file": "C:\\Renders\\project_v1.mp4",
  "duration_seconds": 145,
  "artifacts": ["log.txt", "thumb.png"]
}

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

    What you get

    Trigger Windows-only CLI tools from a Linux-based AI agent environment.Coordinate work across machines behind NAT without exposing public endpoints.Delegate long-running tasks to an external worker to bypass agent timeouts.Implement a robust "human-in-the-loop" approval flow via shared files.

    About this skill

    What it does

    The Shared Task Queue skill provides a robust, low-tech way for an AI agent to delegate tasks to external processes using a shared filesystem directory as the transport. It implements an asynchronous inbox/outbox pattern that works across different machines, operating systems, and user accounts without requiring complex network setup or message brokers.

    Why use this skill

    Developers often face the "walled garden" problem where an AI agent in a Linux container needs to trigger a process on a Windows host, a legacy machine, or a browser session behind a NAT. This skill bridges that gap. Unlike standard MCP servers or HTTP webhooks, it requires zero infrastructure beyond a shared folder (SMB, NFS, Dropbox, or SyncThing). It handles the messy details of atomic file writes, cross-OS line endings, and polling logic.

    Supported tools

    • Compatible with any watcher process that can read and write JSON files.
    • Built-in bash scripts for send, wait, receive, and purge operations.
    • Fallback support for Python 3 when specialized CLI utilities are missing.
    • Supports shared directories via Samba, SyncThing, NFS, or local mounts.

    The Result

    The agent submits a structured JSON payload and receives a structured response once the external worker completes the task. All communication is persisted in the filesystem, providing a clear audit log and making failures easy to debug.

    How to install

    Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.

    ~30 seconds
    1. 1

      Download the ZIP

      Free skills download straight away. Paid skills unlock right after purchase.

    2. 2

      Unzip into your skills folder

      Every agent reads skills from one folder on your machine. Drop the unzipped folder in there.

    3. 3

      Ask your agent to use it

      Restart the agent if it was already running. It picks the skill up automatically - no config needed.

    Skills folder by agent

    Click the path to copy it. Create the folder if it does not exist yet.

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    Fresh listing

    Recently published to Agensi

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    Trust & safety

    Security scanned

    Verified clean 4 months ago

    • Passed all security checks, Safe to install

    Listed4 months ago

    What's inside

    Frequently Asked Questions