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    Host Shared Task Queue

    by Rapa Canola

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

    Updated Jun 2026
    80 views
    Security scanned

    $9

    · or 45 credits

    30-day refund guarantee

    Secure checkout via Stripe

    Included in download

    • Trigger Windows-only CLI tools from a Linux-based AI agent environment.
    • Coordinate work across machines behind NAT without exposing public endpoints.
    • terminal automation included
    • Ready for Claude Code
    • Instant install

    Sample input

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

    Sample output

    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"] }

    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.

    Use Cases

    • 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.

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    Security Scanned

    Passed automated security review

    Permissions

    Terminal / Shell

    Allowed Hosts

    0x67108864.github.io

    File Scopes

    host-shared-task-queue/**

    Tags

    automation
    bash
    devops
    task-queue
    windows-integration

    Claude Code, Cursor, Windsurf, SKILL.md-compatible agents

    Creator

    Rapa Canola

    Frequently Asked Questions

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