How does this skill identify peers on the network?

The skill uses 'tailscale status' to identify mesh nodes and then performs a UDP multicast probe on the LocalSend port to find active file-transfer endpoints.

Can I use this for automated server synchronization?

Absolutely. With the 'just' command integration and Python API, you can automate file propagation between any nodes authorized on your Tailscale network.

Is the file transfer process secure?

Yes, transfers occur over the Tailscale mesh network, which provides end-to-end encryption, while using the LocalSend REST API for the handshake and data exchange.

What is the benefit of the Gay.jl color assignment?

It provides a deterministic hex color for each peer based on their unique fingerprint, making it easier to track and distinguish nodes in logs and network graphs.

Does this require the LocalSend desktop app?

While it uses the LocalSend protocol, the skill includes a Python implementation that can act as both a sender and receiver without the full GUI application.

Tailscale LocalSend Discovery

Name: Tailscale LocalSend Discovery
Author: plurigrid

byplurigrid

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Collaboration Tools

Facilitates seamless peer discovery and secure file exchange between Tailscale mesh nodes using the LocalSend protocol.

This skill bridges the gap between private mesh networking and localized file sharing by integrating Tailscale's network status with the LocalSend protocol. It allows Claude to programmatically discover peers within a Tailscale tailnet, probe for LocalSend availability via UDP multicast, and execute secure file transfers. It is particularly useful for developers managing distributed systems, automated data synchronization between remote nodes, and implementing complex knowledge propagation patterns in topological network structures.

Key Features

01Support for UDP multicast probing and REST-based secure uploads

02LocalSend protocol implementation for cross-platform file transfers

03Deterministic peer color assignment for consistent visual identification

04Integration with epistemic-arbitrage for distributed knowledge propagation

05Automated Tailscale mesh peer discovery via CLI or API integration

062 GitHub stars

Use Cases

01Managing knowledge synchronization across distributed AI nodes in a mesh network

02Syncing configuration files or datasets between remote servers on a private tailnet

03Automating cross-device file sharing during collaborative development sessions

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add plurigrid/asi tailscale-localsend

For use in Claude.ai and ChatGPT

Download Skill