Which transfer strategy should I use for large files?

The 'parallel' strategy is optimized for large files and high bandwidth, utilizing 4 concurrent threads to maximize throughput.

How does the play/coplay semantic work in file transfers?

The 'play' phase initiates the file transfer (forward pass), while the 'coplay' phase handles the receiver's acknowledgment and calculates a utility score based on speed and completeness (backward pass).

Can I discover peers automatically within my network?

Yes, the skill includes a discover_mesh_peers method that identifies online Tailscale peers, their hostnames, and their 100.x.y.z IP addresses.

What is GF(3) trit semantics in this context?

It uses ternary logic to track perspectives: +1 (covariant) for the receiver's benefit, -1 (contravariant) for the sender's perspective, and 0 for neutral network observation.

What are the requirements for using this skill?

It requires an active Tailscale mesh network configuration, Ruby 2.7+, and the HedgesOpenGames framework for lens-based bidirectional optics.

Tailscale File Transfer (Open Games)

Name: Tailscale File Transfer (Open Games)
Author: plurigrid

byplurigrid

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クラウドインフラストラクチャ

Facilitates peer-to-peer file sharing across Tailscale mesh networks using game-theoretic semantics and bidirectional lens optics.

The Tailscale File Transfer skill integrates Jules Hedges' Compositional Game Theory with Tailscale's mesh VPN to create a sophisticated P2P data exchange system. By treating transfers as 'open games' with distinct forward (play) and backward (coplay) passes, it ensures that every file movement includes built-in acknowledgment and utility scoring. This skill is particularly useful for distributed systems requiring verifiable state synchronization, offering multiple transfer strategies—sequential, parallel, and adaptive—to optimize throughput across complex topological network architectures.

主な機能

01Three transfer strategies: sequential, parallel, and adaptive

02Bidirectional Lens Optics for state transformation and utility propagation

03Automated Tailscale mesh peer discovery and recipient resolution

04Compositional Game Theory integration with play/coplay semantics

05GF(3) trit-based perspective tracking for covariant and contravariant roles

067 GitHub stars

ユースケース

01Implementing verifiable P2P transfers with deterministic game-theoretic utility scoring

02Automating high-bandwidth file distribution to specific mesh hostnames or IPs

03Synchronizing distributed CRDT models and learned networks across private mesh peers

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add plurigrid/asi tailscale-file-transfer

For use in Claude.ai and ChatGPT

Download Skill