What is the primary purpose of the Lattice Spatial-Collective skill?

It provides a standardized protocol for multiple AI agents to maintain a shared, coherent memory across a distributed network without relying on a central server.

How does LATTICE handle agent failures or churn?

It uses erasure coding to split context into shards; as long as a minimum threshold (K of N) of agents remain, the full context can be reconstructed by the network.

What is Semantic Anchoring in this context?

Semantic Anchoring uses embedding vectors to ensure that the meaning of shared information doesn't distort or drift as it is passed between different AI models.

Does this skill protect against malicious AI behavior?

Yes, it incorporates HoneyBadgerBFT consensus, requiring a 67% majority for critical updates, and uses cryptographic signatures to ensure data integrity.

Lattice Spatial-Collective

Name: Lattice Spatial-Collective
Author: starwreckntx

bystarwreckntx

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Data Science & ML

Implements a decentralized context-sharing protocol for multi-agent systems using cryptographic sharding and Byzantine fault tolerance.

About

The Lattice Spatial-Collective skill enables Claude to implement and manage the LATTICE Protocol, a sophisticated 'mycelial intelligence' framework for distributed AI. By utilizing peer-to-peer context sharding, erasure coding, and gossip propagation, it ensures that multi-agent networks maintain coherent shared memory even during node failures or adversarial attacks. This skill is essential for developers architecting complex, decentralized AI swarms that require high-integrity governance, fault-tolerant state management, and resilient collaborative reasoning across dynamic environments.

Key Features

Decentralized P2P networking using WebRTC and Kademlia DHT for agent discovery.
Cryptographic context sharding with Reed-Solomon erasure coding for fault tolerance.
Gossip-based propagation for efficient, O(log N) information diffusion across networks.
1 GitHub stars
Byzantine Fault Tolerance (BFT) consensus to prevent context corruption by malicious nodes.
Semantic Anchoring Protocol to detect and prevent interpretation drift in shared data.

Use Cases

Managing state consistency in distributed AI tasks across heterogeneous hardware.
Coordinating resilient multi-agent swarms with shared long-term memory.
Implementing decentralized AI-to-AI governance and security frameworks.

About

Key Features

Decentralized P2P networking using WebRTC and Kademlia DHT for agent discovery.
Cryptographic context sharding with Reed-Solomon erasure coding for fault tolerance.
Gossip-based propagation for efficient, O(log N) information diffusion across networks.
1 GitHub stars
Byzantine Fault Tolerance (BFT) consensus to prevent context corruption by malicious nodes.
Semantic Anchoring Protocol to detect and prevent interpretation drift in shared data.

Use Cases

Managing state consistency in distributed AI tasks across heterogeneous hardware.
Coordinating resilient multi-agent swarms with shared long-term memory.
Implementing decentralized AI-to-AI governance and security frameworks.