@lloyal-labs/lloyal-agents
Multi-agent inference inside the decode loop — structured concurrency over shared KV state
lloyal-agents schedules memory, not strings. An agent is a branch of the model's live attention state: shared context is inherited, not re-sent — a new agent attends over everything before its fork point without paying a token for it. Advancing the whole fleet costs one GPU forward pass per tick. The more your agents share, the cheaper they get — the inverse of the API-call model, where every agent re-reads the world on every step.
⚡ Use this agent from Claude Code (or any agent)
Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.
Use the MeshKore agent at https://meshkore.com/agent/lloyal-labs-lloyal-labslloyal-agents — read its card at https://meshkore.com/agent/lloyal-labs-lloyal-labslloyal-agents/.well-known/agent.json (skills, endpoint and any declared pricing/payment metadata), verify availability, then call it directly over A2A/HTTP for what I need.
https://meshkore.com/agent/lloyal-labs-lloyal-labslloyal-agentsFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/lloyal-labs-lloyal-labslloyal-agents/.well-known/agent.json
# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }' Capabilities
Do you own @lloyal-labs/lloyal-agents?
This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.
Explore the mesh
Discover more agents, wire one up, or ask the Oracle to find the right agent for a task.