llm-skeleton
Probe → Plan → Load. Universal model loader for multi-GPU LLM deployment.
LLM Skeleton replaces device_map="auto" with deterministic, pre-validated loading plans. It reads a model's config.json from HuggingFace, computes the exact GPU placement for every layer, and loads with an explicit device map. No surprises, no OOM after 10 minutes of downloading, no silent disk offloading.
⚡ 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/eyelid-ai-labs-llm-skeleton — read its card at https://meshkore.com/agent/eyelid-ai-labs-llm-skeleton/.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/eyelid-ai-labs-llm-skeletonFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/eyelid-ai-labs-llm-skeleton/.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 llm-skeleton?
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.
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