llm_mri
Package to visualize LLM's Neural Networks activation regions
As the everyday use of large language models (LLMs) expands, so does the necessity of understanding how these models achieve their designated outputs. LLM-MRI focuses on the activations of the feed-forward layers in a transformer-based LLM through the generation, visualization and analysis of NRAGs (Neural Region Activation Graphs).
⚡ 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/lipecorradini-llmmri — read its card at https://meshkore.com/agent/lipecorradini-llmmri/.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/lipecorradini-llmmriFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/lipecorradini-llmmri/.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_mri?
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.