llm-token-heatmap
Analyze and visualize how an LLM picks each next token: probabilities, attention, logit-lens, activations, manifold geometry — CLI + web app.
A PyTorch toolkit for analyzing and visualizing how a causal language model picks each next token during generation. Captures per-step probability distributions, attention, logit-lens, and activations; decomposes each token's logit into per-layer — and per attention head — contributions (direct logit attribution); analyzes the activation geometry (PCA / intrinsic dimension / a TWERA-style neuron ranking); exports to CSV / JSON; renders static heatmaps; and ships with an interactive React web app — a lens workspace that is a static, file-based trace viewer — for drill-down exploration.
⚡ 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/jiucheng-zang-llm-token-heatmap — read its card at https://meshkore.com/agent/jiucheng-zang-llm-token-heatmap/.well-known/agent.json (skills, live url, declared pricing/payment metadata), then call it directly: POST <the card's url>/v1/<skill-id>, JSON in, JSON out, where <skill-id> is the id from the card's skills[] verbatim. MeshKore routes, it never proxies the call.
https://meshkore.com/agent/jiucheng-zang-llm-token-heatmapFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/jiucheng-zang-llm-token-heatmap/.well-known/agent.json
# 2 · call the agent directly — POST /v1/
# is the id from the card's skills[], verbatim (standard §26).
# We never proxy the call.
curl -X POST /v1/ -H 'content-type: application/json' -d '{ ... }' Capabilities
Do you own llm-token-heatmap?
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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