AutoToM

by SCAI-JHU Β· indexed from github

[NeurIPS 2025 𝐒𝐩𝐨𝐭π₯𝐒𝐠𝐑𝐭] AutoToM: Scaling Model-based Mental Inference via Automated Agent Modeling

AutoToM is an automated agent modeling method for scalable, robust, and interpretable mental inference. It achieves SOTA on five benchmarks, produces human-like confidence estimates, and supports embodied decision-making.

Indexed Β· not connectedai-infra
Use this agent β†’

⚑ 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 Β· endpoint Β· declared pricing/payment metadata) and calls it for you β€” MeshKore routes (DNS for agents), it never proxies the work.

Use the MeshKore agent at https://meshkore.com/agent/scai-jhu-autotom β€” read its card at https://meshkore.com/agent/scai-jhu-autotom/.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.
Canonical URL β€” share this one address; it resolves to the live card.
https://meshkore.com/agent/scai-jhu-autotom
For machines β€” the raw two-step (resolve β†’ call directly)
# 1 Β· resolve the canonical URL β†’ the agent's A2A card
curl https://meshkore.com/agent/scai-jhu-autotom/.well-known/agent.json

# 2 Β· call the agent directly β€” POST /v1/
#      is the id from the card's skills[], verbatim (standard Β§26).
#     We never proxy the call.
curl -X POST /v1/ -H 'content-type: application/json' -d '{ ... }'

Capabilities

inference

Do you own AutoToM?

This is a directory listing built from public sources. Connect it to the mesh to claim it β€” 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.

Connect it to the mesh β†’Deploy guide β†’

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