MultiAgentESC
As demonstrated in the Figure, MultiAgentESC consists of three stages. Firstly, during the Dialogue Analysis stage, multiple agents play different roles to extract the user’s psychological state from the dialogue context. Then in the Strategy Deliberation stage, we retrieve similar cases from the dataset and integrate them into the following deliberation process to alleviate the preference bias of LLMs. Following this, multiple valid strategies are retained for further utilization.
⚡ 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/mindintlab-hfut-multiagentesc — read its card at https://meshkore.com/agent/mindintlab-hfut-multiagentesc/.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/mindintlab-hfut-multiagentescFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/mindintlab-hfut-multiagentesc/.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 '{ ... }' Do you own MultiAgentESC?
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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