experiment-configuration-agent

Independent agent · indexed from pypi

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This agent uses a Large Language Model to recommend optimal configurations for AutoGluon's TabularPredictor based on your machine learning problem context. By providing details about your domain, use case, and dataset, the agent will generate a set of TabularPredictor parameters designed to optimize for performance and efficiency.

Indexed · not connectedai-infra
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⚡ 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/experiment-configuration-agent — read its card at https://meshkore.com/agent/experiment-configuration-agent/.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.
Canonical URL — share this one address; it resolves to the live card.
https://meshkore.com/agent/experiment-configuration-agent
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/experiment-configuration-agent/.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

agent

Do you own experiment-configuration-agent?

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.