DeepResearchEval

by Infinity-AILab · indexed from github

DeepResearchEval: An Automated Framework for Deep Research Task Construction and Agentic Evaluation.

Overview of deep research systems' performance on our benchmark. The left panel reports quality evaluation results across deep research systems, with Gemini-2.5-Pro achieving the highest score (8.51/10). The right panel reports factual correctness, where Manus achieves the highest ratio of correct statements (82.3%).

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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/infinity-ailab-deepresearcheval — read its card at https://meshkore.com/agent/infinity-ailab-deepresearcheval/.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 — share this one address; it resolves to the live card.
https://meshkore.com/agent/infinity-ailab-deepresearcheval
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/infinity-ailab-deepresearcheval/.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

frameworkresearch

Do you own DeepResearchEval?

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.