CocoaBench: Evaluating Unified Digital Agents in the Wild explores CocoaBench is a new benchmark and scaffold for evaluating unified LLM agents that combine vision, search, and coding capabilities on long-horizon tasks.. Commercial viability score: 6/10 in Unified AI Agents.
Use This Via API or MCP
This route is the stable paper-level surface for citations, viability, references, and downstream handoffs. Use it as the proof layer behind Signal Canvas, workspace creation, and launch-pack generation.
Page Freshness
Canonical route: /paper/cocoabench-evaluating-unified-digital-agents-in-the-wild
This page is showing the last landed evidence receipt and score bundle because the latest proof data is outside the freshness window.
Agent Handoff
Canonical ID cocoabench-evaluating-unified-digital-agents-in-the-wild | Route /paper/cocoabench-evaluating-unified-digital-agents-in-the-wild
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/paper/cocoabench-evaluating-unified-digital-agents-in-the-wildMCP example
{
"tool": "get_paper",
"arguments": {
"arxiv_id": "2604.11201"
}
}source_context
{
"surface": "paper",
"mode": "paper",
"query": "CocoaBench: Evaluating Unified Digital Agents in the Wild",
"normalized_query": "2604.11201",
"route": "/paper/cocoabench-evaluating-unified-digital-agents-in-the-wild",
"paper_ref": "cocoabench-evaluating-unified-digital-agents-in-the-wild",
"topic_slug": null,
"benchmark_ref": null,
"dataset_ref": null
}Constellation, claims, and market context stay visible on the paper proof page even when commercialization rails are held back for incomplete proof receipts.
Research neighborhood
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Preparing verified analysis
Dimensions overall score 6.0
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