Published September 16, led by Jiacheng Miao and James Zou. The idea: a paper's methods, code and data become tools an agent can run, instead of a PDF it reads. Each paper becomes three things: executable tools that wrap its methods, resources holding the manuscript and datasets, and prompts that encode the workflow. Every tool is tested before it ships. Numbers from the paper as reported by MarkTechPost: for AlphaGenome it built 22 tools in about 45 minutes for $14, all passing. On a set of 100 biomedical papers, 74 converted and 593 of 599 proposed tools passed validation. On 300 questions it scored 91.2 percent at about $0.20 a query. Code is MIT-licensed at github.com/jmiao24/Paper2Agent. Why it matters: the same trick works on any internal runbook or script library you own. What to watch: 26 of 100 papers failed to convert, so it is not magic.
AI tool turns any paper into an 'agent' that can collaborate and answer queries