AI

Enrich-Retrieve-Rank: Scaling Capability Discovery Beyond In-Context Routing

Researchers have proposed an alternative approach to discovering capabilities within agent ecosystems, which currently rely on in-context routing. This method involves enriching metadata with additional information and then using a retrieve-then-rank pipeline to find the most suitable capability without invoking it online. The authors claim that this approach is more scalable than existing methods and can outperform them at large scales.
Researchers have proposed an alternative approach to discovering capabilities within agent ecosystems, which currently rely on in-context routing. This method involves enriching metadata with additional information and then using a retrieve-then-rank pipeline to find the most suitable capability without invoking it online. The authors claim that this approach is more scalable than existing methods and can outperform them at large scales. --- Why it matters: This matters because current agent ecosystems are growing rapidly, with thousands of components, making discovery increasingly difficult. This research provides a potential solution for scaling up these systems and improving their efficiency. Source: https://arxiv.org/abs/2608.22695

This article was originally published at: https://arxiv.org/abs/2608.22695