Enrich-Retrieve-Rank: Scaling Capability Discovery Beyond In-Context Routing
Quick summary
arXiv:2608.22695v1 Announce Type: cross Abstract: Agent ecosystems now include thousands of MATS components (Models, Agents, Tools, and Skills), yet their discovery still relies on in-context routing. These systems read a registry (names, hints, or descriptions, as context budget permits), pick a candidate, invoke it, and retry on failure. This pattern degrades with scale, and registries are growing fast. We recast capability discovery as search over a registry by defining an offline enrichment step that turns sparse metadata into searchable profiles, and an online retrieve-then-rank pipeline
Key takeaways
- arXiv:2608.22695v1 Announce Type: cross Abstract: Agent ecosystems now include thousands of MATS components (Models, Agents, Tools, and Skills), yet their discovery still relies on in-context routing.
- These systems read a registry (names, hints, or descriptions, as context budget permits), pick a candidate, invoke it, and retry on failure.
- This pattern degrades with scale, and registries are growing fast.
Why it matters
The importance of “Enrich-Retrieve-Rank: Scaling Capability Discovery Beyond In-Context Routing” will be measured by what changes in practice. User behavior, access conditions, verifiable performance and responsible-use outcomes are the signals worth following.
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