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DatabricksCharlie Klein, Bryan Smith7 min readintermediate

The Web Search Your Agent Inherited Isn't Good Enough

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Summary

Omnigent is a unified agent definition layer that lets you write an LLM‑agent once and run it on any harness (Claude Code, Codex, raw API). By plugging Nimble’s specialized web‑search API into the Omnigent web_search builtin, you get consistent, deeper, and cheaper web results – benchmark accuracy jumps from 46 % to 71 % and search cost halves. All model calls go through Databricks Foundation Mod…

  • Define an agent (model, tools, policies) once in Omnigent → eliminates duplicated harness‑specific implementations.
  • Route all model calls through Databricks Foundation Model APIs for unified cost tracking and governance.
  • Swap the web‑search provider via a single config line; using Nimble improves retrieval depth (JS, pagination) and reuses learned retrieval paths.
  • Nimble’s Search API + Web Search Agents raise LLM benchmark accuracy from 46 % to 71 % and cut token‑cost of web search by ~50 %.

Enterprise LLM agents often need up‑to‑date external signals. Without a shared search layer each harness’s built‑in search is inconsistent, costly, and ungoverned, forcing engineers to rebuild the same logic three times. A unified definition and a specialized search backend give reliable data, lowe…

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