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Set config.mode: "agentic" on POST /v1/search when queries read like a person describing what they want rather than a keyword phrase. An LLM decomposes the query into a structured plan — brands, retailers, category, gender, age, condition, price range, colors, and product attributes — then runs multiple structured sub-searches and merges them into one ranked result list. 
import Channel3 from "@channel3/sdk";

const client = new Channel3(); // reads CHANNEL3_API_KEY from env

const results = await client.products.search({
  query: "waterproof trail running shoes for wide feet under $120",
  config: { mode: "agentic" },
});

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Default vs. agentic

Default search already does some entity extraction on your query. Agentic search goes much further:
  • Rich filter extraction — extracts constraints across all SearchFilters: price, brands, websites, gender, age, condition, availability, colors, and category.
  • Multiple queries — plans and runs several searches, then intelligently picks the quality results from across them.
  • Structured attribute enrichment — parses implied categories and features out of the query and deterministically filters products down to only those that match the attributes.

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Everything else works the same

The request and response shapes are identical to default mode. Explicit filters are combined with what the planner extracts, and pagination via next_page_token works as usual.