Brand Search

1. Pick the right search tool

Both tools return the same thing: website references, each with summary brand metadata and a screenshot. They differ in what goes in.

search_brands: a natural-language query goes in. What the user or the agent asked for becomes the query. Ex: search_brands("dark brutalist developer tools"), search_brands("warm pastel skincare landing pages"). search_similar_brands: the submission_id of a completed extraction goes in, and that site's nearest visual neighbours come out. Ex: you extracted linear.app, got back its submission_id, and pass that id in.

search_brands

Build each query knowing what you're looking for — style, layout, palette, motion, tone — and write it by the guidelines below.

• Always follow the original intent of the user's or agent's prompt. Don't add anything they didn't ask for, and don't translate what they did. If the prompt says "monochromatic", the query is monochromatic, not "black and white".
• Inspect every returned result as described in step 3 before selecting references.

A prompt that's just a vibe gets a query that's just the vibe: search_brands("dreamy editorial skincare, calm and warm", top_k=6).

When the user names a style or movement, carry the word exactly as they wrote it. The search is what interprets style terms, including ones nothing is formally tagged with — swapping in your own synonym would decide what the search was supposed to decide. search_brands("vintage feeling clothing brand site") keeps "vintage" even though the corpus's official tag for that register is "Retro": the user said vintage, so vintage is what gets searched. Same discipline behind search_brands("y2k web aesthetic for a music label") and search_brands("swiss international style studio portfolio").