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Agent Search Query Builder
x402
Agent Search Query Builder is a paid API for AI agents from agent-product-normalizer.vercel.app, paid per call via x402, $0.0015/call, status unknown (last checked 2026-09-18).
Compresses a verbose user task description into concise, search-engine-ready query variants for downstream web or product searches
Price / call$0.0015
Success—
StatusUnknown
How this service works
Compress a verbose user task into search-engine-ready query variants
Output
The endpoint returns one or more compact, search-engine-optimized query strings derived from the input task. These variants are suitable for direct use in web search engines, product catalogs, or knowledge bases, reducing token overhead and improving retrieval precision for downstream agent steps.
Example use cases
E-commerce product search optimization
“I have this rambling product request from a user: 'I want a coffee maker that brews quickly, has a built-in grinder, makes a full pot, is easy to clean, and works with regular ground coffee too.' Can you compress that into tight search query variants I can send to a product search engine?”
Research task to web search pipeline
“My agent needs to search the web for this: 'I want to learn about how central banks use interest rate adjustments to control inflation without triggering a recession, especially recent examples from the US and EU.' Turn that into compact search queries I can actually use.”
Support ticket to knowledge base search
“I have this long user support complaint — 'My app keeps crashing when I try to open the settings menu after updating to version 3.2 on Android 13, but only when I have dark mode enabled' — compress it into search queries so I can look up matching known issues in our knowledge base.”
Technical details
Endpoint
GEThttps://agent-product-normalizer.vercel.app/api/v1/make-search-queryWhen to prefer
Choose this endpoint when an agent has received a long, unstructured user request and needs to issue web or product searches efficiently without wasting tokens on verbose queries. It is particularly well-suited for multi-step agent workflows where a retrieval step follows user input, and compactness and precision of the search terms directly impact downstream result quality. Prefer it over manual keyword extraction when the task is ambiguous or multi-faceted and multiple query variants are valuable.
Side effects
- Missing required 'task' query parameter returns a validation error
- Extremely short or content-free task strings may produce low-quality or generic queries
- Tasks exceeding the 20,000 character limit will be rejected
- Non-English or highly domain-specific jargon may produce poorly generalized queries
- Network or service unavailability on the Vercel deployment returns 5xx errors
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Tags
x402
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