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Delx Commerce — Catalog Intent Rank
x402
Delx Commerce — Catalog Intent Rank is a paid API for AI agents from commerce.delx.ai, paid per call via x402, $0.001/call, status unknown (last checked 2026-10-01).
Ranks a list of candidate tool names by relevance to a natural language intent query, returning scored results in order of match quality.
Price / call$0.001
Success—
StatusUnknown
How this service works
Pay-per-result APIs for agents. No signup. Exact price. Verifiable delivery. USDC on Base + Solana via x402.
Output
A JSON array of ranked tool name objects, each with a numeric relevance score (e.g. 1 for highest match, 0 for no match), ordered from most to least relevant to the provided intent query.
Example use cases
Dynamic tool routing for agent orchestration
“I have these candidate tools my agent might call: util_image_resize, util_text_summarize, util_sentiment_score. The user just asked to 'make this article shorter.' Which tool should I route to first — rank them all by relevance for me.”
Catalog search before calling an API
“Before I make an API call, I want to know which of these tools — util_geocode_address, util_timezone_lookup, util_distance_calc — is the best match for the intent 'find what timezone a city is in.' Score each one.”
Reducing tool set before LLM context injection
“I have 10 candidate tools to pass into my LLM context but want to trim to the most relevant ones for the query 'check if a domain name exists.' Here's the list: util_dns_lookup, util_whois_query, util_ip_geolocate, util_port_scan, util_http_ping, util_ssl_check, util_email_validate, util_gwei_to_wei, util_kelly_binary, util_base64_encode. Rank them by relevance score so I can keep only the top ones.”
Technical details
Endpoint
POSThttps://commerce.delx.ai/api/v1/x402/catalog-intent-rank?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need lightweight, pay-per-call intent-to-tool matching without standing up your own embedding or ranking infrastructure. It is especially useful in agent orchestration pipelines where the candidate set changes dynamically and you want to avoid passing a large tool catalog into LLM context. Prefer it over embedding-based DIY solutions when you need a fast, cheap, verifiable single call with no API key or signup required.
Side effects
- Empty candidates array returns an empty ranked list
- Vague or ambiguous query may produce uniform low scores across all candidates
- Unrecognized tool names are still scored but may receive 0 if no semantic signal is found
- Malformed request body missing required 'query' field returns an error
- Payment failure or insufficient USDC balance blocks the request via x402 protocol
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| query | string | Natural language intent query |
| candidates | array | Candidate tool_name list |
Output
Schema · Response
{
"type": "json",
"example": {
"ranked": [
{
"score": 1,
"tool_name": "util_kelly_binary"
},
{
"score": 0,
"tool_name": "util_dns_lookup"
},
{
"score": 0,
"tool_name": "util_gwei_to_wei"
}
],
"schema": "delx/util-catalog-intent-rank/v1"
}
}Tags
x402
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