# NetIntel Semantic Rank

> NetIntel Semantic Rank is a paid API for AI agents from netintel.dev, paid per call via x402, $0.02/call, status unknown (last checked 2026-09-13).

Ranks a list of text passages by semantic similarity to a query using embedding-based scoring

## Facts

- Endpoint: POST https://netintel.dev/semantic/rank
- Price: $0.02/call
- Payment: x402
- Status: unknown
- Last checked: 2026-09-13
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/netintel-semantic-rank-a5fc259a
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_HmMUz2LTe7lvWhNwHjUn7

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability netintel-semantic-rank-a5fc259a -d '<json body>'
```

Example prompt: Rank these three support snippets by how relevant they are to the question 'how do I reset my password?': 'Use the Forgot Password link to recover your account.', 'Refunds are accepted within 30 days.', 'Contact billing for invoice issues.' — give me a similarity score for each.

## When to prefer this

Use this endpoint when you need to rerank or score a pre-fetched list of text passages against a query using embedding similarity — ideal for RAG pipelines, FAQ matching, customer support routing, or search result reranking. Pay-per-call at $0.02 USDC with no signup; failed/invalid calls are not billed, making it low-risk for agentic workflows.

## Known failure modes

- Empty or missing passage list returns input validation error with no charge
- Query text exceeds token limit causes rejection without billing
- Upstream OpenAI embedding API failure returns server error with no charge
- Malformed JSON body returns 400 validation error without billing
- Too many passages in a single call may exceed limits

## How this service works

Semantic similarity ranking — send a query plus up to 100 candidate texts, get the candidates back ranked by semantic similarity with scores. No vectors, no cosine math, no embedding model to manage: one call, one price, ranked results. Flat $0.02 per call in USDC via x402, no API key. For RAG retrieval, FAQ matching, and search result ordering.

## Output

Returns a JSON object with each input passage ranked by cosine similarity score (0–1) to the query, along with the embedding model used (text-embedding-3-small), number of prompt tokens consumed, embedding dimensions (1536), and whether scores are normalized.

## Request schema (JSON Schema)

```json
{
 "$schema": "https://json-schema.org/draft/2020-12/schema",
 "type": "object",
 "properties": {
  "input": {
   "type": "object",
   "properties": {
    "type": {
     "type": "string",
     "const": "http"
    },
    "method": {
     "type": "string",
     "enum": [
      "POST"
     ]
    },
    "bodyType": {
     "type": "string",
     "enum": [
      "json",
      "form-data",
      "text"
     ]
    },
    "body": {
     "type": "object",
     "properties": {
      "query": {
       "type": "string",
       "description": "The text to rank candidates against."
      },
      "candidates": {
       "type": "array",
       "description": "1-100 candidate strings to rank (64000 chars total on the default model).",
       "items": {
        "type": "string"
       }
      },
      "model": {
       "type": "string",
       "description": "text-embedding-3-small (default) or text-embedding-3-large"
      },
      "top_k": {
       "type": "number",
       "description": "Return only the best N results. Optional."
      },
      "min_score": {
       "type": "number",
       "description": "Drop results scoring below this (-1 to 1). Optional."
      }
     },
     "required": [
      "query",
      "candidates"
     ]
    }
   },
   "required": [
    "type",
    "method",
    "bodyType",
    "body"
   ],
   "additionalProperties": false
  },
  "output": {
   "type": "object",
   "properties": {
    "type": {
     "type": "string"
    },
    "example": {
     "type": "object",
     "properties": {
      "results": {
       "type": "array",
       "description": "Ranked best-first: [{index (original position), score, text}]"
      },
      "method": {
       "type": "string",
       "description": "Always 'embedding_similarity'"
      },
      "provider": {
       "type": "string"
      },
      "model": {
       "type": "string"
      },
      "dimensions": {
       "type": "number"
      },
      "normalized": {
       "type": "boolean"
      },
      "usage": {
       "type": "object",
       "description": "prompt_tokens (input-only)"
      }
     }
    }
   },
   "required": [
    "type"
   ]
  }
 },
 "required": [
  "input"
 ]
}
```

## Response schema (JSON Schema)

```json
{
 "type": "json",
 "example": {
  "model": "text-embedding-3-small",
  "usage": {
   "prompt_tokens": 36
  },
  "method": "embedding_similarity",
  "results": [
   {
    "text": "Use the Forgot Password link to recover your account.",
    "index": 0,
    "score": 0.5361
   },
   {
    "text": "Refunds are accepted within 30 days.",
    "index": 1,
    "score": 0.1399
   }
  ],
  "provider": "openai",
  "dimensions": 1536,
  "normalized": true
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/netintel-semantic-rank-a5fc259a/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from netintel.dev](https://www.zero.xyz/host/netintel.dev/llms.txt)