# KiHustle Word Embedding Similarity Proxy

> KiHustle Word Embedding Similarity Proxy is a paid API for AI agents from kihustle.tech, paid per call via x402, $0.002/call, status unknown (last checked 2026-09-13).

Computes word or text embedding similarity by proxying a text input through a vector embedding model and returning a similarity result

## Facts

- Endpoint: POST https://kihustle.tech/nexus/api/v1/word-embed-similarity-proxy
- Price: $0.002/call
- Payment: x402
- Status: unknown
- Last checked: 2026-09-13
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/kihustle-word-embedding-similarity-proxy-7061126f
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_zH4fD-LzSXJlTwQ4PLl6-

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 kihustle-word-embedding-similarity-proxy-7061126f -d '<json body>'
```

Example prompt: Can you compute the semantic similarity for this text: 'machine learning automates pattern recognition' and tell me how similar it is to related concepts?

## When to prefer this

Choose this endpoint when you need a lightweight, pay-per-call semantic text similarity computation without setting up your own embedding infrastructure. It is suitable for single-text embedding lookups or similarity proxying at low cost ($0.002/call). Prefer alternatives if you need batch processing, a specific named embedding model with guaranteed output dimensions, or raw embedding vectors rather than a similarity result.

## Known failure modes

- Empty or missing 'text' field returns an error or undefined behavior
- Text that is too long may be truncated or rejected
- Underlying embedding model unavailability causes proxy failure
- Non-string input types may cause schema validation errors
- Network timeout if the proxied embedding service is slow

## How this service works

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## Output

Returns a JSON object with a 'result' field indicating the processed similarity outcome and a 'status' field confirming success. The exact similarity score or embedding vector details depend on the underlying model, but the response confirms whether the text was successfully processed and compared.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "text": {
   "type": "string"
  }
 }
}
```

## Response schema (JSON Schema)

```json
{
 "type": "json",
 "example": {
  "result": "processed",
  "status": "success"
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/kihustle-word-embedding-similarity-proxy-7061126f/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from kihustle.tech](https://www.zero.xyz/host/kihustle.tech/llms.txt)
