KiHustle N-Gram Frequency Analyzer

x402

KiHustle N-Gram Frequency Analyzer is a paid API for AI agents from kihustle.tech, paid per call via x402, $0.002/call, status unknown (last checked 2026-10-13).

Analyzes text to compute the frequency of n-grams (contiguous sequences of n words or characters) within the input string.

Price / call$0.002

Seller volume →—

Success—

StatusUnknown

How this service works

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Output

Returns a JSON object with a 'result' and 'status' field confirming successful processing; expected to include computed n-gram frequencies for the submitted text, though the full frequency map detail depends on the implementation.

Example use cases

SEO keyword phrase repetition check

“I want to know how often each 2-word phrase appears in this blog post draft so I can spot over-used keyword pairs. Here's the text: 'Content marketing drives traffic. Content marketing builds authority. Quality content marketing is essential for SEO.' — run a bigram frequency analysis on it.”

Readability pattern detection in prose

“Can you find the most repeated 4-word sequences in this product description? I'm trying to catch awkward repetition before publishing. Text: 'Our innovative smart home device connects your smart home seamlessly. The smart home device is energy-efficient and our smart home device ships free.'”

Corpus phrase profiling for NLP training

“Run a trigram frequency count on this sample training text so I can see which 3-word sequences dominate: 'machine learning models require large datasets. Large datasets improve machine learning models. Machine learning models generalize better with diverse data.'”

Technical details

Endpoint

POSThttps://kihustle.tech/bot-bazaar/api/v1/ngram-frequency-analyzer?utm_source=zero.xyz

When to prefer

Choose this endpoint when you need a lightweight, pay-per-call n-gram frequency extraction on arbitrary text without setting up a local NLP pipeline. It is well-suited for quick ad-hoc analysis, content auditing, or feeding frequency data into a downstream agent step. Prefer it over a full NLP library when you want a simple API call rather than hosting your own text processing stack.

Side effects

Missing or empty 'text' field returns an error or empty result
Invalid or non-integer 'n' value may cause a 400 error
n value larger than the number of tokens in the text may return empty frequencies
Very large text inputs may time out or hit payload limits
Malformed JSON request body returns a parsing error

Input

Schema · Request body

Field	Type	Description
n	integer
text	string

Output

Schema · Response

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

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