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KiHustle Keyword Proximity Analyzer
x402
KiHustle Keyword Proximity Analyzer is a paid API for AI agents from kihustle.tech, paid per call via x402, $0.002/call, status unknown (last checked 2026-09-14).
Analyzes the proximity (closeness) between two specified keywords within a given text passage.
Price / call$0.002
Success—
StatusUnknown
How this service works
Kostenlose Guides, Solo-Playbooks und Artikel zu KI, Automation und Side Hustles — für Menschen, die mit echten Systemen online Einkommen aufbauen wollen. Transparent finanziert über faire Affiliate-Links.
Output
Returns a JSON object indicating the computed proximity result between the two specified keywords within the provided text, along with a success status flag. The exact numeric or categorical proximity score is represented in the 'result' field.
Example use cases
SEO keyword co-occurrence check
“I want to know how close the terms 'AI' and 'side hustle' are in this paragraph: 'Using AI tools for your side hustle can dramatically reduce the time you spend on repetitive tasks and boost your online income.' Can you run a proximity analysis on those two words?”
Content quality audit for article drafts
“I'm reviewing a blog post draft and need to check how near the keywords 'automation' and 'passive income' are throughout this text: 'Automation is a core driver of passive income strategies for modern digital entrepreneurs who want to work smarter.' Tell me the proximity result.”
Ad copy keyword density check
“Before I publish this ad copy, can you analyze how close the words 'freelance' and 'earnings' appear in it? Here's the text: 'Freelance professionals are unlocking new earnings potential by leveraging AI-powered workflows in their daily routines.'”
Technical details
Endpoint
POSThttps://kihustle.tech/bot-bazaar/api/v1/keyword-proximity-analyzerWhen to prefer
Use this endpoint when you need a lightweight, low-cost computation to determine how closely two specific keywords appear within a text passage — especially useful for SEO content auditing, keyword co-occurrence analysis, or content optimization pipelines. Prefer it over full NLP libraries or semantic similarity APIs when you only need positional or syntactic proximity between two discrete terms.
Side effects
- Missing required fields (text, word_a, or word_b) returns an error or malformed response
- Very short text with neither keyword present may return a zero-proximity or null result
- Ambiguous or multi-token keyword inputs may not match expected tokens in the text
- Non-English text may produce unreliable proximity measurements given the site's multilingual context
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| text | string | |
| word_a | string | |
| word_b | string |
Output
Schema · Response
{
"type": "json",
"example": {
"result": "processed",
"status": "success"
}
}Tags
x402
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