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PennyRail Word Frequency Counter
x402
PennyRail Word Frequency Counter is a paid API for AI agents from pennyrail.vercel.app, paid per call via x402, $0.001/call, status unknown (last checked 2026-09-14).
Counts the frequency of each word in a given text input, returning word counts as structured data
Price / call$0.001
Success—
StatusUnknown
How this service works
Machine-readable settlement service
Output
A JSON object mapping each unique word (lowercased or as parsed) to its integer count of occurrences in the input text. The response schema is open (additionalProperties: true), so the keys are the words and the values are their frequencies.
Example use cases
SEO keyword density analysis
“Analyze this blog post draft and tell me the frequency of every word so I can check my keyword density: 'Content marketing is essential. Content drives traffic. Great content builds trust.'”
Academic text vocabulary audit
“Count every word's frequency in this paragraph from my essay so I can see if I'm overusing certain terms: 'The theory of evolution explains biological diversity. Evolution occurs through natural selection. Natural selection acts on variation.'”
Customer review term extraction
“Take this batch of customer feedback text and count how many times each word appears so I can spot the most commonly mentioned topics: 'great service fast delivery good packaging fast shipping great quality.'”
Technical details
Endpoint
POSThttps://pennyrail.vercel.app/api/p/nano/text.word-frequency--count-words-frequencyWhen to prefer
Use this endpoint when you need a quick, cheap ($0.001 USDC) server-side word frequency count without running local NLP libraries. Prefer it over client-side solutions when you need a reproducible, stateless computation in a pipeline or agent workflow. It's well-suited for small-to-medium text snippets where spinning up a full NLP stack is overkill.
Side effects
- Empty input string may return an empty object or an error
- Very large text inputs may hit payload size limits or timeout
- Missing 'input' field returns a 400-level validation error
- Non-string values for 'input' may cause a parsing error
- Punctuation handling may vary — words may or may not be stripped of punctuation
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | string |
Output
Schema · Response
{
"type": "object",
"additionalProperties": true
}Tags
x402
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