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PennyRail Text Word Count
x402
PennyRail Text Word Count 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 words and computes text statistics for a given input string
Price / call$0.001
Success—
StatusUnknown
How this service works
Machine-readable settlement service
Output
Returns a JSON object containing text statistics such as word count, character count, and potentially sentence count or other computed metrics derived from the input text string.
Example use cases
Writing length check for blog post
“I just wrote this intro paragraph and need to know if it hits 150 words — can you count the words for me? 'Content marketing is one of the most effective strategies for building brand awareness. By consistently publishing high-quality articles...'”
SEO meta description word count
“Check the word count on this meta description so I know if it's within limits: 'Discover the best hiking trails in the Pacific Northwest, from scenic coastal paths to challenging mountain routes suitable for all skill levels.'”
Student essay word count verification
“My essay submission needs to be exactly 500 words — can you count the words in this text and tell me if I'm over or under? 'The industrial revolution transformed society in profound ways, reshaping everything from labor practices to urban development...'”
Technical details
Endpoint
POSThttps://pennyrail.vercel.app/api/p/nano/text.stats--word-countWhen to prefer
Choose this endpoint when you need a fast, cheap, programmatic word count or text statistics computation via a pay-per-call micropayment model. It is ideal for agents that process many small text snippets on demand without needing a full NLP pipeline or heavyweight text analysis service.
Side effects
- Missing 'input' field returns a 400 or validation error
- Empty string input may return zero counts or an error
- Very large text inputs may hit payload size limits
- Payment failure (x402) if USDC not provided or insufficient balance
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | string |
Output
Schema · Response
{
"type": "object",
"additionalProperties": true
}Tags
x402
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