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PennyRail Text Statistics
x402
PennyRail Text Statistics 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).
Computes statistical metrics (character count, word count, sentence count, readability scores, etc.) for a given input text string
Price / call$0.001
Success—
StatusUnknown
How this service works
Machine-readable settlement service
Output
A JSON object containing computed statistical properties of the input text, likely including word count, character count, sentence count, paragraph count, and readability scores (e.g. Flesch-Kincaid grade level). The exact fields may vary but the response schema is open-ended (additionalProperties: true).
Example use cases
Blog post readability check
“I just finished writing this article intro — can you tell me how many words and sentences it has and give me a readability score? Here it is: 'Artificial intelligence is transforming the way we work, communicate, and create. From healthcare to finance, its impact is felt across every sector of modern life.'”
Student essay length verification
“Can you check this essay excerpt and tell me the exact word count, character count, and sentence count? Here's the text: 'Climate change represents one of the most pressing challenges of our time. Scientists warn that without immediate action, global temperatures could rise by two degrees Celsius by 2050.'”
Marketing copy complexity analysis
“I need to know if this tagline is too complex for a general audience — can you run text stats on it and give me the readability metrics? The text is: 'Empowering entrepreneurs through scalable, data-driven, AI-augmented business solutions that optimize operational efficiency and accelerate market penetration.'”
Technical details
Endpoint
POSThttps://pennyrail.vercel.app/api/p/nano/text.stats--proven-text-statsWhen to prefer
Choose this endpoint when you need lightweight, pay-per-call text statistics without standing up your own NLP pipeline. Ideal for agents that occasionally need word counts, readability scores, or sentence-level metrics on arbitrary text, and want a metered micro-payment model rather than a subscription. Not suited for deep semantic analysis, sentiment classification, or entity extraction.
Side effects
- Empty or missing 'input' field returns a validation error
- Extremely long text strings may exceed processing limits or time out
- Malformed JSON body returns a 400-level error
- Payment failure (x402) if USDC balance is insufficient
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | string |
Output
Schema · Response
{
"type": "object",
"additionalProperties": true
}Tags
x402
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