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PennyRail Token Count (Proven)
x402
PennyRail Token Count (Proven) 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 number of tokens in a given text input using a verified, settlement-ready method accessible via micropayment
Price / call$0.001
Success—
StatusUnknown
How this service works
Machine-readable settlement service
Output
Returns an object containing the verified token count for the submitted text input, indicating how many tokens the text resolves to under the tokenization scheme used by the service.
Example use cases
Pre-flight LLM context check
“Before I send this document to GPT-4, can you count how many tokens it contains so I know if it fits within the 8k context window? Here's the text: [document content]”
Prompt cost estimation
“I'm building a chatbot and need to know exactly how many tokens this system prompt uses so I can estimate API costs accurately — can you count the tokens in this prompt text for me?”
Batch text size auditing
“I have this article draft and need to verify its token count before publishing it as training data — can you give me a proven token count for the text?”
Technical details
Endpoint
POSThttps://pennyrail.vercel.app/api/p/nano/text.token-count--proven-token-countWhen to prefer
Choose this endpoint when you need a trustworthy, settlement-backed token count — particularly in contexts where verifiability or micropayment-gated auditability matters, such as billing verification, LLM pre-flight checks, or agentic pipelines where token usage needs to be independently confirmed rather than estimated client-side.
Side effects
- Missing or malformed 'input' object returns a validation error
- Empty text input may return a zero count or an error
- Payment failure or insufficient USDC balance blocks the request
- Malformed JSON body results in a 400-level error
- Oversized input beyond service limits may be rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object |
Output
Schema · Response
{
"type": "object",
"additionalProperties": true
}Tags
x402
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