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Whatchuneed Tempest Proofreader
x402
Whatchuneed Tempest Proofreader is a paid API for AI agents from whatchuneed.vercel.app, paid per call via x402, $0.15/call, status unknown (last checked 2026-09-14).
Proofreads submitted text and returns a corrected version with a detailed list of individual corrections and error count
Price / call$0.15
Success—
StatusUnknown
How this service works
320+ pay-per-call API endpoints across accommodation, LLM, code execution, crypto, medical, finance, and more. One API, one payment. Powered by x402 protocol.
Output
Returns a JSON object containing: a 'corrected' string with all errors fixed, a 'corrections' array where each item includes the error type, the original erroneous fragment, its character position in the original text, and the corrected replacement, plus an 'error_count' integer summarizing the total number of corrections made.
Example use cases
Email quality check before sending
“Before I send this email to our client, proofread it and tell me every mistake: 'Dear Mr. Smyth, thankyou for you're patiance with are delayed shipment. We appologize for any inconvienence this may of caused.'”
Blog post grammar correction
“I just finished writing this blog post intro and I want you to proofread it and fix all the errors, then show me a list of what you changed: 'Their are many reasons why entrepeneurs fail in there first year of busines, and most of them is avoidable with the right preperation.'”
User-generated content moderation pipeline
“Run a proofread on this product review text and give me the corrected version plus the full error count so I can flag it if there are more than 5 mistakes: 'This prodcut is amazng, i recieved it yesturday and it work perfecly out of the box. Definately recomend!'”
Technical details
Endpoint
POSThttps://whatchuneed.vercel.app/api/tempest/proofreadWhen to prefer
Choose this endpoint when you need both a corrected version of text AND a structured, position-indexed list of individual corrections — ideal for pipelines that need to audit, log, or display specific changes rather than just receive a clean output. It is pay-per-call with no subscription overhead, making it suitable for sporadic or agent-driven proofreading tasks. Prefer it over LLM-based prompting when you want deterministic, structured correction metadata rather than a free-form rewrite.
Side effects
- Empty or missing 'text' field returns validation error
- Extremely long text may hit payload size limits
- Non-English text may produce unreliable corrections or no corrections
- Payment failure (HTTP 402) if USDC balance is insufficient
- Service unavailability returns 5xx error with no correction data
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| textrequired | string |
Output
Schema · Response
| Field | Type | Description |
|---|---|---|
| corrected | string | |
| corrections | array | |
| error_count | integer |
Tags
x402
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