{"uid":"cap_b_8jM3jaIB2Z1FEGH3NZ1","slug":"whatchuneed-tempest-proofreader-33be3c86","name":"Whatchuneed Tempest Proofreader","description":"320+ pay-per-call API endpoints across accommodation, LLM, code execution, crypto, medical, finance, and more. One API, one payment. Powered by x402 protocol.","url":"https://whatchuneed.vercel.app/api/tempest/proofread","method":"POST","headers":{},"bodySchema":{"type":"object","required":["text"],"properties":{"text":{"type":"string"}}},"responseSchema":{"type":"object","properties":{"corrected":{"type":"string"},"corrections":{"type":"array","items":{"type":"object","properties":{"type":{"type":"string"},"original":{"type":"string"},"position":{"type":"integer"},"corrected":{"type":"string"}}}},"error_count":{"type":"integer"}}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.15","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.15/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.15","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.15","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_mfsZktfqi426ElkEJzCcX","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.15","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Proofreads submitted text and returns a corrected version with a detailed list of individual corrections and error count","exampleAgentPrompt":"Can you proofread this for me and show me exactly what was wrong: 'The quik brown fox jumpd over the lasy dog and it's freind'?","exampleUseCases":[{"title":"Email quality check before sending","prompt":"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.'"},{"title":"Blog post grammar correction","prompt":"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.'"},{"title":"User-generated content moderation pipeline","prompt":"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!'"}],"resultDescription":"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.","failureModes":["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"],"whenToPreferThis":"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.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-14T19:00:44.131Z","isFirstParty":false}