{"uid":"cap_GSnlYuZ2DOOxOoHtsc3tn","slug":"one-engine-text-to-paragraphs-tokenizer-1d749722","name":"ONE Engine Text-to-Paragraphs Tokenizer","description":"Low-cost pay-per-call utility APIs for autonomous agents using x402 on Base.","url":"https://one-search.one-engine.workers.dev/v3/text-token/paragraphs/t7?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","required":["text"],"properties":{"text":{"type":"string","description":"Text up to 50000 characters"}}},"responseSchema":{"type":"object","additionalProperties":true},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.0065","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":"$0.0065/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.0065","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.0065","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_5q0H0hLDWhlcy18t_yi_W","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.0065","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Splits and tokenizes input text (up to 50,000 characters) into paragraph-level token segments via a pay-per-call API.","exampleAgentPrompt":"Can you split this article into paragraph-level token chunks so I can see how many tokens each paragraph contains? Here's the text: 'The global economy has faced unprecedented challenges in recent years. Central banks around the world have responded with a variety of monetary tools...'","exampleUseCases":[{"title":"Preprocessing article for LLM context window","prompt":"I have this long news article and I need to break it into paragraph-level token segments so I can feed each chunk into an LLM without exceeding context limits — here's the full text."},{"title":"Counting tokens per paragraph in a report","prompt":"Can you tokenize this quarterly earnings report paragraph by paragraph so I can see the token count for each section? I'll paste the full report text now."},{"title":"Segmenting scraped web content","prompt":"I just scraped this webpage's body text and I need it split into paragraph tokens so my pipeline can process each paragraph individually — here's the raw text content."}],"resultDescription":"Returns a JSON object containing the input text segmented into paragraph-level units with associated token information, enabling downstream NLP tasks or LLM preprocessing.","failureModes":["Text exceeds 50,000 character limit — request rejected","Empty or missing 'text' field — validation error returned","Payment not provided or insufficient USDC — 402 Payment Required response","Malformed JSON body — 400 Bad Request","Cloudflare Worker timeout for very large text near the character limit"],"whenToPreferThis":"Choose this endpoint when you need a lightweight, pay-per-call tokenization and paragraph segmentation service for text up to 50,000 characters, especially within x402-enabled agent pipelines on Base. It is ideal for preprocessing documents before LLM ingestion or NLP tasks where per-paragraph token awareness is needed.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-02T12:43:38.873Z","isFirstParty":false,"canonicalSlug":"one-engine-text-to-paragraphs-tokenizer-7ee283a3"}