{"uid":"cap_KvKFv0G1gzHUbbo67VYRe","slug":"one-engine-text-paragraph-tokenizer-84801e72","name":"ONE Engine Text Paragraph 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/t8?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":"0.01","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":"$0.01/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_0etkd-UqMBbz5PjKTO-0K","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.01","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Splits a text input (up to 50,000 characters) into tokenized paragraph segments via a pay-per-call API.","exampleAgentPrompt":"Can you split this article into paragraph-level tokens? Here's the text: 'Artificial intelligence is transforming industries worldwide. Companies are investing heavily in machine learning. However, challenges around data privacy remain significant. Regulatory frameworks are still catching up.'","exampleUseCases":[{"title":"Document chunking for RAG pipeline","prompt":"I need to split this 10,000-word research paper into paragraph-level chunks so I can index each one separately for my retrieval system — here's the full text."},{"title":"Preprocessing legal contract text","prompt":"Can you tokenize this legal contract paragraph by paragraph? I want each paragraph as a separate unit so I can analyze them individually."},{"title":"Blog post paragraph segmentation","prompt":"Break this blog post into its individual paragraphs as tokens so I can run sentiment analysis on each section separately. Here's the full article text."}],"resultDescription":"Returns a JSON object containing the input text segmented into paragraph-level tokens, likely as an array of paragraph strings or token objects representing each paragraph unit from the original text.","failureModes":["Text exceeds 50,000 character limit — input will be rejected or truncated","Payment failure via x402 on Base — call will not proceed without valid USDC payment","Empty or missing 'text' field — required field validation error","Malformed JSON request body — 400 bad request","Network timeout on Cloudflare Workers edge — transient error requiring retry"],"whenToPreferThis":"Choose this endpoint when you need a lightweight, low-cost ($0.01 USDC) paragraph-level tokenization of text up to 50,000 characters, especially in autonomous agent workflows that already use x402 micropayment infrastructure on Base. It is ideal for preprocessing steps in document pipelines, RAG chunking, or any NLP workflow requiring paragraph segmentation without needing a full-scale NLP library.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-02T12:41:00.316Z","isFirstParty":false,"canonicalSlug":"one-engine-text-paragraph-tokenizer-84801e72"}