{"uid":"cap_27AkQmaF20C2chUxiiCSh","slug":"newbotlabor-text-chunker-c31564cb","name":"NewBotLabor Text Chunker","description":"Pay-per-call utilities for autonomous agents, paid with x402 (USDC on Base; no account, no API key).","url":"https://newbotlabor--254ecdfcc2de11f19b541607ee4eb77e.web.val.run/api/text/chunk?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"mode":{"enum":["markdown","plain"],"type":"string","description":"default auto-detect"},"text":{"type":"string","description":"plain text or markdown, max 1 MB"},"overlap":{"type":"integer","minimum":0,"description":"default 150, must be < maxChars/2"},"maxChars":{"type":"integer","maximum":8000,"minimum":200,"description":"default 1500"}}},"responseSchema":{"type":"json","example":{"mode":"markdown","chunks":[{"text":"# Guide","chars":7,"index":0,"endOffset":7,"headingPath":["Guide"],"startOffset":0,"approxTokens":2},{"text":"## Install\n\nRun the installer. Then restart.\n\n```sh\nnpm i x402\n```","chars":66,"index":1,"endOffset":75,"headingPath":["Guide","Install"],"startOffset":9,"approxTokens":17}],"overlap":150,"maxChars":1500,"inputChars":75,"totalChars":73,"totalChunks":2,"approxTokens":19}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.002","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":"$0.002/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.002","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.002","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_P7UHmyTWdvtCJLjhufJy5","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.002","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Splits plain text or markdown into overlapping chunks with heading-path metadata, paid per-call via x402 USDC on Base.","exampleAgentPrompt":"Chunk this markdown document into pieces of at most 1500 characters with 150-character overlap, preserving heading context so I can index each chunk for RAG retrieval.","exampleUseCases":[{"title":"RAG pipeline document ingestion","prompt":"Take this 50,000-character markdown documentation page and split it into chunks of up to 2000 characters with 200-character overlap — I need each chunk to carry its heading path so I can store them in my vector database."},{"title":"LLM context window preparation","prompt":"I have a long plain-text article that's too big for a single LLM call — break it into chunks of at most 1000 characters with 100-character overlap so I can feed them one at a time."},{"title":"Token-budget-aware text segmentation","prompt":"Split this markdown README into chunks no bigger than 800 characters with 50-character overlap, using markdown mode so heading structure is preserved, and tell me the approximate token count for each chunk."}],"resultDescription":"A JSON object containing an array of chunk objects, each with its text content, character length, start/end byte offsets, approximate token count, zero-based index, and heading path (breadcrumb of parent headings for markdown mode). Also returns summary fields: total chunks, total characters, input characters, overlap, maxChars, and detected or specified mode.","failureModes":["overlap >= maxChars/2 returns a validation error","text exceeding 1 MB is rejected","invalid mode enum value returns a 400 error","missing required 'text' field returns a 400 error","payment failure or insufficient USDC balance returns a 402 Payment Required response"],"whenToPreferThis":"Choose this endpoint when you need deterministic, structure-aware text chunking with heading-path metadata for markdown documents, especially in RAG or embedding pipelines where preserving section context matters. It is ideal for agents that cannot install local libraries and need a pay-per-call, zero-account-setup solution via x402 USDC micropayments on Base.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-22T12:39:48.690Z","isFirstParty":false,"canonicalSlug":"newbotlabor-text-chunker-c31564cb"}