{"uid":"cap_kvBVWSkWksW2b-gHZ7T56","slug":"return-reason-labelled-jsonl-export-e8e2f94e","name":"Return Reason Labelled JSONL Export","description":"Return reason - Labelled JSONL export: Labelled JSONL export for Return reason. Up to 200 supplied labelled text records. Local dataset tools, evaluation and small naive-Bayes baselines; no hosted model or foundation-model training. One of 25 profiles or calculations across 20 shared operations in this sector. 0.01 USDC includes one bounded labelled jsonl export deliverable.","url":"https://market.datapackvibe.com/x402/assistant-sector-ml-return-reason-jsonl-export?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"records":{"type":"array","items":{"type":"object","required":["id","text","actual"],"properties":{"id":{"type":"string","default":"","maxLength":80,"minLength":1},"text":{"type":"string","default":"","maxLength":1000},"actual":{"enum":["damaged","wrong_item","unwanted","other"],"type":"string"}},"additionalProperties":false},"default":[{"id":"example-0-0","text":"damaged sample document number 0 for this supplied dataset.","actual":"damaged"},{"id":"example-0-1","text":"damaged sample document number 1 for this supplied dataset.","actual":"damaged"},{"id":"example-0-2","text":"damaged sample document number 2 for this supplied dataset.","actual":"damaged"},{"id":"example-1-0","text":"wrong_item sample document number 0 for this supplied dataset.","actual":"wrong_item"},{"id":"example-1-1","text":"wrong_item sample document number 1 for this supplied dataset.","actual":"wrong_item"},{"id":"example-1-2","text":"wrong_item sample document number 2 for this supplied dataset.","actual":"wrong_item"},{"id":"example-2-0","text":"unwanted sample document number 0 for this supplied dataset.","actual":"unwanted"},{"id":"example-2-1","text":"unwanted sample document number 1 for this supplied dataset.","actual":"unwanted"},{"id":"example-2-2","text":"unwanted sample document number 2 for this supplied dataset.","actual":"unwanted"},{"id":"example-3-0","text":"other sample document number 0 for this supplied dataset.","actual":"other"},{"id":"example-3-1","text":"other sample document number 1 for this supplied dataset.","actual":"other"},{"id":"example-3-2","text":"other sample document number 2 for this supplied dataset.","actual":"other"}],"maxItems":200,"minItems":2}}},"responseSchema":null,"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_HhR4TG04zJfbk__SpnA8L","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":"Exports up to 200 labelled return-reason text records in JSONL format for local ML evaluation and naive-Bayes baseline training","exampleAgentPrompt":"Export my 12 labelled return reason records as a JSONL file — I have texts tagged as damaged, wrong_item, unwanted, or other that I want to use for evaluating a naive Bayes classifier locally.","exampleUseCases":[{"title":"Naive Bayes baseline training data","prompt":"I have 80 customer return comments already labelled as damaged, wrong_item, unwanted, or other. Can you export them as a JSONL file so I can train a quick naive Bayes baseline model on my local machine?"},{"title":"Return reason classifier evaluation set","prompt":"Generate a JSONL export from these 50 labelled return reason records — I need them in a clean format to run offline evaluation metrics against my existing text classifier."},{"title":"Small dataset for ML pipeline testing","prompt":"I want to test my local ML data pipeline end-to-end. Can you package these 30 return reason text samples with their labels — damaged, wrong_item, unwanted, or other — into a labelled JSONL export?"}],"resultDescription":"A bounded JSONL export containing up to 200 labelled records, each with an ID, text string, and return reason label (damaged, wrong_item, unwanted, or other), suitable for local dataset tooling, model evaluation, and naive Bayes baseline training.","failureModes":["Fewer than 2 records supplied — minimum input requirement not met","More than 200 records supplied — exceeds maximum item limit","Invalid label value outside the enum (damaged, wrong_item, unwanted, other)","Text field exceeds 1000 character limit per record","Missing required fields (id, text, or actual) on any record","Payment not completed — x402 payment required before delivery"],"whenToPreferThis":"Choose this endpoint when you need a ready-to-use labelled JSONL export of return reason data for offline use cases such as local evaluation, dataset inspection, or training a lightweight naive Bayes classifier — and you do not need hosted model inference or foundation model fine-tuning pipelines.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-18T00:58:35.737Z","isFirstParty":false,"canonicalSlug":"return-reason-labelled-jsonl-export-e8e2f94e"}