{"uid":"cap_wYB-WicZT7QTXkGY0p3AU","slug":"transcript-preparation-numeric-row-ordering-explicit-missing-value-fill-dcdb4376","name":"Transcript Preparation: Numeric Row Ordering + Explicit Missing-Value Fill","description":"Transcript preparation — Numeric row ordering + Explicit missing-value fill: Numeric row ordering + Explicit missing-value fill for supplied transcript preparation records (transcribed_minutes, source_minutes). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-writing-12-124?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","document_group","date","transcribed_minutes","source_minutes"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"document_group":{"type":"string","default":"","maxLength":80},"source_minutes":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"transcribed_minutes":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","document_group":"group-a","source_minutes":1,"transcribed_minutes":10},{"date":"2026-10-02","row_id":"row-2","document_group":"group-b","source_minutes":2,"transcribed_minutes":20},{"date":"2026-10-03","row_id":"row-3","document_group":"group-a","source_minutes":3,"transcribed_minutes":15},{"date":"2026-10-04","row_id":"row-4","document_group":"group-b","source_minutes":4,"transcribed_minutes":30}],"maxItems":200,"minItems":1},"field":{"enum":["transcribed_minutes","source_minutes"],"type":"string","default":"transcribed_minutes"},"method":{"enum":["zero","mean","median"],"type":"string","default":"median"}}},"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_0kPa2O8ZKtkVcWceuigs8","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":"Sorts transcript preparation rows numerically and fills missing transcribed_minutes or source_minutes values using zero, mean, or median imputation — up to 200 rows, two reports per call.","exampleAgentPrompt":"I have up to 50 rows of transcript preparation data with some missing transcribed_minutes values — can you sort them numerically by row and fill those nulls using median imputation, then give me two analytical reports?","exampleUseCases":[{"title":"Clean media transcription log gaps","prompt":"I've got a batch of 120 transcript records from our podcast archive with some null source_minutes values — sort them numerically and fill those missing values using mean imputation, and give me the two reports."},{"title":"Prepare interview transcripts for QA review","prompt":"Before I run QA on these interview transcripts, can you order the rows numerically and replace any missing transcribed_minutes with zero? I have about 80 rows across two document groups."},{"title":"Normalize court transcript minute data","prompt":"I need to clean up my court transcript dataset — it has gaps in source_minutes across around 150 rows. Sort them by row number and use median to fill the missing values, then return the two summary reports."}],"resultDescription":"Returns two analytical reports on the submitted transcript preparation rows: one covering numeric row ordering and one covering the explicit missing-value fill applied to the specified field (transcribed_minutes or source_minutes). Reports reflect local computation only — no external lookups or predictions.","failureModes":["More than 200 rows submitted — request rejected with validation error","Missing required fields (row_id, date, transcribed_minutes, source_minutes) on any row — schema validation failure","Invalid date format (not YYYY-MM-DD) — pattern validation error","Invalid field or method enum value — schema rejection","Empty rows array — minItems violation"],"whenToPreferThis":"Choose this endpoint when you have transcript preparation data (transcribed_minutes and/or source_minutes per row) and need both numeric row ordering and systematic null imputation in a single low-cost call. It is best suited for batch cleaning of up to 200 rows with no need for live data, external lookups, or prediction — just deterministic local sorting and fill computation with two bundled output reports.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-29T13:17:11.499Z","isFirstParty":false,"canonicalSlug":"transcript-preparation-numeric-row-ordering-explicit-missing-value-fill-dcdb4376"}