{"uid":"cap_6_ppA2xME5vO2daYus10k","slug":"editorial-turnaround-adjacent-row-changes-two-measure-correlation-48641727","name":"Editorial Turnaround Adjacent Row Changes & Two-Measure Correlation","description":"Editorial turnaround — Adjacent row changes + Two-measure correlation: Adjacent row changes + Two-measure correlation for supplied editorial turnaround records (draft_hours, review_hours). 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-news-15-158?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","channel_group","date","draft_hours","review_hours"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"draft_hours":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"review_hours":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"channel_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","draft_hours":10,"review_hours":1,"channel_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","draft_hours":20,"review_hours":2,"channel_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","draft_hours":15,"review_hours":3,"channel_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","draft_hours":30,"review_hours":4,"channel_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["draft_hours","review_hours"],"type":"string","default":"draft_hours"}}},"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_e7QerQ_0SWO-G9WyMyW2a","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":"Computes adjacent row changes and two-measure correlation for editorial turnaround data (draft_hours, review_hours) supplied by the caller, returning two analytical reports for up to 200 rows.","exampleAgentPrompt":"Can you analyze my editorial turnaround data for adjacent row-to-row changes and the correlation between draft_hours and review_hours? I have 4 records: row-1 on 2026-10-01 for group-a with draft_hours=10 and review_hours=1, row-2 on 2026-10-02 for group-b with draft_hours=20 and review_hours=2, row-3 on 2026-10-03 for group-a with draft_hours=15 and review_hours=3, and row-4 on 2026-10-04 for group-b with draft_hours=30 and review_hours=4 — focus the field analysis on draft_hours.","exampleUseCases":[{"title":"Day-over-day draft time shift analysis","prompt":"I have a week's worth of editorial records across group-a and group-b channels — can you compute the adjacent row changes in draft_hours and also show me how draft_hours and review_hours correlate? Here are my 7 rows with dates from 2026-10-01 to 2026-10-07, row IDs row-1 through row-7, draft hours ranging from 8 to 35, and review hours from 1 to 6."},{"title":"Channel group correlation comparison","prompt":"Can you run the two-measure correlation and adjacent row change reports on my editorial turnaround data for group-a and group-b? I have 10 rows from 2026-09-01 to 2026-09-10, and I want the field analysis focused on review_hours so I can see how review time tracks against drafting time."},{"title":"Editorial throughput trend reporting","prompt":"Please analyze these 15 editorial turnaround records — dates from 2026-08-01 through 2026-08-15, mixed across channel groups alpha and beta, with draft_hours and review_hours recorded for each row — run the adjacent row changes and the two-measure correlation reports with draft_hours as the primary field."}],"resultDescription":"Returns two analytical reports: (1) an adjacent row changes report showing how draft_hours or review_hours shift between consecutive rows, and (2) a two-measure correlation report quantifying the statistical relationship between draft_hours and review_hours across the supplied dataset of up to 200 rows. All computation is performed locally on the supplied data with no external lookups.","failureModes":["More than 200 rows submitted — request rejected due to maxItems constraint","Missing required fields (row_id, date, channel_group, draft_hours, review_hours) on any row — validation error","Invalid date format not matching YYYY-MM-DD pattern — schema validation failure","Invalid field enum value (not 'draft_hours' or 'review_hours') — rejected","Empty rows array (minItems=1 violated) — schema error","All review_hours or draft_hours are null — correlation may be undefined or not computable"],"whenToPreferThis":"Choose this endpoint when you have editorial turnaround records with draft_hours and review_hours and need both sequential row-change analysis and a two-measure correlation in a single call, at very low cost ($0.01 USDC for both reports). Prefer it over generic analytics tools when your dataset is already structured with row_id, date, and channel_group fields and you need fast, offline statistical reports without external data dependencies or predictions.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T18:37:31.435Z","isFirstParty":false,"canonicalSlug":"editorial-turnaround-adjacent-row-changes-two-measure-correlation-48641727"}