{"uid":"cap_KjV27y_s_8HaD8PyojJTh","slug":"editorial-turnaround-string-normalisation-numeric-row-ordering-453f5dba","name":"Editorial Turnaround String Normalisation & Numeric Row Ordering","description":"Editorial turnaround — String normalisation + Numeric row ordering: String normalisation + Numeric row ordering 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-15-025?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_uKymG1xLPO-rYNjpmNYyB","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":"Normalises string fields and orders rows numerically for editorial turnaround records containing draft_hours and review_hours data, producing two analytical reports for up to 200 rows.","exampleAgentPrompt":"I have 4 editorial turnaround records for October 2026 — row-1 (group-a, draft 10h, review 1h), row-2 (group-b, draft 20h, review 2h), row-3 (group-a, draft 15h, review 3h), row-4 (group-b, draft 30h, review 4h) — can you normalise the string fields and sort them by draft_hours, giving me two reports?","exampleUseCases":[{"title":"Ranking editorial teams by draft speed","prompt":"I've got 50 editorial rows from this quarter with channel groups, dates, draft hours and review hours — can you normalise the channel group names and rank all rows by draft_hours so I can see which teams turn drafts around fastest?"},{"title":"Cleaning review hour data for reporting","prompt":"I need to tidy up 120 editorial turnaround records before our monthly report — please normalise the string fields and produce a numerically ordered view sorted by review_hours so the data is clean and ranked for the stakeholder deck."},{"title":"Comparing channel groups by turnaround time","prompt":"We have editorial records across group-a and group-b spanning the last 200 working days with draft and review hours — normalise the strings and give me two ordered reports sorted by draft_hours so I can compare channel group performance."}],"resultDescription":"Two analytical reports: one with string-normalised editorial turnaround records (cleaned channel_group and string fields) and one with rows ordered numerically by the selected field (draft_hours or review_hours), covering up to 200 input rows processed entirely with local analytical engines.","failureModes":["More than 200 rows submitted — request rejected due to maxItems constraint","Missing required fields (row_id, channel_group, date, draft_hours, review_hours) — validation error","Invalid date format not matching YYYY-MM-DD pattern — schema validation failure","Invalid field enum value other than draft_hours or review_hours — rejected","Empty rows array — minItems violation","Numeric values outside the allowed range — schema rejection"],"whenToPreferThis":"Choose this endpoint when you have up to 200 editorial turnaround records (with draft_hours and review_hours) that need both string field normalisation and numeric row ordering in a single call, and you want two independent reports without any live data lookup, prediction, or external action. It is particularly suited for pre-reporting data cleaning of editorial workflow datasets where channel group label consistency and time-ranked ordering are both required.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T18:38:35.078Z","isFirstParty":false,"canonicalSlug":"editorial-turnaround-string-normalisation-numeric-row-ordering-453f5dba"}