{"uid":"cap_vgadZvbMoFj1CHTc3MKF_","slug":"shot-schedules-string-normalisation-and-secondary-measure-weighted-mean-7ddef8bb","name":"Shot Schedules String Normalisation and Secondary-Measure Weighted Mean","description":"Shot schedules — String normalisation + Secondary-measure weighted mean: String normalisation + Secondary-measure weighted mean for supplied shot schedules records (planned_hours, actual_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-creative-13-034?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","asset_group","date","planned_hours","actual_hours"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"asset_group":{"type":"string","default":"","maxLength":80},"actual_hours":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"planned_hours":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","asset_group":"group-a","actual_hours":1,"planned_hours":10},{"date":"2026-10-02","row_id":"row-2","asset_group":"group-b","actual_hours":2,"planned_hours":20},{"date":"2026-10-03","row_id":"row-3","asset_group":"group-a","actual_hours":3,"planned_hours":15},{"date":"2026-10-04","row_id":"row-4","asset_group":"group-b","actual_hours":4,"planned_hours":30}],"maxItems":200,"minItems":1},"field":{"enum":["planned_hours","actual_hours"],"type":"string","default":"planned_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_MnLg9HR95_JZ12whCCRC_","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 asset_group strings and computes a secondary-measure weighted mean for shot schedule records containing planned_hours and actual_hours fields.","exampleAgentPrompt":"Normalise the asset group strings in my shot schedule and compute the secondary-measure weighted mean for planned_hours — I have rows for group-a and group-b across dates 2026-10-01 to 2026-10-04, with planned hours of 10, 20, 15, 30 and actual hours of 1, 2, 3, 4.","exampleUseCases":[{"title":"Production schedule hours audit","prompt":"I've got a shot schedule with 50 rows for our film production — asset groups have inconsistent capitalisation and spacing. Can you normalise the group names and compute the weighted mean of planned_hours so I can see where budget time is concentrated?"},{"title":"Actual vs planned hours weighted summary","prompt":"Here's our shot schedule data for Q4 with 120 rows across groups alpha and beta. Normalise the asset_group strings and give me the secondary-measure weighted mean for actual_hours so I can report burn rate to the producer."},{"title":"VFX team schedule data cleanup","prompt":"Our VFX scheduling export has messy group labels and I need string normalisation plus a weighted mean of planned_hours for the 80 shots — can you run both reports on this data?"}],"resultDescription":"Returns two analytical reports: (1) normalised asset_group string values across all supplied rows, and (2) a secondary-measure weighted mean computed for the selected field (planned_hours or actual_hours), covering up to 200 rows with no external lookups or predictions.","failureModes":["More than 200 rows submitted — request rejected, must split into batches","Missing required fields (row_id, date, planned_hours, actual_hours) — validation error","Date strings not matching YYYY-MM-DD pattern — schema validation failure","All values for the weighted field are null — cannot compute meaningful weighted mean","Invalid field enum value (not planned_hours or actual_hours) — schema rejection"],"whenToPreferThis":"Choose this endpoint when you need both string normalisation of categorical group labels AND a weighted mean computation on shot schedule hour data in a single call. It is best suited for offline batch analysis of up to 200 rows of shot schedule records where no live data lookup or external prediction is required, and when you want two analytical outputs (normalisation + weighted mean) for a flat $0.01 USDC cost.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-22T00:49:26.214Z","isFirstParty":false,"canonicalSlug":"shot-schedules-string-normalisation-and-secondary-measure-weighted-mean-7ddef8bb"}