{"uid":"cap_OpuSoxLZKFAiBlVK9GPL2","slug":"resource-bookings-data-quality-analytics-bundle-af995099","name":"Resource Bookings Data Quality & Analytics Bundle","description":"Resource bookings — Record quality audit + String normalisation + Secondary-measure weighted mean: Record quality audit + String normalisation + Secondary-measure weighted mean for supplied resource bookings records (booked_hours, available_hours). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-operations-09-205?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","team_group","date","booked_hours","available_hours"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"team_group":{"type":"string","default":"","maxLength":80},"booked_hours":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"available_hours":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","team_group":"group-a","booked_hours":10,"available_hours":1},{"date":"2026-10-02","row_id":"row-2","team_group":"group-b","booked_hours":20,"available_hours":2},{"date":"2026-10-03","row_id":"row-3","team_group":"group-a","booked_hours":15,"available_hours":3},{"date":"2026-10-04","row_id":"row-4","team_group":"group-b","booked_hours":30,"available_hours":4}],"maxItems":200,"minItems":1},"field":{"enum":["booked_hours","available_hours"],"type":"string","default":"booked_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_DNpi5BsH_jIXOD92zKMqJ","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":"Runs three analytical reports on resource booking records: record quality audit, string normalisation, and secondary-measure weighted mean — all computed locally on up to 200 supplied rows.","exampleAgentPrompt":"Can you run a data quality audit, string normalisation, and weighted mean report on my resource bookings — here are 4 rows with row_id, team_group, date, booked_hours, and available_hours; use booked_hours as the primary field?","exampleUseCases":[{"title":"Scheduling data quality check","prompt":"I have a batch of 150 resource booking records with team groups, dates, booked_hours and available_hours — can you audit them for quality issues, normalize the team group strings, and give me a weighted mean of booked_hours weighted by available_hours?"},{"title":"Operations team utilisation analysis","prompt":"Run a weighted mean on our booked_hours field across these 80 booking rows, also flag any record quality problems and normalise the team_group strings — the data has row_id, date, team_group, booked_hours, and available_hours columns."},{"title":"Pre-reporting data clean-up","prompt":"Before I send this booking dataset to the dashboard, can you audit the record quality, normalise team group names, and compute a secondary-measure weighted mean on available_hours? I have about 60 rows with the standard fields."}],"resultDescription":"Returns three separate analytical reports in a single response: (1) a record quality audit flagging missing values, format violations, and anomalies; (2) string-normalised versions of text fields like team_group; and (3) a secondary-measure weighted mean of the selected numeric field (booked_hours or available_hours) weighted by the other measure — all computed on the supplied rows without any external lookups.","failureModes":["More than 200 rows submitted — request rejected with row limit error","Missing required fields (row_id, date, booked_hours, available_hours) — validation error returned","Invalid date format (non-YYYY-MM-DD) — pattern validation failure","Field enum value not in ['booked_hours','available_hours'] — schema rejection","Empty rows array — minItems violation","Numeric values outside allowed range — schema error"],"whenToPreferThis":"Choose this endpoint when you need three lightweight analytical operations — data quality auditing, string normalization, and weighted mean computation — on resource booking records in a single low-cost call. It is ideal for pre-processing scheduling or workforce data before reporting, when you want to validate data integrity and compute a utilisation-style weighted average without spinning up a full analytics platform. At $0.01 USDC for all three reports on up to 200 rows, it is economical for batch data hygiene workflows on booking datasets.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-24T12:48:40.941Z","isFirstParty":false,"canonicalSlug":"resource-bookings-data-quality-analytics-bundle-af995099"}