{"uid":"cap_6q-4lTPSiLZqvRkRuosqU","slug":"dataset-storage-record-quality-audit-date-by-category-pivot-55da128b","name":"Dataset Storage Record Quality Audit + Date by Category Pivot","description":"Dataset storage — Record quality audit + Date by category pivot: Record quality audit + Date by category pivot for supplied dataset storage records (used_mb, row_count). 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-analytics-18-017?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","used_mb","row_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"used_mb":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"row_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","used_mb":10,"row_count":1,"dataset_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","used_mb":20,"row_count":2,"dataset_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","used_mb":15,"row_count":3,"dataset_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","used_mb":30,"row_count":4,"dataset_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["used_mb","row_count"],"type":"string","default":"used_mb"}}},"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_z_xEgbkP9JateFtAcdp8-","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 two analytical reports on supplied dataset storage records: a record quality audit and a date-by-category pivot table, for up to 200 rows.","exampleAgentPrompt":"Can you run a record quality audit and a date-by-category pivot on my dataset storage records? I have rows with fields like used_mb and row_count across groups 'group-a' and 'group-b' from October 2026 — analyze the used_mb field.","exampleUseCases":[{"title":"Storage usage quality check","prompt":"I have 150 storage records with used_mb and row_count values across several dataset groups — can you audit them for data quality issues and also give me a pivot of used_mb by date and dataset group?"},{"title":"Monthly dataset growth pivot","prompt":"Here are my dataset storage records from the last quarter with fields date, dataset_group, used_mb, and row_count. Can you pivot the row_count by date and category so I can see how each group has grown, and also flag any quality problems in the records?"},{"title":"Data pipeline health report","prompt":"Before I hand off these storage records to my data team, can you run a quality audit on all 200 rows and produce a date-by-category pivot on used_mb so I can spot any anomalies by group and date?"}],"resultDescription":"Two analytical reports: (1) a record quality audit highlighting missing, null, or anomalous values in the supplied storage rows, and (2) a date-by-category pivot table aggregating the selected metric (used_mb or row_count) across dataset groups and dates. Both reports are computed locally from the supplied data with no external lookups.","failureModes":["More than 200 rows submitted — request will be rejected or truncated","Missing required fields (row_id, dataset_group, date, used_mb, row_count) cause validation errors","Date fields not matching YYYY-MM-DD pattern will fail schema validation","Invalid field selector (not 'used_mb' or 'row_count') causes an error","Empty rows array returns an error"],"whenToPreferThis":"Choose this endpoint when you have up to 200 dataset storage records with used_mb and row_count metrics and need both a data quality audit and a date-by-category pivot in a single low-cost call. It is ideal for pre-processing or health-checking storage datasets before ingestion into a pipeline, and when no external data lookup or prediction is required.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T12:45:45.727Z","isFirstParty":false,"canonicalSlug":"dataset-storage-record-quality-audit-date-by-category-pivot-55da128b"}