{"uid":"cap_7css2dKCdAGZXQjgMqYhX","slug":"aggregation-checks-numeric-row-ordering-date-by-category-pivot-35482b2b","name":"Aggregation Checks — Numeric Row Ordering + Date by Category Pivot","description":"Aggregation checks — Numeric row ordering + Date by category pivot: Numeric row ordering + Date by category pivot for supplied aggregation checks records (source_sum, aggregate_sum). 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-17-122?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","source_sum","aggregate_sum"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"source_sum":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"aggregate_sum":{"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","source_sum":10,"aggregate_sum":1,"dataset_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","source_sum":20,"aggregate_sum":2,"dataset_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","source_sum":15,"aggregate_sum":3,"dataset_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","source_sum":30,"aggregate_sum":4,"dataset_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["source_sum","aggregate_sum"],"type":"string","default":"source_sum"}}},"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_0i8VMS2ysGwOo3fyIU3hP","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 local analytical reports on supplied aggregation-check records: numeric row ordering and date-by-category pivot, for up to 200 rows.","exampleAgentPrompt":"Can you run an aggregation check on these records — I need a numeric row ordering report and a date-by-category pivot for the source_sum field? Here are up to 200 rows with row_id, date, dataset_group, source_sum, and aggregate_sum values.","exampleUseCases":[{"title":"ETL pipeline totals audit","prompt":"I have output from our ETL pipeline with source_sum and aggregate_sum per row — can you sort them by numeric value and also pivot by date and dataset group so I can see where the totals don't line up?"},{"title":"Financial reconciliation row check","prompt":"Here are 150 rows of financial aggregation data with source sums and aggregate sums per category and date. Run a numeric ordering report and a date-by-category pivot on the aggregate_sum field so I can spot any mismatches."},{"title":"Data QA before dashboard publish","prompt":"Before I publish this dashboard, can you validate these aggregation records by running a row-ordering check and a date-by-category pivot on source_sum? I'll paste the rows — there are about 80 of them with group labels and dates."}],"resultDescription":"Returns two independent analytical reports computed locally on the supplied data: (1) a numeric row ordering report ranking rows by the selected field (source_sum or aggregate_sum), and (2) a date-by-category pivot table summarizing the selected field across dataset_group and date dimensions. No external lookups or predictions are made.","failureModes":["Missing required fields (row_id, date, source_sum, aggregate_sum, dataset_group) cause validation errors","Date values not matching YYYY-MM-DD pattern are rejected","More than 200 rows submitted exceeds the maxItems limit","Numeric values outside ±1,000,000,000,000 are rejected","Empty rows array returns an error"],"whenToPreferThis":"Choose this endpoint when you need quick, offline analytical reports on aggregation check data — specifically numeric ordering and date-by-category pivoting — without any external data lookups. It is ideal for ETL auditing, data reconciliation, and QA workflows where you supply up to 200 rows of source_sum and aggregate_sum records and need both reports in a single $0.01 call.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:38:48.975Z","isFirstParty":false,"canonicalSlug":"aggregation-checks-numeric-row-ordering-date-by-category-pivot-35482b2b"}