{"uid":"cap_wHeQ2ng4tcCClDTrgSBE9","slug":"schema-conformity-record-quality-audit-date-by-category-pivot-3df1384e","name":"Schema Conformity — Record Quality Audit + Date by Category Pivot","description":"Schema conformity — Record quality audit + Date by category pivot: Record quality audit + Date by category pivot for supplied schema conformity records (valid_records, checked_records). 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-02-017?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","valid_records","checked_records"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"dataset_group":{"type":"string","default":"","maxLength":80},"valid_records":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"checked_records":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","dataset_group":"group-a","valid_records":10,"checked_records":1},{"date":"2026-10-02","row_id":"row-2","dataset_group":"group-b","valid_records":20,"checked_records":2},{"date":"2026-10-03","row_id":"row-3","dataset_group":"group-a","valid_records":15,"checked_records":3},{"date":"2026-10-04","row_id":"row-4","dataset_group":"group-b","valid_records":30,"checked_records":4}],"maxItems":200,"minItems":1},"field":{"enum":["valid_records","checked_records"],"type":"string","default":"valid_records"}}},"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_bAQvYNxN4YcEUt_5KCllA","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 schema conformity records: a record quality audit and a date-by-category pivot, for up to 200 rows of valid_records and checked_records data.","exampleAgentPrompt":"Can you run a record quality audit and a date-by-category pivot on our schema conformity data? I have up to 50 rows with fields row_id, dataset_group, date, valid_records, and checked_records — analyze the valid_records field.","exampleUseCases":[{"title":"Data pipeline quality review","prompt":"I have daily schema conformity logs for two dataset groups — can you audit the record quality and pivot valid_records by date and group? Here are 30 rows with row_id, dataset_group, date, valid_records, and checked_records."},{"title":"Monthly conformity trend analysis","prompt":"Run a record quality audit and a date-by-category pivot on these 120 schema conformity records across multiple dataset groups — I want to see how checked_records vary by date and category over the past month."},{"title":"Data validation health check","prompt":"We're reviewing our ETL pipeline's conformity stats. Can you generate both a quality audit and a date-pivot report for these 80 rows of valid_records and checked_records data, grouped by dataset_group?"}],"resultDescription":"Returns two independent analytical reports: (1) a record quality audit summarizing conformity metrics such as validity rates, anomalies, and completeness across rows, and (2) a date-by-category pivot table breaking down the selected field (valid_records or checked_records) by date and dataset_group. Both reports are computed locally from the supplied data with no external lookups.","failureModes":["Input array exceeds 200 rows — request rejected","Missing required fields (row_id, date, valid_records, checked_records) — validation error","Invalid date format (must be YYYY-MM-DD) — schema rejection","Numeric values out of bounds (±1 trillion limit) — validation failure","Empty rows array — minimum 1 item required","Invalid field enum value — must be 'valid_records' or 'checked_records'"],"whenToPreferThis":"Choose this endpoint when you need two combined analytical reports — a record quality audit and a date-by-category pivot — on schema conformity data in a single low-cost API call. Ideal for data engineers or QA pipelines that track valid vs. checked record counts across dataset groups over time and need quick, local analytics without external dependencies. Best for datasets up to 200 rows where cost efficiency ($0.01 for two reports) and no-side-effect computation are priorities.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-17T00:47:10.596Z","isFirstParty":false,"canonicalSlug":"schema-conformity-record-quality-audit-date-by-category-pivot-3df1384e"}