{"uid":"cap_h2xOovgxeJ1DnqnuhaMGW","slug":"null-coverage-record-quality-audit-date-by-category-pivot-7b766731","name":"Null Coverage Record Quality Audit + Date by Category Pivot","description":"Null coverage — Record quality audit + Date by category pivot: Record quality audit + Date by category pivot for supplied null coverage records (missing_values, total_values). 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-03-017?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","missing_values","total_values"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"total_values":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80},"missing_values":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","total_values":1,"dataset_group":"group-a","missing_values":10},{"date":"2026-10-02","row_id":"row-2","total_values":2,"dataset_group":"group-b","missing_values":20},{"date":"2026-10-03","row_id":"row-3","total_values":3,"dataset_group":"group-a","missing_values":15},{"date":"2026-10-04","row_id":"row-4","total_values":4,"dataset_group":"group-b","missing_values":30}],"maxItems":200,"minItems":1},"field":{"enum":["missing_values","total_values"],"type":"string","default":"missing_values"}}},"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_DXzbNN4rkOoLdPKcSpHh3","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":"Analyzes supplied row data to produce two analytical reports: a null coverage/record quality audit and a date-by-category pivot, using local engines on up to 200 rows.","exampleAgentPrompt":"I have up to 200 rows of data with fields row_id, dataset_group, date, missing_values, and total_values — can you run a null coverage quality audit and a date-by-category pivot on them, focusing on the missing_values field?","exampleUseCases":[{"title":"Dataset completeness audit before pipeline run","prompt":"Before I kick off my ETL pipeline, can you audit this batch of 150 rows for null coverage? Each row has a row_id, dataset_group, date, missing_values, and total_values — I want to know the record quality and see a pivot of missing_values by date and group."},{"title":"Weekly data quality report by category","prompt":"Every week I get a CSV with up to 200 rows of group-level data including missing_values and total_values per date. Can you generate a null coverage audit and a date-by-category pivot so I can see which groups are degrading in quality over time?"},{"title":"Compare null rates across two dataset groups","prompt":"I have two dataset groups — 'group-a' and 'group-b' — with rows spanning October 2026, each with missing_values and total_values counts. Can you run both a record quality audit and a date pivot so I can compare null coverage between the two groups?"}],"resultDescription":"Returns two analytical reports: (1) a record quality audit showing null coverage metrics (missing vs total values, rates) per row or group, and (2) a date-by-category pivot summarizing missing and total values broken down by date and dataset_group. Both reports are computed locally from the supplied rows with no external lookups.","failureModes":["Fewer than 1 row supplied — minimum 1 row required","More than 200 rows submitted — maximum cap exceeded, request rejected","Row missing required fields (row_id, dataset_group, date, missing_values, total_values)","Date field not matching YYYY-MM-DD pattern — validation error","missing_values or total_values outside allowed numeric range","row_id exceeds 80 character limit","field enum value not one of: missing_values, total_values"],"whenToPreferThis":"Choose this endpoint when you have tabular row data with explicit missing_values and total_values counts and need two complementary analytical views — a per-record null quality audit AND a date-by-category pivot — in a single low-cost call. It is ideal for batch data quality checks on up to 200 rows where no external data lookup, prediction, or live enrichment is needed.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-18T00:57:54.418Z","isFirstParty":false,"canonicalSlug":"null-coverage-record-quality-audit-date-by-category-pivot-7b766731"}