{"uid":"cap_QvBTmLN3MFLirFSWwQHOi","slug":"null-coverage-record-quality-audit-with-iqr-outlier-flags-248757c7","name":"Null Coverage Record Quality Audit with IQR Outlier Flags","description":"Null coverage — Record quality audit + IQR outlier flags: Record quality audit + IQR outlier flags 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-03-014?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_n_CiESWvGCOxmLYK_2U2F","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":"Performs two analytical reports on up to 200 null-coverage records: a record quality audit and IQR-based outlier flagging for missing_values or total_values fields.","exampleAgentPrompt":"Can you run a record quality audit and IQR outlier check on my null coverage data? Here are my rows — each has a row_id, dataset_group, date, missing_values, and total_values — I want the analysis on the missing_values field across up to 50 rows.","exampleUseCases":[{"title":"Data pipeline completeness audit","prompt":"I have a batch of 120 null coverage records from our ETL pipeline with row IDs, dataset groups, dates, and missing/total value counts — can you run a record quality audit and flag any IQR outliers on the missing_values field so I can catch bad data before it hits production?"},{"title":"Anomaly detection in dataset group coverage","prompt":"We track null coverage across multiple dataset groups daily and I want to know which rows have statistically unusual missing_values counts — can you do an IQR outlier analysis and quality audit on these 80 records grouped by dataset_group?"},{"title":"Monthly data quality review","prompt":"At the end of each month I review our data completeness metrics — can you audit these 200 null coverage records for quality issues and flag any outliers in total_values using IQR so I can spot which dates or groups had abnormal coverage?"}],"resultDescription":"Returns two independent analytical reports: (1) a record quality audit summarizing data issues across the supplied null coverage rows, and (2) IQR-based outlier flags identifying which rows have statistically anomalous values in the selected field (missing_values or total_values). Results are computed locally with no external lookups.","failureModes":["Missing required fields (row_id, date, missing_values, total_values) returns validation error","More than 200 rows submitted exceeds batch limit","Invalid date format not matching YYYY-MM-DD pattern causes rejection","Null or out-of-range numeric values outside ±1 trillion boundary fail schema validation","Empty rows array returns error due to minItems:1 constraint"],"whenToPreferThis":"Choose this endpoint when you need both a record-level quality audit AND IQR outlier detection on null coverage data in a single call, processing up to 200 rows at once. It is best suited for batch data quality workflows where you have pre-collected missing_values and total_values metrics and want statistical anomaly flags without any external data enrichment or prediction.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-18T00:58:10.893Z","isFirstParty":false,"canonicalSlug":"null-coverage-record-quality-audit-with-iqr-outlier-flags-248757c7"}