{"uid":"cap_Xi0x1shpecfjdHnGDs8yC","slug":"null-coverage-analytics-string-normalisation-grouped-numeric-summary-a9e2bdab","name":"Null Coverage Analytics: String Normalisation + Grouped Numeric Summary","description":"Null coverage — String normalisation + Grouped numeric summary: String normalisation + Grouped numeric summary 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-03-023?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_N56qpb5FeLMQLPn4u0Lsd","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 null/missing value coverage records by normalizing string fields and producing grouped numeric summaries across up to 200 rows, generating 2 reports per call.","exampleAgentPrompt":"Can you analyze this batch of null coverage records — I have up to 50 rows with dataset groups like 'group-a' and 'group-b', each with missing_values and total_values counts — and give me a string normalization report plus a grouped numeric summary for the missing_values field?","exampleUseCases":[{"title":"Data quality audit by dataset group","prompt":"I have a list of 80 dataset records tagged with groups like 'finance' and 'ops', each with a date, row ID, number of missing values, and total values. Can you normalize the string fields and give me a grouped numeric summary of missing_values across those groups?"},{"title":"Monitoring null rates across data pipelines","prompt":"We're tracking null coverage daily across two pipeline groups. Here are 120 rows with row IDs, dates, group names, and missing/total value counts — can you run the string normalization and grouped summary on the total_values field so I can see how each group compares?"},{"title":"Pre-analysis data completeness check","prompt":"Before I run my model, I need to understand my data completeness. I've got 30 rows each with a dataset group, date, missing_values, and total_values. Can you produce both reports — the string normalization and the grouped numeric summary — for the missing_values column?"}],"resultDescription":"Returns two analytical reports: (1) a string normalization report for the supplied row/group/date fields, and (2) a grouped numeric summary of either missing_values or total_values broken down by dataset_group — covering up to 200 input rows. No external lookups or predictions are included; all analysis uses local computation on supplied data.","failureModes":["Input array exceeds 200 rows — rejected with validation error","Missing required fields (row_id, dataset_group, date, missing_values, total_values) on any row causes rejection","Invalid date format (not YYYY-MM-DD) triggers pattern validation failure","row_id exceeds 80 characters or is empty — validation error","Field enum value not 'missing_values' or 'total_values' — rejected","Empty rows array (minItems: 1 violated) causes failure","Payment of 0.01 USDC not supplied — x402 payment required error"],"whenToPreferThis":"Choose this endpoint when you have tabular null-coverage or data-completeness records (with missing_values and total_values) and need both string normalization and grouped numeric aggregation in a single low-cost call. Ideal for data quality audits, pipeline monitoring, and pre-analysis completeness checks where you supply the data locally and don't need live data fetches, predictions, or external enrichment. Best for batch sizes up to 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-18T00:54:56.091Z","isFirstParty":false,"canonicalSlug":"null-coverage-analytics-string-normalisation-grouped-numeric-summary-a9e2bdab"}