{"uid":"cap_ozwDZ8pk8GXPVVsueYb_s","slug":"null-coverage-analytics-record-quality-audit-string-normalisation-aef2ce0f","name":"Null Coverage Analytics — Record Quality Audit, String Normalisation & Adjacent Row Changes","description":"Null coverage — Record quality audit + String normalisation + Adjacent row changes: Record quality audit + String normalisation + Adjacent row changes for supplied null coverage records (missing_values, total_values). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-analytics-03-200?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_zgmLoCI87l7wIqZPqEAUE","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 three independent analytical reports (record quality audit, string normalisation, and adjacent row changes) on up to 200 rows of null-coverage data containing missing_values and total_values fields.","exampleAgentPrompt":"Can you run the null-coverage triple report on these 50 rows — record quality audit, string normalisation, and adjacent row changes — using the missing_values field? I have row IDs, dataset groups, dates, and both missing and total value counts ready to send.","exampleUseCases":[{"title":"Dataset completeness audit for ETL pipeline","prompt":"I have 120 rows from our ETL pipeline with row IDs, dataset group names, dates in YYYY-MM-DD format, and missing_values and total_values counts. Can you run a record quality audit, string normalisation check, and adjacent row changes report on the missing_values field for all of them?"},{"title":"Daily null-coverage drift detection","prompt":"Here are 80 daily null-coverage records across two dataset groups — 'group-a' and 'group-b' — with missing and total value counts. Run the adjacent row changes and record quality audit reports on the total_values field so I can see if anything shifted significantly day over day."},{"title":"String consistency check across dataset groups","prompt":"I've got 60 null-coverage rows with dataset group labels that might have inconsistent capitalisation or formatting. Can you run the string normalisation report alongside the record quality audit on my missing_values data so I can clean it up before loading into the warehouse?"}],"resultDescription":"Returns three independent analytical reports: (1) a record quality audit summarising completeness and validity issues across supplied rows, (2) a string normalisation report identifying and standardising inconsistencies in text fields such as dataset_group, and (3) an adjacent row changes report highlighting value shifts between consecutive rows for the selected field (missing_values or total_values). All analysis is performed locally on supplied data with no external lookups.","failureModes":["Exceeding 200 rows causes rejection — trim input to at most 200 rows","Missing required fields (row_id, dataset_group, date, missing_values, total_values) causes validation failure","Dates not matching YYYY-MM-DD pattern are rejected","Numeric values outside ±1,000,000,000,000 are rejected","Empty rows array (minItems:1 not met) causes schema error","Payment failure via x402 protocol blocks execution"],"whenToPreferThis":"Choose this endpoint when you need a bundled, cost-effective analytical pass over null-coverage records — specifically when you want all three of record quality auditing, string normalisation, and adjacent row change detection in a single $0.01 call on up to 200 rows. Prefer it over building custom scripts when you want reproducible, engine-consistent reports across dataset groups without any external API calls, live lookups, or professional assessments involved.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-18T00:58:12.504Z","isFirstParty":false,"canonicalSlug":"null-coverage-analytics-record-quality-audit-string-normalisation-aef2ce0f"}