{"uid":"cap_wV4gWBwBZcs7i8eyt_ABY","slug":"null-coverage-analytics-record-quality-audit-string-normalisation-a7f14ade","name":"Null Coverage Analytics — Record Quality Audit, String Normalisation & Trailing Mean Series","description":"Null coverage — Record quality audit + String normalisation + Trailing mean series: Record quality audit + String normalisation + Trailing mean series 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-03-199?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"},"window":{"type":"integer","default":2,"maximum":200,"minimum":2}}},"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_EFK8NBygpuZxDWdXVgD-2","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 local analytical reports (record quality audit, string normalisation, and trailing mean series) on null coverage data rows containing missing_values and total_values fields.","exampleAgentPrompt":"Can you run a null coverage audit on my dataset? I have 4 rows: row-1 on 2026-10-01 for group-a with 10 missing out of 1 total, row-2 on 2026-10-02 for group-b with 20 missing out of 2 total, row-3 on 2026-10-03 for group-a with 15 missing out of 3 total, and row-4 on 2026-10-04 for group-b with 30 missing out of 4 total — analyse the missing_values field with a window of 2 and give me the record quality audit, string normalisation, and trailing mean series reports.","exampleUseCases":[{"title":"Daily data pipeline completeness check","prompt":"I've got 50 rows from yesterday's pipeline with date, dataset_group, missing_values, and total_values — can you run the full null coverage audit on them, normalise the string fields, and compute the trailing mean of missing_values with a window of 7?"},{"title":"Dataset group quality comparison","prompt":"Can you audit the record quality and run a trailing mean series with window size 3 on these 20 rows of null coverage data across my 'sales' and 'inventory' groups so I can see which group has the most data completeness issues?"},{"title":"Rolling average of data gaps over time","prompt":"I want to track how my missing_values trend has changed over the past month — here are 30 daily rows for group-a, please compute the trailing mean series for missing_values with a window of 5 and include the string normalisation and quality audit reports too."}],"resultDescription":"Three analytical reports for up to 200 supplied null coverage rows: (1) a record quality audit summarising completeness and issues per row, (2) a string normalisation report for text fields, and (3) a trailing mean series for the selected numeric field (missing_values or total_values) using the specified rolling window. All computed locally with no external lookups.","failureModes":["Fewer than 1 or more than 200 rows submitted — returns validation error","Missing required fields (row_id, dataset_group, date, missing_values, total_values) on any row — row rejected or error returned","Date field not matching YYYY-MM-DD pattern — validation error","Window value less than 2 or greater than 200 — validation error","Numeric values outside allowed range (-1e12 to 1e12) — validation error","Payment not completed via x402 protocol — request not processed"],"whenToPreferThis":"Choose this endpoint when you need three simultaneous local analytical reports on null coverage data in a single call — specifically record quality auditing, string normalisation, and rolling/trailing mean computation — without requiring any external data lookups or predictions. It is cost-effective at $0.01 USDC for up to 200 rows and three reports. Prefer it over building custom analytics when you have structured null coverage records with date, group, missing_values, and total_values fields and need a quick completeness and trend summary.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-18T00:58:20.792Z","isFirstParty":false,"canonicalSlug":"null-coverage-analytics-record-quality-audit-string-normalisation-a7f14ade"}