{"uid":"cap_qCUW2VhrCfvcFL0COKiIW","slug":"data-freshness-record-quality-audit-string-normalisation-daily-sum-aed90362","name":"Data Freshness Record Quality Audit + String Normalisation + Daily Sum Series","description":"Data freshness — Record quality audit + String normalisation + Daily sum series: Record quality audit + String normalisation + Daily sum series for supplied data freshness records (age_minutes, record_count). 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-06-198?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","age_minutes","record_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"age_minutes":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"record_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","age_minutes":10,"record_count":1,"dataset_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","age_minutes":20,"record_count":2,"dataset_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","age_minutes":15,"record_count":3,"dataset_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","age_minutes":30,"record_count":4,"dataset_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["age_minutes","record_count"],"type":"string","default":"age_minutes"}}},"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_j3w0fRsx6W9msVbm6A6_d","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 on supplied data freshness records: a record quality audit, string normalisation, and a daily sum series for age_minutes or record_count fields.","exampleAgentPrompt":"Can you run a record quality audit, string normalisation, and daily sum series on my data freshness records? I have rows with date, row_id, dataset_group, age_minutes, and record_count — up to about 50 rows — and I want the analysis on the age_minutes field.","exampleUseCases":[{"title":"Pipeline freshness quality audit","prompt":"I have 80 rows of data freshness logs with date, row_id, dataset_group, age_minutes, and record_count fields. Can you audit them for record quality issues, normalise the dataset_group strings, and give me a daily sum series for age_minutes?"},{"title":"Daily record count aggregation","prompt":"Run a quality audit, string normalisation, and daily sum series on my 150 freshness records — I want the series computed on the record_count field so I can see how record volumes accumulate day by day."},{"title":"Data monitoring dashboard prep","prompt":"I'm preparing a dashboard and need three reports on my freshness dataset: a record quality audit, normalised strings for the group labels, and a daily aggregate of age_minutes. Here are 40 rows with date, row_id, dataset_group, age_minutes, and record_count."}],"resultDescription":"Three independent analytical reports: (1) a record quality audit flagging issues in the supplied rows, (2) a string normalisation report for text fields like dataset_group, and (3) a daily sum series for the selected numeric field (age_minutes or record_count), all computed locally with no external lookups.","failureModes":["More than 200 rows submitted — request will be rejected or truncated","Missing required fields (row_id, dataset_group, date, age_minutes, record_count) causes validation error","Invalid date format (not YYYY-MM-DD) triggers pattern validation failure","Field selector not one of 'age_minutes' or 'record_count' causes enum validation error","Empty rows array returns error due to minItems:1 constraint"],"whenToPreferThis":"Choose this endpoint when you have up to 200 data freshness records and need three bundled analytical reports — quality audit, string normalisation, and daily sum series — in a single low-cost call ($0.01 USDC), without requiring any live lookups, predictions, or external data enrichment. Prefer it over separate analytics services when all three report types are needed together on the same dataset.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-24T19:17:20.785Z","isFirstParty":false,"canonicalSlug":"data-freshness-record-quality-audit-string-normalisation-daily-sum-aed90362"}