{"uid":"cap_6gCUbXKfnAXSCFMMon7io","slug":"structured-data-observations-record-quality-audit-string-4c4a69e3","name":"Structured Data Observations — Record Quality Audit + String Normalisation + Numeric Row Ordering","description":"Structured data observations — Record quality audit + String normalisation + Numeric row ordering: Record quality audit + String normalisation + Numeric row ordering for supplied structured data observations records (valid_items, total_items). 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-web-08-196?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","site_group","date","valid_items","total_items"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"site_group":{"type":"string","default":"","maxLength":80},"total_items":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"valid_items":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","site_group":"group-a","total_items":1,"valid_items":10},{"date":"2026-10-02","row_id":"row-2","site_group":"group-b","total_items":2,"valid_items":20},{"date":"2026-10-03","row_id":"row-3","site_group":"group-a","total_items":3,"valid_items":15},{"date":"2026-10-04","row_id":"row-4","site_group":"group-b","total_items":4,"valid_items":30}],"maxItems":200,"minItems":1},"field":{"enum":["valid_items","total_items"],"type":"string","default":"valid_items"}}},"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_niunQTEI8MCrtIo5hBTL4","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":"Audits record quality, normalises strings, and orders rows numerically for up to 200 rows of structured observations data containing valid_items and total_items fields, producing 3 independent analytical reports.","exampleAgentPrompt":"Can you run a record quality audit, string normalisation, and numeric row ordering on my structured observations data? I have rows with site_group, date, valid_items, and total_items — up to 50 rows — and I want to analyse the valid_items field.","exampleUseCases":[{"title":"Data quality check on site observations","prompt":"I have about 80 rows of site observation records with site_group, date, valid_items, and total_items columns. Can you audit the record quality, normalise the string fields, and sort the rows by valid_items to help me spot issues?"},{"title":"Validate and clean multi-group dataset","prompt":"We collected observations across several site groups and I'm worried about inconsistent strings and bad records in our dataset. Can you run the three-report check — quality audit, string normalisation, and numeric ordering — on these 120 rows, focusing on total_items?"},{"title":"Pre-processing check before analytics pipeline","prompt":"Before I feed this 200-row observations dataset into our dashboard, can you audit the record quality, normalise the site_group strings, and order everything by valid_items so I know the data is clean?"}],"resultDescription":"Returns three independent analytical reports: (1) a record quality audit identifying missing, null, or malformed values across the supplied rows; (2) a string normalisation report for text fields such as site_group; and (3) a numeric row ordering report ranking rows by the selected numeric field (valid_items or total_items). All reports are generated locally from the supplied data with no external lookups.","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, date, valid_items, total_items) causes rejection","Invalid date format (non YYYY-MM-DD) triggers a schema error","Numeric values outside allowed range (-1e12 to 1e12) are rejected","Invalid field enum value (not valid_items or total_items) causes error","Empty rows array returns an error"],"whenToPreferThis":"Choose this endpoint when you need a bundled three-in-one local data quality analysis — record auditing, string normalisation, and numeric ordering — on tabular structured observation data with valid_items and total_items fields, without requiring external lookups, predictions, or live data. It is cost-effective at $0.01 USDC for all three reports on up to 200 rows. Prefer it over single-report alternatives when you need all three analytical angles in one call.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-28T12:43:06.175Z","isFirstParty":false,"canonicalSlug":"structured-data-observations-record-quality-audit-string-4c4a69e3"}