{"uid":"cap_C04eMqatEvhFAJz2fbu7Z","slug":"price-basket-observations-record-quality-audit-numeric-interval-filter-00b32cca","name":"Price Basket Observations — Record Quality Audit & Numeric Interval Filter","description":"Price basket observations — Record quality audit + Numeric interval filter: Record quality audit + Numeric interval filter for supplied price basket observations records (item_price, quantity_weight). 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-economics-07-008?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","region","date","item_price","quantity_weight"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"region":{"type":"string","default":"","maxLength":80},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"item_price":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"quantity_weight":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","region":"group-a","row_id":"row-1","item_price":10,"quantity_weight":1},{"date":"2026-10-02","region":"group-b","row_id":"row-2","item_price":20,"quantity_weight":2},{"date":"2026-10-03","region":"group-a","row_id":"row-3","item_price":15,"quantity_weight":3},{"date":"2026-10-04","region":"group-b","row_id":"row-4","item_price":30,"quantity_weight":4}],"maxItems":200,"minItems":1},"field":{"enum":["item_price","quantity_weight"],"type":"string","default":"item_price"},"maximum":{"type":"number","default":100,"maximum":1000000000000,"minimum":-1000000000000},"minimum":{"type":"number","default":0,"maximum":1000000000000,"minimum":-1000000000000}}},"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_wyPUtXQ_PH9w8UTQgqo6M","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 data quality and filters by numeric interval for up to 200 rows of price basket observations (item_price, quantity_weight), returning two analytical reports per call.","exampleAgentPrompt":"Can you run a record quality audit and numeric interval filter on my price basket observations? I have 50 rows with item_price and quantity_weight fields — filter item_price between 0 and 500, and flag any quality issues in the records.","exampleUseCases":[{"title":"Price data quality audit for retail survey","prompt":"I have 120 rows of regional price basket data collected from a retail survey — each row has a row_id, region, date, item_price, and quantity_weight. Can you audit the quality of these records and also filter out any item_price values that fall outside the range of 5 to 250?"},{"title":"Flagging abnormal quantity weights in supply chain","prompt":"I need to check my quantity_weight data for anomalies — I have 80 rows of supply chain price basket observations and I want a quality audit plus a filter to show only records where quantity_weight is between 0.1 and 100."},{"title":"Cleaning economics dataset before analysis","prompt":"Before I run my economics analysis, can you audit these 200 price basket observation rows for data quality issues and filter the item_price field to only include values between 1 and 10000? I want both the audit report and the filtered interval report."}],"resultDescription":"Returns two analytical reports: (1) a record quality audit identifying data issues such as nulls, malformed values, or out-of-range entries across the supplied rows; and (2) a numeric interval filter report showing which rows for the selected field (item_price or quantity_weight) fall within or outside the specified minimum-maximum range. No live data or external lookups are involved — all analysis is local to the submitted data.","failureModes":["Submitting more than 200 rows returns a validation error","Missing required fields (row_id, region, date, item_price, or quantity_weight) causes row-level rejection","Invalid date format (non-YYYY-MM-DD) triggers a pattern validation error","Specifying a minimum greater than maximum may yield an empty interval filter result","Null values in item_price or quantity_weight are flagged in the quality audit but may not cause a call failure","Invalid field enum value (anything other than item_price or quantity_weight) returns a schema error"],"whenToPreferThis":"Choose this endpoint when you need a lightweight, low-cost ($0.01 USDC) dual-report check on price basket observation data — specifically when you want both a data quality audit and a numeric range filter in a single call for up to 200 rows. Prefer this over general-purpose data validation tools when your data specifically contains item_price and quantity_weight fields with region and date context, and you do not need live lookups, predictive analytics, or external data enrichment.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-27T13:06:37.900Z","isFirstParty":false,"canonicalSlug":"price-basket-observations-record-quality-audit-numeric-interval-filter-00b32cca"}