{"uid":"cap_WGVhE9hgVVV2G-LwGhggU","slug":"trade-observations-record-quality-audit-string-normalisation-numeric-766f15be","name":"Trade Observations — Record Quality Audit + String Normalisation + Numeric Interval Filter","description":"Trade observations — Record quality audit + String normalisation + Numeric interval filter: Record quality audit + String normalisation + Numeric interval filter for supplied trade observations records (export_amount, import_amount). 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-economics-06-197?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","region","date","export_amount","import_amount"],"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},"export_amount":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"import_amount":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","region":"group-a","row_id":"row-1","export_amount":10,"import_amount":1},{"date":"2026-10-02","region":"group-b","row_id":"row-2","export_amount":20,"import_amount":2},{"date":"2026-10-03","region":"group-a","row_id":"row-3","export_amount":15,"import_amount":3},{"date":"2026-10-04","region":"group-b","row_id":"row-4","export_amount":30,"import_amount":4}],"maxItems":200,"minItems":1},"field":{"enum":["export_amount","import_amount"],"type":"string","default":"export_amount"},"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_sxnsepHWVQndYO2ftla0c","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, normalises strings, and filters by numeric interval across up to 200 trade observation rows (export_amount, import_amount), returning 3 analytical reports.","exampleAgentPrompt":"Can you audit these 50 trade observation rows for record quality issues, normalise the region strings, and filter the export_amount field to only keep rows between 500 and 50000? Here's the data: [row_id, region, date, export_amount, import_amount].","exampleUseCases":[{"title":"Export data range validation","prompt":"I have 120 trade records with export_amount and import_amount values. Can you run a quality audit, normalise the region names, and filter export_amount to only keep rows between 1000 and 500000?"},{"title":"Import anomaly detection for economics team","prompt":"We have a batch of 80 trade observations from various regions. Please audit record quality, clean up the region strings, and filter import_amount to show only rows within the range 0 to 250000."},{"title":"Data cleaning before trade report","prompt":"Before I generate our quarterly trade report, can you audit these 200 trade rows for data quality problems, normalise any messy region labels, and filter out any export_amount values outside the range 100 to 999999?"}],"resultDescription":"Returns 3 independent analytical reports per call: (1) a record quality audit highlighting missing, malformed, or out-of-range values; (2) a string normalisation report for region and other string fields; and (3) a numeric interval filter report showing which rows fall within the specified minimum–maximum range for the chosen field (export_amount or import_amount). Covers up to 200 input rows with no external lookups or live data.","failureModes":["More than 200 rows submitted — request rejected with maxItems validation error","Missing required fields (row_id, region, date, export_amount, import_amount) in any row — validation error","minimum greater than maximum — may produce empty filter results or error","Date strings not matching YYYY-MM-DD pattern — schema validation failure","Numeric values outside ±1,000,000,000,000 bounds — validation error"],"whenToPreferThis":"Choose this endpoint when you need a combined offline quality audit, string normalisation, and numeric interval filter on trade observation data (export_amount, import_amount) in a single cost-effective call. It is ideal for pre-processing economics datasets up to 200 rows before reporting or analysis, with no need for external lookups or predictions. Prefer alternatives if you need live market data, forecasting, or datasets exceeding 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-26T12:32:11.317Z","isFirstParty":false,"canonicalSlug":"trade-observations-record-quality-audit-string-normalisation-numeric-766f15be"}