{"uid":"cap_1al6d863tpGXFJML8ZxI6","slug":"competitor-supplied-prices-record-quality-audit-string-normalisation-20373f4c","name":"Competitor Supplied Prices — Record Quality Audit + String Normalisation + Numeric Distribution","description":"Competitor supplied prices — Record quality audit + String normalisation + Numeric distribution: Record quality audit + String normalisation + Numeric distribution for supplied competitor supplied prices records (list_price, package_quantity). 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-company-07-193?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","company_group","date","list_price","package_quantity"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"list_price":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"company_group":{"type":"string","default":"","maxLength":80},"package_quantity":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","list_price":10,"company_group":"group-a","package_quantity":1},{"date":"2026-10-02","row_id":"row-2","list_price":20,"company_group":"group-b","package_quantity":2},{"date":"2026-10-03","row_id":"row-3","list_price":15,"company_group":"group-a","package_quantity":3},{"date":"2026-10-04","row_id":"row-4","list_price":30,"company_group":"group-b","package_quantity":4}],"maxItems":200,"minItems":1},"field":{"enum":["list_price","package_quantity"],"type":"string","default":"list_price"}}},"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_mQuT1UXoke0P00UEaYdbI","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, numeric distribution) on up to 200 rows of competitor price data containing list_price and package_quantity fields.","exampleAgentPrompt":"Can you audit the quality of these competitor pricing records, normalise the string fields, and give me a numeric distribution report on list_price? I have up to 50 rows with row_id, company_group, date, list_price, and package_quantity.","exampleUseCases":[{"title":"Pricing data quality check before analysis","prompt":"I've collected competitor prices from several suppliers and want to make sure the data is clean before I use it — can you run a record quality audit, string normalisation, and numeric distribution report on these 80 rows of list_price and package_quantity data?"},{"title":"Detecting outliers in competitor package quantities","prompt":"Can you run a numeric distribution analysis on the package_quantity field across these 120 competitor pricing rows grouped by company_group so I can spot outliers or skewed distributions before benchmarking?"},{"title":"Pre-processing competitor data for reporting","prompt":"Before I build my pricing comparison report, can you audit these 150 competitor price records for quality issues, normalise any inconsistent string values, and summarise the numeric distribution of list_price by date?"}],"resultDescription":"Returns three independent analytical reports: (1) a record quality audit flagging completeness, consistency, and validity issues per row; (2) a string normalisation report standardising text fields like company_group; and (3) a numeric distribution summary (e.g. min, max, mean, percentiles) for the selected numeric field (list_price or package_quantity). All analysis is performed locally with no external lookups.","failureModes":["Payload exceeds 200 rows — request rejected","Missing required fields (row_id, company_group, date, list_price, or package_quantity) — validation error","Invalid date format (must be YYYY-MM-DD) — schema validation failure","Numeric values outside allowed range (±1,000,000,000,000) — rejected","Empty rows array — minimum 1 item required","Invalid field selector value (must be list_price or package_quantity)"],"whenToPreferThis":"Choose this endpoint when you have raw competitor pricing data (up to 200 rows) that needs simultaneous quality auditing, string standardisation, and numeric distribution profiling in a single low-cost call. It is ideal as a pre-processing step before deeper competitive analysis, when you want three bundled analytical views without building separate pipelines. Prefer it over general-purpose data tools when your data specifically includes list_price and package_quantity fields from competitor or supplier sources.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:14.202Z","isFirstParty":false,"canonicalSlug":"competitor-supplied-prices-record-quality-audit-string-normalisation-20373f4c"}