{"uid":"cap_0iNaUjFO7LluAhWDVMIA9","slug":"competitor-supplied-prices-record-quality-audit-string-normalisation-08da67bd","name":"Competitor Supplied Prices — Record Quality Audit + String Normalisation + Exact Row Deduplication","description":"Competitor supplied prices — Record quality audit + String normalisation + Exact row deduplication: Record quality audit + String normalisation + Exact row deduplication 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-07-191?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}}},"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_Sp2afjwCL0Ul3zN0RaXr7","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 deduplicates exact rows for competitor supplied price data (list_price, package_quantity) across up to 200 rows, producing 3 independent analytical reports.","exampleAgentPrompt":"Can you run a record quality audit, string normalisation, and exact row deduplication on this competitor pricing dataset — it has columns for row_id, company_group, date, list_price, and package_quantity, about 50 rows total, and I need all three reports back?","exampleUseCases":[{"title":"Pre-analysis competitor price data cleaning","prompt":"I've got a batch of competitor pricing records with list_price and package_quantity fields — about 120 rows — and before I do any analysis I want to audit them for quality issues, normalise the string fields, and remove any exact duplicate rows. Can you run those three checks for me?"},{"title":"Validating scraped pricing before import","prompt":"We scraped competitor prices from three suppliers and have around 80 rows with company_group, date, list_price, and package_quantity. Please run a full record quality audit, string normalisation, and exact deduplication check on this data so we know what's clean enough to import."},{"title":"Routine data hygiene on monthly pricing feed","prompt":"Every month we get a competitor price feed with up to 150 rows covering list_price and package_quantity by company group. Run the record quality audit, string normalisation, and exact row deduplication on this month's batch and give me all three reports."}],"resultDescription":"Three independent analytical reports covering: (1) a record quality audit flagging missing, malformed, or out-of-range values in list_price and package_quantity fields; (2) a string normalisation report detailing transformations applied to text fields such as company_group; and (3) an exact row deduplication report identifying and removing fully duplicate rows across the submitted dataset of up to 200 rows.","failureModes":["Submitting more than 200 rows returns a validation error","Missing required fields (row_id, company_group, date, list_price, package_quantity) causes row-level rejection","Invalid date format (not YYYY-MM-DD) triggers schema validation failure","Empty array input (minItems:1 not met) returns an input validation error","Numeric values outside allowed range cause field-level errors"],"whenToPreferThis":"Choose this endpoint when you have up to 200 rows of competitor supplied pricing data (with list_price and package_quantity) and need all three of record quality auditing, string normalisation, and exact row deduplication in a single low-cost call. It is ideal for pre-processing competitor price feeds before downstream analysis, and when no live external lookup, prediction, or human assessment is needed — purely local analytical processing on supplied data.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:45:28.534Z","isFirstParty":false,"canonicalSlug":"competitor-supplied-prices-record-quality-audit-string-normalisation-08da67bd"}