{"uid":"cap_Xrn9c1VXKzmtGAaTulzRE","slug":"competitor-supplied-prices-record-quality-audit-string-normalisation-f53c2685","name":"Competitor Supplied Prices — Record Quality Audit + String Normalisation + Category Frequencies","description":"Competitor supplied prices — Record quality audit + String normalisation + Category frequencies: Record quality audit + String normalisation + Category frequencies 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-07-195?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_SihTh_5UcbikskGjU9olG","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 on up to 200 competitor price records: a record quality audit, string normalisation, and category frequency analysis on list_price and package_quantity fields.","exampleAgentPrompt":"Can you run a quality audit, string normalisation, and category frequency report on these competitor price records? I have up to 200 rows with fields like row_id, company_group, date, list_price, and package_quantity — for example: row-1, group-a, 2026-10-01, list_price 10, package_quantity 1.","exampleUseCases":[{"title":"Auditing competitor price data quality","prompt":"I've scraped competitor prices from a few suppliers and I want to check the data quality before I use it — can you audit these records for missing values, format issues, and bad entries? I have about 150 rows with row IDs, company groups, dates, list prices, and package quantities."},{"title":"Normalising company group strings","prompt":"My competitor pricing dataset has inconsistent company group labels — things like 'Group A', 'group-a', and 'GROUP A' mixed together. Can you normalise those strings across my 80 records so they're consistent?"},{"title":"Category frequency breakdown by supplier","prompt":"I want to know how often each company group appears in my competitor pricing dataset. I have 200 rows of competitor prices — can you give me a frequency count broken down by category?"}],"resultDescription":"Three independent reports returned together: (1) a record quality audit flagging missing, out-of-range, or malformed values in each row; (2) normalised string representations of text fields like company_group; (3) category frequency counts showing how often each distinct category value appears across the submitted rows.","failureModes":["Empty or missing rows array returns a validation error","More than 200 rows submitted exceeds the maximum and will be rejected","Rows missing required fields (row_id, company_group, date, list_price, package_quantity) fail schema validation","Dates not matching YYYY-MM-DD pattern fail pattern validation","list_price or package_quantity values outside ±1,000,000,000,000 are rejected","Payment of 0.01 USDC not included causes 402 Payment Required response"],"whenToPreferThis":"Choose this endpoint when you have a batch of up to 200 competitor price records (with list_price and package_quantity) and need simultaneous data quality auditing, string field normalisation, and category frequency analysis in a single call without any external lookups or predictions. It is ideal for preprocessing competitor pricing data before downstream analysis or modelling.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:44:26.771Z","isFirstParty":false,"canonicalSlug":"competitor-supplied-prices-record-quality-audit-string-normalisation-f53c2685"}