{"uid":"cap_3Yk-O5YZP9YrpjMjdzAOW","slug":"competitor-supplied-prices-string-normalisation-exact-row-deduplication-a95f5d68","name":"Competitor Supplied Prices — String Normalisation + Exact Row Deduplication","description":"Competitor supplied prices — String normalisation + Exact row deduplication: String normalisation + Exact row deduplication for supplied competitor supplied prices records (list_price, package_quantity). 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-company-07-020?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_0BC9fnc15ONShXvixeaza","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":"Normalises strings and deduplicates exact rows in competitor-supplied price records (list_price, package_quantity), producing 2 analytical reports for up to 200 rows.","exampleAgentPrompt":"I have a batch of up to 200 competitor price records with list prices and package quantities — can you normalise the strings and remove any exact duplicate rows, then give me 2 analytical reports? Here's the data: [{\"row_id\":\"row-1\",\"company_group\":\"group-a\",\"date\":\"2026-10-01\",\"list_price\":10,\"package_quantity\":1},{\"row_id\":\"row-2\",\"company_group\":\"group-b\",\"date\":\"2026-10-02\",\"list_price\":20,\"package_quantity\":2}].","exampleUseCases":[{"title":"Weekly competitor price feed cleanup","prompt":"I've pulled this week's competitor pricing feed — 150 rows with list prices and package quantities — can you normalise all the string fields and remove exact duplicate rows, and send back 2 summary reports?"},{"title":"Multi-supplier price list deduplication","prompt":"We have competitor price records from three suppliers all merged into one file, about 180 rows total, and there are likely duplicates. Can you clean up the strings and deduplicate exact rows across company groups and dates, and give me 2 reports on what was found?"},{"title":"Retail pricing audit before import","prompt":"Before I import these 90 competitor price rows into our system, can you normalise any inconsistent strings in the company_group field and strip out exact duplicate list_price and package_quantity entries, with 2 analytical reports on the cleaned data?"}],"resultDescription":"Two independent analytical reports covering the submitted competitor price records, reflecting string normalisation applied to text fields and exact row deduplication of list_price and package_quantity entries, processed locally without external lookups or predictions.","failureModes":["Submitting more than 200 rows causes rejection (maxItems exceeded)","Missing required fields (row_id, company_group, date, list_price, package_quantity) causes validation error","Date values not matching YYYY-MM-DD pattern are rejected","row_id values exceeding 80 characters are rejected","Numeric fields outside ±1,000,000,000,000 range are rejected"],"whenToPreferThis":"Choose this endpoint when you have competitor-supplied pricing records (list_price, package_quantity) that need string normalisation and exact duplicate removal before analysis or import, and you want two structured reports from a single low-cost call. It is ideal for small-to-medium batches (up to 200 rows) where no live lookup, prediction, or external data enrichment is needed — purely local analytical processing of your own supplied data.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:45:43.390Z","isFirstParty":false,"canonicalSlug":"competitor-supplied-prices-string-normalisation-exact-row-deduplication-a95f5d68"}