{"uid":"cap_LJOWzl_a9wxCtWK7I1eGq","slug":"competitor-supplied-prices-string-normalisation-date-by-category-pivot-a8e7a3a5","name":"Competitor Supplied Prices — String Normalisation + Date by Category Pivot","description":"Competitor supplied prices — String normalisation + Date by category pivot: String normalisation + Date by category pivot 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-07-035?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_5OdMT3OcG0sKv_jpQamyC","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 string fields and produces a date-by-category pivot for up to 200 rows of competitor supplied pricing data (list_price, package_quantity), returning two analytical reports per call.","exampleAgentPrompt":"I have 150 rows of competitor pricing data with company groups, dates, list prices, and package quantities — can you normalise the strings and give me a date-by-category pivot on list_price so I can see how each competitor group's prices change over time?","exampleUseCases":[{"title":"Competitor pricing landscape report","prompt":"I've got 80 rows of competitor price records with company groups like 'group-a' and 'group-b', dates in YYYY-MM-DD format, and list prices — can you normalise the strings and pivot the list_price by date and category so I can compare them?"},{"title":"Package quantity trend pivot","prompt":"I have supplier data with 120 rows including company_group, date, and package_quantity fields — please run string normalisation and generate a date-by-category pivot on package_quantity so I can spot volume trends across competitors."},{"title":"Multi-group price data cleanup","prompt":"Can you take these 200 rows of messy competitor pricing records with company groups and dates and give me two analytical reports — one that normalises the string fields and one that pivots list_price by date and category group?"}],"resultDescription":"Two analytical reports per call: (1) string-normalised version of the supplied competitor pricing rows, and (2) a date-by-category pivot table for the selected numeric field (list_price or package_quantity), computed locally with no external lookups or predictions. Results are limited to up to 200 input rows.","failureModes":["More than 200 rows submitted — request will be rejected or truncated","Invalid date format (not YYYY-MM-DD) causes parsing failure","Missing required fields (row_id, company_group, date) causes validation error","Invalid field selector (not 'list_price' or 'package_quantity') returns error","Numeric values outside allowed range (-1T to +1T) may be rejected","Empty rows array returns validation error"],"whenToPreferThis":"Choose this endpoint when you have up to 200 rows of pre-collected competitor pricing data (with company group, date, list_price, and/or package_quantity fields) and need both string normalisation and a date-by-category pivot in a single low-cost call. It is ideal for offline/batch analytical enrichment of supplied datasets rather than live price lookups or predictive modelling. At $0.01 USDC for two reports, it is cost-effective for small-to-medium competitor price datasets that need light transformation before downstream analysis.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:45:38.757Z","isFirstParty":false,"canonicalSlug":"competitor-supplied-prices-string-normalisation-date-by-category-pivot-a8e7a3a5"}