{"uid":"cap_BRlLY3pgW3j3o_vZslZW5","slug":"promotion-observations-duplicate-key-report-category-frequencies-e82f01b7","name":"Promotion Observations — Duplicate Key Report + Category Frequencies","description":"Promotion observations — Duplicate key report + Category frequencies: Duplicate key report + Category frequencies for supplied promotion observations records (discount_amount, units_sold). 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-retail-05-057?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","store_group","date","discount_amount","units_sold"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"units_sold":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"store_group":{"type":"string","default":"","maxLength":80},"discount_amount":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","units_sold":1,"store_group":"group-a","discount_amount":10},{"date":"2026-10-02","row_id":"row-2","units_sold":2,"store_group":"group-b","discount_amount":20},{"date":"2026-10-03","row_id":"row-3","units_sold":3,"store_group":"group-a","discount_amount":15},{"date":"2026-10-04","row_id":"row-4","units_sold":4,"store_group":"group-b","discount_amount":30}],"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_X8laf4pXWtyPO0ARgCcnS","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":"Analyzes up to 200 promotion observation records (discount_amount, units_sold) to produce a duplicate row_id report and category frequency counts for store_group and date fields.","exampleAgentPrompt":"Can you check my promotion records for duplicate row IDs and tell me the frequency of each store group and date? Here are up to 200 rows with fields row_id, store_group, date, discount_amount, and units_sold.","exampleUseCases":[{"title":"Retail promotion data quality audit","prompt":"I have 150 promotion observation records from our retail stores — each has a row_id, store_group, date, discount_amount, and units_sold. Can you run a duplicate key check on row_id and also tell me how frequently each store_group and date appears in the dataset?"},{"title":"Pre-analysis deduplication for discount data","prompt":"Before I run any analysis on our promotion dataset, I want to know if there are any duplicate row IDs that could skew results, and I also want a breakdown of how many records fall under each store group. The data has discount_amount and units_sold columns along with dates."},{"title":"Store group distribution check for promotions","prompt":"We ran promotions across several store groups last quarter and I want to see if the data is evenly distributed — can you count how many promotion records we have per store group and date, and flag any duplicate row IDs in our dataset of about 80 rows?"}],"resultDescription":"Returns two analytical reports: (1) a duplicate key report identifying any row_ids that appear more than once in the submitted dataset, and (2) category frequency tables showing how often each distinct value of store_group and date appears across the supplied promotion observation rows. Both reports are computed locally from the submitted data with no external lookups.","failureModes":["Fewer than 1 row submitted — request rejected due to minItems constraint","More than 200 rows submitted — request rejected due to maxItems limit","row_id missing or empty string — validation error","date field does not match YYYY-MM-DD pattern — validation error","discount_amount or units_sold outside allowed numeric range — validation error","Malformed JSON payload — HTTP 400 or similar parse error","Payment of 0.01 USDC not completed — request blocked by x402 payment requirement"],"whenToPreferThis":"Choose this endpoint when you need to simultaneously detect duplicate row IDs and compute category frequency distributions on promotion data (discount_amount, units_sold) in a single low-cost call. It is ideal for lightweight data quality audits on small-to-medium promotion datasets (up to 200 rows) without requiring a full analytics platform. It does not perform predictions, live lookups, or external data enrichment — it works purely on the data you supply.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-23T12:47:04.971Z","isFirstParty":false,"canonicalSlug":"promotion-observations-duplicate-key-report-category-frequencies-e82f01b7"}