{"uid":"cap_lYUSEr2BB3W7c_spqFBV5","slug":"promotion-observations-string-normalisation-duplicate-key-report-77488285","name":"Promotion Observations — String Normalisation + Duplicate Key Report","description":"Promotion observations — String normalisation + Duplicate key report: String normalisation + Duplicate key report 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-05-021?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_W118iTrlGgNtXswX9tw8y","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 two local analytical reports on promotion observation records: string normalisation of text fields and a duplicate key detection report, covering up to 200 rows of discount_amount and units_sold data.","exampleAgentPrompt":"Can you run a string normalisation and duplicate key check on my promotion records? I have about 50 rows with fields like row_id, store_group, date, discount_amount, and units_sold — I want to catch any duplicate row IDs and get the store group strings cleaned up.","exampleUseCases":[{"title":"Pre-analysis promotion data cleanup","prompt":"Before I analyze this month's promotion results, can you normalise the store_group strings and flag any duplicate row IDs in my dataset? I have 120 rows covering October 2026 with discount_amount and units_sold columns."},{"title":"Retail discount data audit","prompt":"I need to audit my promotion observations for data quality issues — specifically duplicate row keys and messy string values in store_group. Can you run both reports on my 80 rows of discount and units-sold records?"},{"title":"Promotion dataset deduplication check","prompt":"We're merging two promotion datasets and I'm worried there are duplicate row IDs. Can you run a duplicate key report and string normalisation on the combined 150-row file that has store_group, date, discount_amount, and units_sold?"}],"resultDescription":"Returns two independent analytical reports: (1) a string normalisation report showing standardised versions of text fields such as store_group, and (2) a duplicate key report identifying any rows sharing the same row_id, covering up to 200 supplied promotion observation rows with no external lookups or predictions.","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, store_group, date, discount_amount, units_sold) causes rejection","Invalid date format (not YYYY-MM-DD) triggers schema validation failure","Numeric values outside ±1,000,000,000,000 are rejected","Empty rows array returns an error","Payment of 0.01 USDC must be included or request is rejected"],"whenToPreferThis":"Choose this endpoint when you need lightweight, local data-quality checks on promotion observation records — specifically string normalisation of categorical fields and duplicate key detection — without requiring external lookups, predictions, or professional assessments. Best suited for datasets up to 200 rows where both reports are needed together at low cost.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-23T12:46:23.151Z","isFirstParty":false,"canonicalSlug":"promotion-observations-string-normalisation-duplicate-key-report-77488285"}