{"uid":"cap_OXM_3KeU1th4rQNjnYO5G","slug":"packaging-usage-string-normalisation-and-exact-row-deduplication-c0ef0db7","name":"Packaging Usage String Normalisation and Exact Row Deduplication","description":"Packaging usage — String normalisation + Exact row deduplication: String normalisation + Exact row deduplication for supplied packaging usage records (packages_sent, material_grams). 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-17-020?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","store_group","date","packages_sent","material_grams"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"store_group":{"type":"string","default":"","maxLength":80},"packages_sent":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"material_grams":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","store_group":"group-a","packages_sent":10,"material_grams":1},{"date":"2026-10-02","row_id":"row-2","store_group":"group-b","packages_sent":20,"material_grams":2},{"date":"2026-10-03","row_id":"row-3","store_group":"group-a","packages_sent":15,"material_grams":3},{"date":"2026-10-04","row_id":"row-4","store_group":"group-b","packages_sent":30,"material_grams":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_krqtUdt-zTSrrXRcdiHGQ","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 removes exact duplicate rows from packaging usage records (packages_sent, material_grams) for up to 200 rows, producing 2 analytical reports.","exampleAgentPrompt":"Can you clean up my packaging usage data — normalise the store group strings and remove any exact duplicate rows? I have records for store groups like 'group-a' and 'group-b' with packages sent and material grams from October 2026, about 50 rows total.","exampleUseCases":[{"title":"Retail packaging sustainability audit prep","prompt":"I need to clean my monthly packaging dispatch data before submitting our sustainability report — can you normalise the store group names and strip out any exact duplicate rows? I have about 120 records with packages sent and material grams across our store groups for Q3 2026."},{"title":"Multi-store packaging data deduplication","prompt":"Our warehouse system exported packaging usage records with inconsistent capitalisation in store group names and some duplicate entries — can you normalise those strings and remove exact duplicate rows? There are around 80 rows covering October and November 2026."},{"title":"Pre-analysis packaging data cleaning","prompt":"Before I run my packaging efficiency analysis I want to make sure the raw data is clean — please normalise string fields and deduplicate exact matching rows in my packages sent and material grams dataset, which has about 150 rows from various store groups in 2026."}],"resultDescription":"Returns 2 reports: (1) a string-normalised version of the submitted packaging usage rows with standardised store_group and date strings, and (2) an exact row deduplication report identifying and removing fully duplicate records, covering up to 200 input rows.","failureModes":["Exceeds 200-row limit — request rejected, must split into smaller batches","Missing required fields (row_id, date, packages_sent, material_grams) — validation error","Invalid date format (not YYYY-MM-DD) — schema validation failure","row_id exceeds 80 characters — rejected","Numeric values outside allowed range (±1,000,000,000,000) — schema error","Empty rows array — minimum 1 item required"],"whenToPreferThis":"Choose this endpoint when you need lightweight, local analytical cleaning of packaging usage data — specifically string normalisation and exact duplicate removal — without any external lookups, predictions, or live data enrichment. It is well-suited for retail or logistics teams preparing packaging dispatch records for reporting or downstream analysis and who want a low-cost ($0.01 USDC for 2 reports) batch clean of up to 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-04T18:49:05.444Z","isFirstParty":false,"canonicalSlug":"packaging-usage-string-normalisation-and-exact-row-deduplication-c0ef0db7"}