{"uid":"cap_42sv75nhpNGkTnww0L31d","slug":"inventory-administration-string-normalisation-exact-row-deduplication-16e7a40e","name":"Inventory Administration — String Normalisation + Exact Row Deduplication","description":"Inventory administration — String normalisation + Exact row deduplication: String normalisation + Exact row deduplication for supplied inventory administration records (count_sessions, discrepancy_count). 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-operations-21-020?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","team_group","date","count_sessions","discrepancy_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"team_group":{"type":"string","default":"","maxLength":80},"count_sessions":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"discrepancy_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","team_group":"group-a","count_sessions":10,"discrepancy_count":1},{"date":"2026-10-02","row_id":"row-2","team_group":"group-b","count_sessions":20,"discrepancy_count":2},{"date":"2026-10-03","row_id":"row-3","team_group":"group-a","count_sessions":15,"discrepancy_count":3},{"date":"2026-10-04","row_id":"row-4","team_group":"group-b","count_sessions":30,"discrepancy_count":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_drxjWfLfw3N6O8SVb12PN","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 inventory administration records containing count sessions and discrepancy counts, producing 2 analytical reports for up to 200 rows.","exampleAgentPrompt":"Can you clean up my inventory administration data — I have up to 50 rows with team groups, dates, count_sessions and discrepancy_count values — by normalising the string fields and removing any exact duplicate rows, then give me the 2 reports?","exampleUseCases":[{"title":"Warehouse count session deduplication","prompt":"I've got about 80 rows of warehouse inventory count session data with team_group names, dates, count_sessions and discrepancy_count numbers — some rows are exact duplicates and the team group strings are inconsistent. Can you normalise the strings and deduplicate them, and give me both reports?"},{"title":"Monthly discrepancy data cleanup","prompt":"My inventory discrepancy records for October have messy string fields in the team_group column and I suspect there are duplicate rows. Here are 120 rows with row_id, date, count_sessions and discrepancy_count — please normalise the strings and strip out exact duplicates, and return the 2 analysis reports."},{"title":"Multi-team inventory audit prep","prompt":"Before I present our quarterly inventory audit, I need to clean up this dataset — about 60 rows across group-a and group-b teams with count_sessions and discrepancy_count fields. Can you normalise any inconsistent team group strings and remove exact duplicate rows, giving me the two standard reports?"}],"resultDescription":"Two local analytical reports: one covering string normalisation results (standardised team_group and other string fields) and one covering exact row deduplication results (identifying and removing identical rows), applied to the submitted inventory administration dataset of up to 200 rows.","failureModes":["Exceeding 200 rows returns a validation error","Rows missing required fields (row_id, team_group, date, count_sessions, discrepancy_count) are rejected","Date values not matching YYYY-MM-DD pattern cause schema validation failure","Numeric values outside ±1,000,000,000,000 are rejected","Empty input array returns an error","Payment failure prevents processing"],"whenToPreferThis":"Choose this endpoint when you need lightweight, offline data-cleaning operations — specifically string normalisation and exact row deduplication — on inventory administration data (count_sessions, discrepancy_count) without requiring live database access, external lookups, or predictions. Ideal for pre-processing small-to-medium inventory datasets (up to 200 rows) at very low cost ($0.01 for 2 reports). Not suitable if you need fuzzy deduplication, statistical outlier detection, or real-time inventory system integration.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T18:35:56.171Z","isFirstParty":false,"canonicalSlug":"inventory-administration-string-normalisation-exact-row-deduplication-16e7a40e"}