{"uid":"cap_bOiArbBj7CEMW2jPCfSvZ","slug":"inventory-administration-string-normalisation-category-frequencies-65b2a714","name":"Inventory Administration — String Normalisation + Category Frequencies","description":"Inventory administration — String normalisation + Category frequencies: String normalisation + Category frequencies 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-21-024?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_-pn9sg6z8Aaa4ITY8k1eJ","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 inventory administration data: string normalisation of text fields and category frequency counts across team_group, for up to 200 rows.","exampleAgentPrompt":"I have up to 200 inventory administration records with fields like row_id, team_group, date, count_sessions, and discrepancy_count — can you run string normalisation on the text fields and give me a category frequency breakdown by team_group?","exampleUseCases":[{"title":"Team group distribution audit","prompt":"I've got 150 rows of inventory admin data with team groups like 'group-a' and 'group-b', dates, session counts, and discrepancy counts — can you normalise the string fields and tell me how many records fall into each team group category?"},{"title":"Session discrepancy frequency analysis","prompt":"Here are our weekly inventory administration records for October — can you clean up any inconsistent text values and give me a frequency count of how many entries each team group has, so I can spot which groups are most active?"},{"title":"Operations data quality clean-up","prompt":"We have a batch of ~80 inventory operation rows with mixed casing and inconsistent team_group labels — please run string normalisation across them and produce a category frequency report showing counts per group."}],"resultDescription":"Returns two reports: (1) a string normalisation report showing cleaned/standardised versions of text fields (e.g. team_group) across the submitted rows, and (2) a category frequency report showing how many records belong to each distinct category value, all computed locally without any external lookups.","failureModes":["Submitting more than 200 rows returns an error — batch must be split","Missing required fields (row_id, team_group, date, count_sessions, discrepancy_count) causes validation failure","Invalid date format (not YYYY-MM-DD) will be rejected by schema validation","Numeric values outside the allowed range (±1,000,000,000,000) will fail validation","Empty rows array (minItems:1 not met) returns an error"],"whenToPreferThis":"Choose this endpoint when you need both string normalisation and category frequency counts on inventory administration records in a single low-cost call. It is best suited for batch offline analysis of up to 200 rows where no live data lookup, prediction, or external action is required. It is not suitable for real-time inventory tracking, predictive analytics, or datasets exceeding 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-31T00:42:37.614Z","isFirstParty":false,"canonicalSlug":"inventory-administration-string-normalisation-category-frequencies-65b2a714"}