{"uid":"cap_o0sHdo7p0d-yZrnjMbmPc","slug":"inventory-administration-numeric-interval-filter-date-by-category-pivot-5f9116ac","name":"Inventory Administration — Numeric Interval Filter + Date by Category Pivot","description":"Inventory administration — Numeric interval filter + Date by category pivot: Numeric interval filter + Date by category pivot 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-21-133?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},"field":{"enum":["count_sessions","discrepancy_count"],"type":"string","default":"count_sessions"},"maximum":{"type":"number","default":100,"maximum":1000000000000,"minimum":-1000000000000},"minimum":{"type":"number","default":0,"maximum":1000000000000,"minimum":-1000000000000}}},"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_EU3DlM5SK6YvKEudBvMxu","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":"Filters inventory administration rows by a numeric interval on a chosen field and produces a date-by-category pivot table, returning two analytical reports for up to 200 supplied rows.","exampleAgentPrompt":"Take my inventory records for team groups alpha and beta from October 2026 — with fields row_id, team_group, date, count_sessions, and discrepancy_count — and give me two reports: first, filter rows where count_sessions is between 10 and 25, and second, pivot the discrepancy_count by date and team group.","exampleUseCases":[{"title":"Flag sessions outside expected range","prompt":"Here are 150 rows of daily inventory data with team_group, date, count_sessions, and discrepancy_count. Give me a report of only the rows where count_sessions falls between 5 and 50, filtering on count_sessions, plus a pivot of those sessions broken down by date and team group."},{"title":"Audit discrepancy spikes by category","prompt":"I have inventory administration records for four team groups across Q4 2026. Run a numeric interval filter on discrepancy_count between 0 and 3, and also pivot discrepancy_count by date and team group so I can see where spikes are occurring."},{"title":"Validate session volume for ops review","prompt":"Here's my ops data — about 80 rows, each with a row_id, team_group, date, count_sessions, and discrepancy_count. Filter to rows where count_sessions is between 12 and 30, and also generate a date-by-category pivot on count_sessions so I can present both views to the operations team."}],"resultDescription":"Returns two independent analytical reports: (1) rows from the supplied dataset whose chosen numeric field (count_sessions or discrepancy_count) falls within the specified minimum–maximum interval, and (2) a pivot table cross-tabulating the chosen numeric field by date and team_group category. Both reports are computed locally from the caller-supplied data with no external lookups.","failureModes":["Rows array is empty or missing — returns validation error","More than 200 rows supplied — request rejected at max limit","minimum value exceeds maximum value — may return empty filter result or error","Invalid date format (not YYYY-MM-DD) in any row — schema validation failure","Unknown field enum value provided — rejected by schema","Null numeric values may be excluded from interval filtering","Payment of 0.01 USDC not confirmed — request not processed"],"whenToPreferThis":"Choose this endpoint when you have up to 200 inventory administration records in hand and need both a numeric range filter (to isolate rows within a specific count window) and a date-by-category pivot table in a single paid call. It is ideal for operations or inventory analysts who want two complementary views — filtered detail rows plus a cross-tabulated summary — without writing custom code or standing up a database. Prefer it over general-purpose analytics APIs when your data is already structured with row_id, team_group, date, count_sessions, and discrepancy_count fields and you want reproducible, local computation at low cost.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-30T19:11:11.737Z","isFirstParty":false,"canonicalSlug":"inventory-administration-numeric-interval-filter-date-by-category-pivot-5f9116ac"}