{"uid":"cap_Kl5JYOxpOanOqhhZVbhvA","slug":"transaction-fee-observations-adjacent-row-changes-date-by-category-08439f3b","name":"Transaction Fee Observations — Adjacent Row Changes + Date by Category Pivot","description":"Transaction fee observations — Adjacent row changes + Date by category pivot: Adjacent row changes + Date by category pivot for supplied transaction fee observations records (fee_units, transaction_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-finance-03-160?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","instrument_group","date","fee_units","transaction_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"fee_units":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"instrument_group":{"type":"string","default":"","maxLength":80},"transaction_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","fee_units":10,"instrument_group":"group-a","transaction_count":1},{"date":"2026-10-02","row_id":"row-2","fee_units":20,"instrument_group":"group-b","transaction_count":2},{"date":"2026-10-03","row_id":"row-3","fee_units":15,"instrument_group":"group-a","transaction_count":3},{"date":"2026-10-04","row_id":"row-4","fee_units":30,"instrument_group":"group-b","transaction_count":4}],"maxItems":200,"minItems":1},"field":{"enum":["fee_units","transaction_count"],"type":"string","default":"fee_units"}}},"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_QV0anUBs903zA_-G-nalx","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 supplied transaction fee data: adjacent row change analysis and a date-by-category pivot table, for up to 200 rows.","exampleAgentPrompt":"Run adjacent row change analysis and a date-by-category pivot on my transaction fee data — I have rows with instrument_group, date, fee_units, and transaction_count fields — and use fee_units as the measure.","exampleUseCases":[{"title":"Fee trend analysis by instrument group","prompt":"I have daily transaction fee records across two instrument groups for October 2026. Can you calculate the row-over-row changes in fee_units and also pivot the data by date and category so I can see how fees shifted across groups over time?"},{"title":"Detecting fee spikes between sequential rows","prompt":"Take my list of transaction fee observations — each row has a date, instrument group, fee_units, and transaction_count — and show me the adjacent row changes in transaction_count so I can spot any sudden spikes or drops."},{"title":"Category-date pivot for finance reporting","prompt":"I need a pivot table of my transaction fee observations grouped by instrument_group and date, plus a row-by-row diff on fee_units. I have about 150 rows to analyze."}],"resultDescription":"Two analytical reports: (1) adjacent row change values showing the sequential delta in the selected field (fee_units or transaction_count) between consecutive rows, and (2) a date-by-category pivot table cross-tabulating the selected measure across instrument_group and date dimensions, computed locally without external lookups.","failureModes":["Missing required fields (row_id, instrument_group, date, fee_units, transaction_count) cause validation errors","Exceeding 200 rows returns an error or truncation","Invalid date format (not YYYY-MM-DD) causes schema rejection","Null values in fee_units or transaction_count may produce incomplete pivot cells","Empty rows array causes a minItems validation failure"],"whenToPreferThis":"Choose this endpoint when you have a dataset of transaction fee observations (up to 200 rows) and need both a sequential row-change diff and a date-by-category pivot in a single low-cost call. It is ideal for lightweight, self-contained fee analytics where no live data, external enrichment, or forecasting is needed — just local computation on supplied data for $0.01 USDC.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-26T12:32:38.873Z","isFirstParty":false,"canonicalSlug":"transaction-fee-observations-adjacent-row-changes-date-by-category-08439f3b"}