{"uid":"cap_Xy6tOWjdH-jHL5rpleK2N","slug":"transaction-fee-observations-daily-sum-series-adjacent-row-changes-02a80f35","name":"Transaction Fee Observations — Daily Sum Series + Adjacent Row Changes","description":"Transaction fee observations — Daily sum series + Adjacent row changes: Daily sum series + Adjacent row changes 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-03-137?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_2FeBy3cU6mLU2nlZJ5kl2","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":"Computes a daily sum time series and adjacent row-to-row change report for supplied transaction fee observation records (fee_units or transaction_count).","exampleAgentPrompt":"Can you run a daily sum series and adjacent row change report on my transaction fee data? I have 4 rows with fee_units values of 10, 20, 15, 30 for dates 2026-10-01 through 2026-10-04, and I want to analyze the fee_units field.","exampleUseCases":[{"title":"Daily fee revenue trend analysis","prompt":"I have a week of transaction fee records with date, fee_units, and transaction_count — can you compute the daily total fee_units and show me how fees changed between consecutive days?"},{"title":"Instrument group fee aggregation","prompt":"I need a daily sum series for fee_units across my instrument groups (group-a and group-b) plus the day-over-day differences. Here are my 10 rows of transaction data with dates from 2026-10-01 to 2026-10-10."},{"title":"Transaction count daily rollup","prompt":"Can you aggregate my transaction_count field into a daily sum series and flag the changes between each adjacent row? I have about 50 records across different instrument groups that I want summarized."}],"resultDescription":"Returns two analytical reports: (1) a daily sum series aggregating the chosen field (fee_units or transaction_count) by date, and (2) an adjacent row change report showing the difference between consecutive observations. Up to 200 input rows supported per call.","failureModes":["Input array exceeds 200 rows — request rejected","Missing required fields (row_id, date, instrument_group, fee_units, transaction_count) — validation error","Invalid date format (must match YYYY-MM-DD pattern) — schema validation failure","Numeric values outside ±1,000,000,000,000 range — schema validation failure","Empty rows array — minimum 1 item required"],"whenToPreferThis":"Use this endpoint when you have raw transaction fee observation records and need both a daily aggregated sum time series and a consecutive-row delta report in a single call. It is ideal for offline/batch analytical workflows where you supply your own data (no live data fetched) and need two complementary reports cheaply. Prefer this over general-purpose analytics tools when working with the specific fee_units/transaction_count schema and needing deterministic local computation.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-25T12:33:59.189Z","isFirstParty":false,"canonicalSlug":"transaction-fee-observations-daily-sum-series-adjacent-row-changes-02a80f35"}