{"uid":"cap_wjOA1piHrAGg0Grvt0eKH","slug":"transaction-fee-observations-string-normalisation-adjacent-row-changes-5d72912c","name":"Transaction Fee Observations — String Normalisation + Adjacent Row Changes","description":"Transaction fee observations — String normalisation + Adjacent row changes: String normalisation + 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-03-029?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_wN-nJu4B5rDPsYC1FLRGI","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":"Applies string normalisation and adjacent row change analysis to up to 200 transaction fee observation records, returning two local analytical reports on fee_units or transaction_count fields.","exampleAgentPrompt":"Can you run string normalisation and adjacent row change analysis on these transaction fee records — I have 4 rows with fee_units and transaction_count for instrument groups group-a and group-b from October 2026, and I want the analysis focused on fee_units?","exampleUseCases":[{"title":"Detect fee drift across trading sessions","prompt":"I have 50 rows of daily transaction fee observations for different instrument groups — can you normalise the fee_units strings and show me the adjacent row changes so I can see how fees shifted from one day to the next?"},{"title":"Audit sequential transaction count changes","prompt":"Run string normalisation and adjacent row difference analysis on my transaction count data — I've got about 120 rows with dates, row IDs, instrument groups, and transaction_count values, and I want the report focused on transaction_count."},{"title":"Compare consecutive fee observations for reconciliation","prompt":"I need to reconcile my fee records — can you take these 30 transaction fee observation rows and give me the string-normalised view plus the adjacent changes in fee_units between each consecutive row?"}],"resultDescription":"Two analytical reports: one covering string normalisation of the instrument_group and related text fields, and one covering adjacent (row-to-row) change values for the selected numeric field (fee_units or transaction_count), applied to up to 200 supplied input rows. No external data or predictions are included.","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, date, instrument_group, fee_units, transaction_count) causes rejection","Invalid date format (non-YYYY-MM-DD) triggers a schema validation error","Numeric values outside ±1,000,000,000,000 are rejected","Empty rows array returns an error","Invalid field enum value (not fee_units or transaction_count) causes failure"],"whenToPreferThis":"Choose this endpoint when you have up to 200 transaction fee observation records and need both string normalisation and adjacent row change analysis in a single low-cost call ($0.01 USDC). It is best suited for offline/batch analytical reporting on supplied data rather than live lookups or predictive analytics. Prefer it when you need two complementary reports (normalisation + delta) on the same dataset without calling separate endpoints.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-26T12:33:19.887Z","isFirstParty":false,"canonicalSlug":"transaction-fee-observations-string-normalisation-adjacent-row-changes-5d72912c"}