{"uid":"cap_0XZgQOuZ-BkYD-Rs0BxmX","slug":"transaction-fee-observations-record-quality-audit-string-5cb3637d","name":"Transaction Fee Observations — Record Quality Audit + String Normalisation + Keyed Dataset Comparison","description":"Transaction fee observations — Record quality audit + String normalisation + Keyed dataset comparison: Record quality audit + String normalisation + Keyed dataset comparison for supplied transaction fee observations records (fee_units, transaction_count). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-finance-03-207?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}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"fee_units":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"instrument_group":{"type":"string","default":"","maxLength":80},"transaction_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","fee_units":10,"instrument_group":"group-a","transaction_count":1},{"date":"2026-10-02","row_id":"row-2","fee_units":20,"instrument_group":"group-b","transaction_count":2},{"date":"2026-10-03","row_id":"row-3","fee_units":15,"instrument_group":"group-a","transaction_count":3},{"date":"2026-10-04","row_id":"row-4","fee_units":30,"instrument_group":"group-b","transaction_count":4}],"maxItems":200,"minItems":1},"other":{"type":"array","items":{"type":"object","required":["row_id","instrument_group","date","fee_units","transaction_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","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":21,"instrument_group":"group-b","transaction_count":2},{"date":"2026-10-03","row_id":"row-3","fee_units":17,"instrument_group":"group-a","transaction_count":3},{"date":"2026-10-04","row_id":"row-4","fee_units":33,"instrument_group":"group-b","transaction_count":4}],"maxItems":200,"minItems":0}}},"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_6rizVQqJlQkWHBKMnpDQ9","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 three local analytical reports (record quality audit, string normalisation, and keyed dataset comparison) on up to 200 rows of transaction fee observation data (fee_units, transaction_count).","exampleAgentPrompt":"Can you run a record quality audit, string normalisation, and keyed dataset comparison on my two sets of transaction fee observations? Here are the rows: primary dataset has row-1 (2026-10-01, group-a, fee_units=10, transaction_count=1), row-2 (2026-10-02, group-b, fee_units=20, transaction_count=2); comparison dataset has the same keys but fee_units=10 and fee_units=21 respectively.","exampleUseCases":[{"title":"Pre-load data quality check for fee records","prompt":"Before I load these 150 transaction fee rows into my data warehouse, can you run a record quality audit and string normalisation on them to catch any bad values or inconsistent instrument_group names? Here are the rows with date, row_id, fee_units, and transaction_count."},{"title":"Reconciling two fee datasets by key","prompt":"I have two extracts of transaction fee observations for October 2026 — one from our trading system and one from the settlement system — both with the same row IDs. Can you do a keyed dataset comparison to show me where fee_units or transaction_count differ between them?"},{"title":"Cleaning instrument group labels in fee data","prompt":"My transaction fee dataset has messy instrument_group strings with mixed casing and whitespace — can you run a string normalisation report on these 80 rows so I can see what gets cleaned up before I use them for reporting?"}],"resultDescription":"Three independent analytical reports returned together: (1) a record quality audit flagging missing, null, or out-of-range values across fee_units and transaction_count fields; (2) a string normalisation report showing standardised versions of text fields like instrument_group; (3) a keyed dataset comparison report highlighting rows where the two supplied datasets differ by key (row_id). All analysis is performed locally on the supplied data — no external lookups or predictions.","failureModes":["Fewer than 1 row supplied — validation error","More than 200 rows supplied — request rejected with max items error","Row missing required fields (row_id, instrument_group, date, fee_units, transaction_count) — schema validation error","Date field does not match YYYY-MM-DD pattern — schema validation error","fee_units or transaction_count outside allowed numeric range — schema validation error","row_id exceeds 80 characters — schema validation error","Payment of 0.01 USDC not provided or rejected — 402 Payment Required"],"whenToPreferThis":"Choose this endpoint when you need three specific analytical operations — record quality audit, string normalisation, and keyed dataset comparison — applied together to transaction fee observations (fee_units, transaction_count) in a single call for $0.01. Prefer it over building your own pipeline when you need a quick, cheap, offline-safe data QA pass on up to 200 rows without sending data to a live prediction or external enrichment service.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-26T12:32:19.005Z","isFirstParty":false,"canonicalSlug":"transaction-fee-observations-record-quality-audit-string-5cb3637d"}