{"uid":"cap_cA9yUPvYLHwEwoLrUTXw4","slug":"transaction-fee-observations-record-quality-audit-iqr-outlier-flags-b47d35e8","name":"Transaction Fee Observations — Record Quality Audit + IQR Outlier Flags","description":"Transaction fee observations — Record quality audit + IQR outlier flags: Record quality audit + IQR outlier flags 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-03-014?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_aMjoWCCW6gs4kO7i1Roxk","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":"Audits up to 200 rows of transaction fee observation records for data quality issues and flags IQR-based outliers across fee_units or transaction_count fields.","exampleAgentPrompt":"Can you run a record quality audit and IQR outlier check on these transaction fee observations? I have about 50 rows with instrument_group, date, fee_units, and transaction_count — flag any quality issues and outliers on the fee_units field.","exampleUseCases":[{"title":"Audit daily fee data before reporting","prompt":"I need to quality-check my transaction fee dataset before I send it to the finance team — it has 80 rows with date, instrument_group, fee_units, and transaction_count. Can you run a record quality audit and flag any IQR outliers on fee_units?"},{"title":"Detect anomalous transaction counts","prompt":"Something looks off in my transaction count data — can you run an IQR outlier analysis on my transaction_count field across these 120 rows of fee observations and also audit them for any data quality problems?"},{"title":"Validate instrument group fee records","prompt":"Before I load this into the data warehouse, can you audit these 200 rows of instrument group fee records for quality issues and IQR-based outliers on fee_units? Each row has a row_id, instrument_group, date, fee_units, and transaction_count."}],"resultDescription":"Returns two independent reports: (1) a record quality audit identifying issues such as missing values, malformed dates, or invalid entries per row; and (2) IQR outlier flags marking which rows fall outside the interquartile range for the selected numeric field (fee_units or transaction_count). Both reports are computed locally without external lookups.","failureModes":["Exceeding 200 rows returns an error — batch must be split","Missing required fields (row_id, date, instrument_group) causes row rejection","Invalid date format (non-YYYY-MM-DD) triggers validation error","Numeric values outside ±1,000,000,000,000 are rejected","Empty rows array returns an error","Field enum value not in ['fee_units','transaction_count'] causes schema rejection"],"whenToPreferThis":"Choose this endpoint when you have up to 200 rows of transaction fee observation data and need both a structural data quality audit and IQR-based statistical outlier detection in a single low-cost call ($0.01 USDC). It is ideal for pre-load validation of fee datasets, catching bad rows before downstream reporting, or quickly flagging anomalous fee or count observations without any live external data dependency.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-28T06:47:06.975Z","isFirstParty":false,"canonicalSlug":"transaction-fee-observations-record-quality-audit-iqr-outlier-flags-b47d35e8"}