{"uid":"cap_ClFwqJk8TXMNLJHpOpOya","slug":"transaction-fee-observations-record-quality-audit-explicit-missing-3bd5400b","name":"Transaction Fee Observations — Record Quality Audit + Explicit Missing-Value Fill","description":"Transaction fee observations — Record quality audit + Explicit missing-value fill: Record quality audit + Explicit missing-value fill 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-03-019?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"},"method":{"enum":["zero","mean","median"],"type":"string","default":"median"}}},"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_u4q4NnJPE_CbhxwlAkNUJ","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 data quality and fills missing values (via zero, mean, or median) for transaction fee observation records containing fee_units and transaction_count fields.","exampleAgentPrompt":"Can you audit the data quality of my transaction fee observations and fill in any missing fee_units values using the median — I have about 50 rows with fields like instrument_group, date, fee_units, and transaction_count?","exampleUseCases":[{"title":"Pre-analysis fee data cleanup","prompt":"I have 120 rows of transaction fee data with some missing fee_units values — can you run a quality audit on them and fill the gaps using the median so I can trust the dataset before I start my analysis?"},{"title":"Zero-fill missing transaction counts","prompt":"My transaction_count column has some nulls in my fee observations dataset — please audit the records for quality issues and fill those missing transaction_count values with zero. Here are my rows with instrument_group, date, fee_units, and transaction_count."},{"title":"Mean imputation for fee data pipeline","prompt":"Before I pass my transaction fee records into the pipeline, I need a quality audit and want any missing fee_units filled using the mean — I've got about 80 rows to check."}],"resultDescription":"Returns two independent reports: (1) a record quality audit identifying issues such as nulls, anomalies, and completeness problems across the supplied rows; and (2) an explicit missing-value fill report showing imputed values for the specified field (fee_units or transaction_count) using the chosen method (zero, mean, or median). Covers up to 200 rows per call.","failureModes":["More than 200 rows submitted — exceeds maxItems limit","Missing required fields (row_id, instrument_group, date) in one or more rows","Invalid date format not matching YYYY-MM-DD pattern","Invalid field enum value (must be 'fee_units' or 'transaction_count')","Invalid method enum value (must be 'zero', 'mean', or 'median')","Empty rows array submitted","Payment failure or insufficient USDC balance"],"whenToPreferThis":"Choose this endpoint when you have up to 200 rows of transaction fee observation data (with fee_units and transaction_count fields) and need both a structured quality audit and deterministic missing-value imputation in a single call. It is specifically designed for financial fee datasets organized by instrument_group and date. Prefer it over generic data cleaning tools when you need both audit and imputation reports together at low cost, 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":"2026-10-28T06:47:15.086Z","isFirstParty":false,"canonicalSlug":"transaction-fee-observations-record-quality-audit-explicit-missing-3bd5400b"}