{"uid":"cap_WUiPaolZfteqMFEwIa8On","slug":"data-ingestion-batches-record-quality-audit-string-normalisation-df5d5edd","name":"Data Ingestion Batches — Record Quality Audit + String Normalisation + Adjacent Row Changes","description":"Data ingestion batches — Record quality audit + String normalisation + Adjacent row changes: Record quality audit + String normalisation + Adjacent row changes for supplied data ingestion batches records (received_rows, accepted_rows). 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-analytics-01-200?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","received_rows","accepted_rows"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"accepted_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80},"received_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","accepted_rows":1,"dataset_group":"group-a","received_rows":10},{"date":"2026-10-02","row_id":"row-2","accepted_rows":2,"dataset_group":"group-b","received_rows":20},{"date":"2026-10-03","row_id":"row-3","accepted_rows":3,"dataset_group":"group-a","received_rows":15},{"date":"2026-10-04","row_id":"row-4","accepted_rows":4,"dataset_group":"group-b","received_rows":30}],"maxItems":200,"minItems":1},"field":{"enum":["received_rows","accepted_rows"],"type":"string","default":"received_rows"}}},"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_yiXcQh61jOgk3ujV_UDfi","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 analytical reports (record quality audit, string normalisation, and adjacent row change detection) on up to 200 data ingestion batch rows covering received_rows and accepted_rows fields.","exampleAgentPrompt":"Run the three-in-one ingestion batch analytics — record quality audit, string normalisation, and adjacent row changes — on these rows for the received_rows field: row-1 on 2026-10-01 with group-a, received 10 and accepted 1; row-2 on 2026-10-02 with group-b, received 20 and accepted 2; row-3 on 2026-10-03 with group-a, received 15 and accepted 3.","exampleUseCases":[{"title":"Pipeline acceptance rate quality check","prompt":"I have 50 rows from our nightly ingestion pipeline with dataset groups 'raw_events' and 'enriched_events' — can you run a record quality audit, string normalisation, and adjacent row change analysis on the received_rows field to flag any data quality issues?"},{"title":"Detecting sudden drops in accepted rows","prompt":"Our ingestion batch for October had some suspicious dips in accepted_rows — can you run adjacent row change detection plus a quality audit on these 80 rows so I can see where the anomalies occurred?"},{"title":"Normalising inconsistent dataset group names","prompt":"We have 120 ingestion batch records where the dataset_group strings look messy with inconsistent casing and spacing — please run the string normalisation report alongside the quality audit on accepted_rows so we can clean up the data."}],"resultDescription":"Returns three independent analytical reports: (1) a record quality audit flagging issues in the supplied ingestion batch rows, (2) a string normalisation report identifying and correcting inconsistencies in string fields, and (3) an adjacent row changes report showing value deltas between consecutive rows — all computed locally against the submitted data without external lookups.","failureModes":["More than 200 rows submitted — request rejected with validation error","Missing required fields (row_id, dataset_group, date, received_rows, accepted_rows) — row rejected or error returned","Invalid date format (not YYYY-MM-DD) — validation failure","Field selector not one of 'received_rows' or 'accepted_rows' — schema validation error","Numeric values outside allowed range (±1,000,000,000,000) — validation rejection","Empty rows array — minimum items constraint violated"],"whenToPreferThis":"Choose this endpoint when you need three simultaneous analytical passes (quality audit, string normalisation, adjacent row changes) on a single batch of up to 200 ingestion records in one cost-efficient call. Ideal for ETL pipeline monitoring, data quality gates, and batch validation workflows where you want bundled analytics without external lookups or predictions. Prefer over single-report alternatives when all three report types are needed at once.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-17T00:46:34.310Z","isFirstParty":false,"canonicalSlug":"data-ingestion-batches-record-quality-audit-string-normalisation-df5d5edd"}