{"uid":"cap_C5JNe3rC7KJasSJ6DpHv1","slug":"data-ingestion-batches-record-quality-audit-string-normalisation-c30b17f9","name":"Data Ingestion Batches — Record Quality Audit + String Normalisation + Numeric Row Ordering","description":"Data ingestion batches — Record quality audit + String normalisation + Numeric row ordering: Record quality audit + String normalisation + Numeric row ordering 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-01-196?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_6f1zeOVoDSbbEafkHu3lW","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 independent analytical reports (record quality audit, string normalisation, and numeric row ordering) on up to 200 rows of data ingestion batch records containing received_rows and accepted_rows fields.","exampleAgentPrompt":"Can you run a record quality audit, string normalisation, and numeric row ordering on my ingestion batch data? I have 4 rows: row-1 on 2026-10-01 in group-a with 10 received and 1 accepted, row-2 on 2026-10-02 in group-b with 20 received and 2 accepted, row-3 on 2026-10-03 in group-a with 15 received and 3 accepted, and row-4 on 2026-10-04 in group-b with 30 received and 4 accepted — please order by received_rows.","exampleUseCases":[{"title":"ETL pipeline batch quality check","prompt":"I have a batch of 50 ingestion records from last week's ETL run with dataset groups like 'sales' and 'inventory' — can you audit their record quality, normalise the group name strings, and rank them by accepted_rows so I can spot which datasets had the worst acceptance rates?"},{"title":"Daily ingestion report for data ops team","prompt":"Run the three standard reports — quality audit, string normalisation, and numeric ordering by received_rows — on today's ingestion batch. It's 12 rows across groups 'crm-feed' and 'erp-feed' with dates from 2026-11-01 to 2026-11-12."},{"title":"Anomaly triage in batch row counts","prompt":"My ingestion monitoring flagged some weird row counts across 30 records in groups 'clickstream' and 'transactions' — can you do a quality audit and then order those rows numerically by accepted_rows so I can find which records look most off?"}],"resultDescription":"Three independent analytical reports delivered together: (1) a record quality audit highlighting issues in the ingestion batch rows, (2) a string normalisation report on dataset_group and related string fields, and (3) a numeric row ordering report ranking rows by the selected field (received_rows or accepted_rows). All computed locally without external lookups or predictions.","failureModes":["More than 200 rows submitted — request exceeds maxItems limit and will be rejected","Missing required fields (row_id, dataset_group, date, received_rows, accepted_rows) cause validation errors","Date strings not matching YYYY-MM-DD pattern cause schema validation failure","Numeric values outside ±1,000,000,000,000 range are rejected","Empty rows array (minItems:1 violated) returns an error","Invalid field enum value (not 'received_rows' or 'accepted_rows') is rejected"],"whenToPreferThis":"Choose this endpoint when you need three bundled analytical reports — quality audit, string normalisation, and numeric ordering — on a batch of up to 200 data ingestion rows at a flat cost of $0.01 USDC. It is ideal for data engineering and ETL contexts where you have received_rows and accepted_rows metrics and need offline, local analysis without any external data lookups, live predictions, or professional assessments. Prefer it over single-report endpoints when you need all three report types in one call.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-16T18:48:40.507Z","isFirstParty":false,"canonicalSlug":"data-ingestion-batches-record-quality-audit-string-normalisation-c30b17f9"}