{"uid":"cap_DnidappjlsBdlqcaihrbO","slug":"transformation-throughput-analytics-record-quality-audit-string-2ef460ed","name":"Transformation Throughput Analytics: Record Quality Audit + String Normalisation + Date by Category Pivot","description":"Transformation throughput — Record quality audit + String normalisation + Date by category pivot: Record quality audit + String normalisation + Date by category pivot for supplied transformation throughput records (processed_rows, duration_seconds). 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-13-206?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","processed_rows","duration_seconds"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"dataset_group":{"type":"string","default":"","maxLength":80},"processed_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"duration_seconds":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","dataset_group":"group-a","processed_rows":10,"duration_seconds":1},{"date":"2026-10-02","row_id":"row-2","dataset_group":"group-b","processed_rows":20,"duration_seconds":2},{"date":"2026-10-03","row_id":"row-3","dataset_group":"group-a","processed_rows":15,"duration_seconds":3},{"date":"2026-10-04","row_id":"row-4","dataset_group":"group-b","processed_rows":30,"duration_seconds":4}],"maxItems":200,"minItems":1},"field":{"enum":["processed_rows","duration_seconds"],"type":"string","default":"processed_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_-a0PXf0LeN7HkwHJE7Vcz","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 date-by-category pivot) on transformation throughput records containing processed_rows and duration_seconds fields, for up to 200 rows.","exampleAgentPrompt":"Can you run a record quality audit, string normalisation, and date-by-category pivot on my transformation throughput data? I have up to 50 rows with fields like row_id, dataset_group, date, processed_rows, and duration_seconds — I want to analyse the processed_rows field.","exampleUseCases":[{"title":"ETL pipeline quality audit","prompt":"I've got a batch of 80 transformation throughput records with row IDs, dataset groups, dates, and processed_rows counts — can you audit their data quality, normalise the string fields, and give me a pivot of processed_rows by date and category?"},{"title":"Duration analysis across pipeline groups","prompt":"Run the three analytics reports on my 120 pipeline run records — I want to focus on duration_seconds, check for quality issues, normalise the dataset group names, and see a date-by-category breakdown."},{"title":"Data cleaning for transformation logs","prompt":"I have transformation logs from last month with fields row_id, dataset_group, date, processed_rows, and duration_seconds — can you do a string normalisation pass and record quality audit, plus pivot processed_rows by date and group, for about 40 rows?"}],"resultDescription":"Three independent analytical reports: (1) a record quality audit flagging issues such as nulls, out-of-range values, and structural problems; (2) a string normalisation report cleaning and standardising text fields like dataset_group; and (3) a date-by-category pivot summarising the selected numeric field (processed_rows or duration_seconds) aggregated by date and dataset_group — all derived locally from the supplied data with no external lookups.","failureModes":["More than 200 rows submitted — request rejected or truncated","Missing required fields (row_id, dataset_group, date, processed_rows, duration_seconds) — validation error","Invalid date format (not YYYY-MM-DD) — schema validation failure","Null or out-of-range numeric values may affect pivot and quality report accuracy","Invalid field enum value (not processed_rows or duration_seconds) — rejected request","Payment of 0.01 USDC not included or declined — request not processed"],"whenToPreferThis":"Choose this endpoint when you need three combined analytical reports — quality audit, string normalisation, and date-by-category pivot — on transformation throughput data in a single low-cost call. It is ideal for data engineers who want a quick, bundled analysis of ETL pipeline records (processed_rows, duration_seconds) without setting up external tooling. Prefer it over general-purpose analytics when your data fits the schema (up to 200 rows with the five required fields) and you need all three report types simultaneously for a flat $0.01 USDC fee.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-28T19:41:41.398Z","isFirstParty":false,"canonicalSlug":"transformation-throughput-analytics-record-quality-audit-string-2ef460ed"}