{"uid":"cap_Csl-ZwPJqaY7187p8LVCG","slug":"record-routing-analytics-quality-audit-string-normalisation-date-pivot-b76e1296","name":"Record Routing Analytics: Quality Audit + String Normalisation + Date Pivot","description":"Record routing — Record quality audit + String normalisation + Date by category pivot: Record quality audit + String normalisation + Date by category pivot for supplied record routing records (accepted_records, rejected_records). 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-19-206?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","accepted_records","rejected_records"],"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},"accepted_records":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"rejected_records":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","dataset_group":"group-a","accepted_records":10,"rejected_records":1},{"date":"2026-10-02","row_id":"row-2","dataset_group":"group-b","accepted_records":20,"rejected_records":2},{"date":"2026-10-03","row_id":"row-3","dataset_group":"group-a","accepted_records":15,"rejected_records":3},{"date":"2026-10-04","row_id":"row-4","dataset_group":"group-b","accepted_records":30,"rejected_records":4}],"maxItems":200,"minItems":1},"field":{"enum":["accepted_records","rejected_records"],"type":"string","default":"accepted_records"}}},"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_wRKbfgRz6EYHIzF-azznJ","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 bundled analytical reports on record routing data — quality audit, string normalisation, and date-by-category pivot — for up to 200 rows of accepted/rejected record counts.","exampleAgentPrompt":"Can you run a quality audit, string normalisation, and date-by-category pivot on my record routing data? I have rows with dataset groups like 'group-a' and 'group-b', dates from 2026-10-01 to 2026-10-04, and I want to analyse the accepted_records field.","exampleUseCases":[{"title":"ETL pipeline quality check","prompt":"I've got a batch of record routing logs with accepted and rejected counts per dataset group — can you audit the quality, normalise the group name strings, and pivot the accepted_records by date and category so I can see where things went wrong?"},{"title":"Rejected records trend analysis","prompt":"Run a date-by-category pivot on my routing data focusing on rejected_records — I have about 150 rows across groups like 'group-a' through 'group-d' spanning the last month, and I want to see the rejection trend by group over time."},{"title":"Data normalisation for downstream reporting","prompt":"My record routing dataset has inconsistent string formatting in the dataset_group field and I need it normalised before reporting — can you also include a quality audit and a date pivot for accepted_records so I get all three reports in one go?"}],"resultDescription":"Three independent analytical reports delivered together: (1) a record quality audit flagging issues in the supplied routing data, (2) string normalisation output for text fields, and (3) a pivot table of accepted or rejected record counts grouped by date and category. All computed locally from the supplied rows with no external lookups.","failureModes":["Rows array empty or missing — minimum 1 row required","More than 200 rows submitted — exceeds maximum batch size","Invalid date format — must match YYYY-MM-DD pattern","row_id missing or empty — required field per row","accepted_records or rejected_records outside numeric bounds (-1e12 to 1e12)","Invalid field enum value — must be 'accepted_records' or 'rejected_records'","Payment not included or insufficient — endpoint costs $0.01 USDC per call"],"whenToPreferThis":"Choose this endpoint when you need three bundled analytical operations — quality audit, string normalisation, and date pivot — on record routing data in a single $0.01 call. It is ideal for ETL validation workflows, data pipeline monitoring, and pre-reporting data hygiene checks where you have up to 200 rows of accepted/rejected routing records and want all three reports without making separate API calls.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-23T18:53:24.304Z","isFirstParty":false,"canonicalSlug":"record-routing-analytics-quality-audit-string-normalisation-date-pivot-b76e1296"}