{"uid":"cap_W-3GbIzYRMqOekqdDY4Vq","slug":"record-routing-string-normalisation-and-numeric-row-ordering-0c7f6dde","name":"Record Routing String Normalisation and Numeric Row Ordering","description":"Record routing — String normalisation + Numeric row ordering: String normalisation + Numeric row ordering for supplied record routing records (accepted_records, rejected_records). 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-analytics-19-025?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_16Hu7RWER8BxA6CIthSTN","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":"Normalises string fields and applies numeric row ordering to accepted_records and rejected_records columns across up to 200 record routing rows, returning two analytical reports.","exampleAgentPrompt":"I have 4 rows of record routing data — row-1 group-a 2026-10-01 with 10 accepted and 1 rejected, row-2 group-b 2026-10-02 with 20 accepted and 2 rejected, row-3 group-a 2026-10-03 with 15 accepted and 3 rejected, row-4 group-b 2026-10-04 with 30 accepted and 4 rejected — can you normalise the string fields and rank them by accepted_records?","exampleUseCases":[{"title":"Routing quality check for daily ETL batch","prompt":"Here are 6 rows from today's ETL run with row IDs, dataset groups, dates, and accepted and rejected record counts — normalise the string labels and give me both rows ordered by accepted_records so I can see which groups are performing best."},{"title":"Rejected records audit across routing groups","prompt":"I need to rank my routing dataset by rejected_records to spot which groups are failing most — I have 10 rows across group-a and group-b from October 2026, can you normalise the strings and order them numerically by rejected_records?"},{"title":"Pre-reporting data cleanup for routing metrics","prompt":"Before I build my weekly routing report, can you clean up the string fields and sort these 15 record routing rows by accepted_records? I'll paste the row IDs, dates, groups, and accept/reject counts now."}],"resultDescription":"Returns two analytical reports: one with normalised string representations of the supplied record routing rows, and one with rows ordered numerically by the selected field (accepted_records or rejected_records), covering up to 200 input rows processed entirely with local analytical engines.","failureModes":["Input array is empty or missing — requires at least 1 row","More than 200 rows supplied — exceeds maximum batch size","Date field does not match YYYY-MM-DD pattern — validation error","accepted_records or rejected_records values outside allowed range (-1e12 to 1e12)","field enum value not one of accepted_records or rejected_records","Missing required fields row_id, dataset_group, date — schema validation failure"],"whenToPreferThis":"Choose this endpoint when you need lightweight, offline string normalisation and numeric ordering of record routing data (accepted/rejected record counts) without any external lookups, predictions, or live data access. Ideal for ETL data quality checks, pre-reporting cleanup, and ranking routing rows by volume metrics across up to 200 rows at very low cost.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-24T00:54:07.976Z","isFirstParty":false,"canonicalSlug":"record-routing-string-normalisation-and-numeric-row-ordering-0c7f6dde"}