{"uid":"cap_-tD_T6woSpqI094cMj_Kk","slug":"record-routing-analytics-quality-audit-string-normalisation-numeric-93659d75","name":"Record Routing Analytics: Quality Audit + String Normalisation + Numeric Distribution","description":"Record routing — Record quality audit + String normalisation + Numeric distribution: Record quality audit + String normalisation + Numeric distribution 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-19-193?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_Xv6ahavPOS59V31iwBryR","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 local analytical reports on record routing data — a record quality audit, string normalisation, and numeric distribution analysis — for up to 200 rows of accepted/rejected record counts.","exampleAgentPrompt":"Can you run a quality audit, string normalisation, and numeric distribution analysis 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":"Data pipeline quality check","prompt":"I've got a batch of record routing rows from last month with accepted_records and rejected_records counts per dataset group — can you run all three reports (quality audit, string normalisation, numeric distribution) on up to 200 of them so I can see if there are quality issues?"},{"title":"Accepted record distribution review","prompt":"Can you analyse the numeric distribution of accepted_records across my routing groups for dates in October 2026? I have about 50 rows across group-a and group-b and want to understand the spread."},{"title":"Rejected record string normalisation","prompt":"I need to run string normalisation and a quality audit on my rejected_records routing data — there are around 30 rows with dataset groups and dates, and I suspect some inconsistent formatting that's causing downstream issues."}],"resultDescription":"Three independent analytical reports covering: (1) a record quality audit flagging data issues, (2) string normalisation results for text fields like dataset_group, and (3) a numeric distribution summary for the selected numeric field (accepted_records or rejected_records). All computed locally with no external lookups, for up to 200 input rows.","failureModes":["Missing required fields (row_id, date, accepted_records, rejected_records) returns validation error","Date field not matching YYYY-MM-DD pattern causes schema rejection","Exceeding 200 rows causes request rejection","Null numeric values may affect distribution report completeness","Invalid field enum value (not 'accepted_records' or 'rejected_records') causes rejection"],"whenToPreferThis":"Choose this endpoint when you need lightweight, local analytical reporting on record routing datasets (up to 200 rows) covering quality auditing, string normalisation, and numeric distribution in a single $0.01 call. Ideal for data pipeline validation, pre-processing checks, and batch quality reviews where no external lookup or prediction is needed.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T06:39:38.752Z","isFirstParty":false,"canonicalSlug":"record-routing-analytics-quality-audit-string-normalisation-numeric-93659d75"}