{"uid":"cap_1c2Bbj8y7R95aWwyOIjZU","slug":"schema-conformity-string-normalisation-numeric-row-ordering-2431a03c","name":"Schema Conformity — String Normalisation + Numeric Row Ordering","description":"Schema conformity — String normalisation + Numeric row ordering: String normalisation + Numeric row ordering for supplied schema conformity records (valid_records, checked_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-02-025?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","valid_records","checked_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},"valid_records":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"checked_records":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","dataset_group":"group-a","valid_records":10,"checked_records":1},{"date":"2026-10-02","row_id":"row-2","dataset_group":"group-b","valid_records":20,"checked_records":2},{"date":"2026-10-03","row_id":"row-3","dataset_group":"group-a","valid_records":15,"checked_records":3},{"date":"2026-10-04","row_id":"row-4","dataset_group":"group-b","valid_records":30,"checked_records":4}],"maxItems":200,"minItems":1},"field":{"enum":["valid_records","checked_records"],"type":"string","default":"valid_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_5CJgU_Jdnk7r_x_RGLnyQ","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 orders rows numerically for schema conformity records (valid_records, checked_records), producing two independent analytical reports for up to 200 rows.","exampleAgentPrompt":"Can you run string normalisation and numeric row ordering on my schema conformity records? I have up to 50 rows with fields like valid_records and checked_records — I want both reports using valid_records as the target field.","exampleUseCases":[{"title":"Audit data pipeline conformity records","prompt":"I have 80 schema conformity records from our data pipeline with date, dataset_group, valid_records, and checked_records columns — can you normalise the string fields and order the rows numerically by valid_records, and give me both reports?"},{"title":"Sort and clean quality check dataset","prompt":"Here are 120 rows of quality check data with row IDs, groups, and checked_records values — please run string normalisation and numeric row ordering on them using checked_records as the field, and return the two analysis reports."},{"title":"Prepare conformity rows for downstream reporting","prompt":"I need to prep my schema conformity batch of 30 rows for a downstream report — run string normalisation and numeric ordering on the valid_records field across all rows and give me the two local analytical reports."}],"resultDescription":"Two independent analytical reports: (1) a string normalisation report showing how string fields (row_id, dataset_group, date) have been normalised, and (2) a numeric row ordering report showing rows ranked/sorted by the selected numeric field (valid_records or checked_records). No external lookups or live data — purely local analytical processing of the supplied rows.","failureModes":["Input array exceeds 200 rows — request rejected","Missing required fields (row_id, date, valid_records, checked_records) on any row — validation error","Date field not matching YYYY-MM-DD pattern — schema validation failure","Numeric values outside allowed range (-1e12 to 1e12) — rejected","Empty rows array (minItems: 1 not met) — error response","Invalid field enum value (must be valid_records or checked_records) — bad request"],"whenToPreferThis":"Choose this endpoint when you need both string normalisation and numeric row ordering applied together to schema conformity records (up to 200 rows) in a single low-cost call. Ideal when you want two bundled local analytical reports without any live lookups, external API calls, or AI-generated predictions — purely deterministic processing of supplied data.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-14T00:37:28.561Z","isFirstParty":false,"canonicalSlug":"schema-conformity-string-normalisation-numeric-row-ordering-2431a03c"}