{"uid":"cap_exii1DS16V69ZmOfw34dq","slug":"validation-rule-results-string-normalisation-two-measure-correlation-214cd92e","name":"Validation Rule Results — String Normalisation + Two-Measure Correlation","description":"Validation rule results — String normalisation + Two-measure correlation: String normalisation + Two-measure correlation for supplied validation rule results records (passed_rules, total_rules). 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-08-033?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","passed_rules","total_rules"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"total_rules":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"passed_rules":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","total_rules":1,"passed_rules":10,"dataset_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","total_rules":2,"passed_rules":20,"dataset_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","total_rules":3,"passed_rules":15,"dataset_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","total_rules":4,"passed_rules":30,"dataset_group":"group-b"}],"maxItems":200,"minItems":1}}},"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_GylOw0RgpznySTdjKW4bQ","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":"Analyzes up to 200 validation rule result records by normalizing string fields and computing two-measure correlation between passed_rules and total_rules, returning two independent analytical reports.","exampleAgentPrompt":"I have validation rule results for two dataset groups — 'group-a' and 'group-b' — covering dates from 2026-10-01 to 2026-10-04, with passed_rules and total_rules values for each row. Can you normalize the string fields and compute the correlation between passed_rules and total_rules across all rows, returning both reports?","exampleUseCases":[{"title":"Data pipeline quality correlation check","prompt":"I have 150 rows of validation rule results from my ETL pipeline across three dataset groups, each with a date, passed_rules count, and total_rules count. Can you normalize the dataset group strings and compute the correlation between passed_rules and total_rules so I can see how consistent my rule pass rate is?"},{"title":"Multi-group validation audit","prompt":"My data quality team logged rule results for group-alpha and group-beta across October 2026 — about 80 rows total with row IDs, dates, and counts of passed and total rules. Run string normalization and a two-measure correlation analysis on those records and give me both reports."},{"title":"Rule compliance trend analysis","prompt":"I've got 200 rows of daily validation rule outcomes across several dataset groups from Q3, each recording how many rules passed out of the total. Please normalize the string identifiers and compute the correlation between the two numeric measures so I can understand how closely they track each other."}],"resultDescription":"Two independent analytical reports: (1) a string normalization report cleaning and standardizing the text fields (row_id, dataset_group, date) across the submitted rows, and (2) a two-measure correlation report quantifying the statistical relationship between passed_rules and total_rules across all submitted records. No external lookups or predictions are included.","failureModes":["Fewer than 1 row submitted — minimum of 1 row required","More than 200 rows submitted — exceeds maximum batch size","Missing required fields (row_id, dataset_group, date, passed_rules, total_rules) on any row — validation error","Date fields not matching YYYY-MM-DD pattern — schema validation failure","Numeric values outside allowed range (±1,000,000,000,000) — rejected","Null values for both passed_rules and total_rules across all rows may degrade correlation computation"],"whenToPreferThis":"Choose this endpoint when you need both string field normalization and a two-measure correlation analysis on validation rule result records in a single call. Prefer it over sibling endpoints when your primary interest is the statistical relationship between passed_rules and total_rules alongside string cleaning, and you do not need outlier flagging, deduplication, or daily sum series — those are covered by other specialized endpoints in the same family.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-11T12:48:38.069Z","isFirstParty":false,"canonicalSlug":"validation-rule-results-string-normalisation-two-measure-correlation-214cd92e"}