{"uid":"cap_ULKh8XuEBOOn3MoOQeyWB","slug":"validation-rule-results-analyzer-record-quality-audit-string-c3095a5b","name":"Validation Rule Results Analyzer — Record Quality Audit, String Normalisation & Base-100 Series","description":"Validation rule results — Record quality audit + String normalisation + Base-100 series: Record quality audit + String normalisation + Base-100 series for supplied validation rule results records (passed_rules, total_rules). 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-08-201?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},"field":{"enum":["passed_rules","total_rules"],"type":"string","default":"passed_rules"},"base_index":{"type":"integer","default":0,"maximum":199,"minimum":0}}},"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_c8GhjBxreixxmZsV8PDck","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 (record quality audit, string normalisation, and base-100 index series) on supplied validation rule result records (passed_rules, total_rules) for up to 200 rows.","exampleAgentPrompt":"Can you run the record quality audit, string normalisation, and base-100 series reports on my validation rule results? I have 4 rows: row-1 on 2026-10-01 with passed_rules=10 and total_rules=1 in group-a, row-2 on 2026-10-02 with passed_rules=20 total_rules=2 in group-b, row-3 on 2026-10-03 passed_rules=15 total_rules=3 in group-a, row-4 on 2026-10-04 passed_rules=30 total_rules=4 in group-b — use passed_rules as the field and start the base-100 index from row 0.","exampleUseCases":[{"title":"Daily pipeline validation compliance audit","prompt":"I have 50 daily validation snapshots across two dataset groups — can you run a record quality audit, string normalisation, and base-100 index series on the passed_rules field, starting the index from the first row? I want to see how compliance has trended over time."},{"title":"Spotting rule coverage gaps across groups","prompt":"Can you audit these 120 rows of validation results — each row has a row_id, date, dataset_group, passed_rules, and total_rules — and give me the quality audit, string normalisation, and base-100 series reports focusing on total_rules, indexed from row 0?"},{"title":"Baseline-relative rule pass-rate indexing","prompt":"I want to track how my rule pass counts have evolved relative to a specific baseline row — run the record quality audit, string normalisation, and base-100 series on passed_rules for my 80 validation rows, setting the base index at row 10."}],"resultDescription":"Returns three independent analytical reports for the supplied rows: (1) a record quality audit flagging completeness and consistency issues per row, (2) a string normalisation report cleaning and standardising text fields like row_id and dataset_group, and (3) a base-100 index series for the selected numeric field (passed_rules or total_rules) rebased to 100 at the specified row. All computation is local with no external lookups.","failureModes":["Fewer than 1 or more than 200 rows submitted — rejected with validation error","Missing required fields (row_id, date, dataset_group, passed_rules, total_rules) in any row","Date strings not matching YYYY-MM-DD pattern — rejected by schema validation","base_index value out of range (must be 0–199 and within actual row count)","Null values in passed_rules or total_rules may affect numeric index computation","Payment not included or insufficient — x402 payment required at $0.01 USDC per call"],"whenToPreferThis":"Choose this endpoint when you need three bundled analytical views — quality audit, string normalisation, and base-100 indexing — on validation rule result data (passed_rules, total_rules) in a single low-cost call. It is best suited for offline/batch analysis of up to 200 rows with no need for external lookups, live data, or predictions. Prefer alternatives if you need real-time validation against a live schema, ML-based anomaly detection, or more than 200 rows processed at once.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-11T12:48:36.607Z","isFirstParty":false,"canonicalSlug":"validation-rule-results-analyzer-record-quality-audit-string-c3095a5b"}