{"uid":"cap_QzZS6uxFV4B0-RIRZ0b9L","slug":"label-review-analytics-record-quality-audit-string-normalisation-5c094dd7","name":"Label Review Analytics — Record Quality Audit, String Normalisation & Numeric Row Ordering","description":"Label review — Record quality audit + String normalisation + Numeric row ordering: Record quality audit + String normalisation + Numeric row ordering for supplied label review records (reviewed_records, changed_labels). 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-12-196?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","reviewed_records","changed_labels"],"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},"changed_labels":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"reviewed_records":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","dataset_group":"group-a","changed_labels":1,"reviewed_records":10},{"date":"2026-10-02","row_id":"row-2","dataset_group":"group-b","changed_labels":2,"reviewed_records":20},{"date":"2026-10-03","row_id":"row-3","dataset_group":"group-a","changed_labels":3,"reviewed_records":15},{"date":"2026-10-04","row_id":"row-4","dataset_group":"group-b","changed_labels":4,"reviewed_records":30}],"maxItems":200,"minItems":1},"field":{"enum":["reviewed_records","changed_labels"],"type":"string","default":"reviewed_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_RGnxVX-BMVfvORK0H9yLe","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 independent analytical reports on label review data: record quality audit, string normalisation, and numeric row ordering for up to 200 rows of reviewed_records and changed_labels data.","exampleAgentPrompt":"Can you run a quality audit, string normalisation, and numeric row ordering on these label review records I have — about 50 rows with reviewed_records and changed_labels fields grouped by dataset_group — and order results by reviewed_records?","exampleUseCases":[{"title":"ML annotation pipeline quality check","prompt":"I have 120 rows of label review logs with row_id, dataset_group, date, reviewed_records, and changed_labels — can you run a record quality audit, string normalisation, and row ordering on them sorted by changed_labels to spot any data issues before I hand them off to the model team?"},{"title":"Dataset group string cleanup","prompt":"My label review export has inconsistent dataset_group names and I need string normalisation plus a quality audit on up to 80 rows — can you run those three reports on it ordered by reviewed_records?"},{"title":"Daily label review numeric ranking","prompt":"Can you take today's label review batch — about 30 rows across group-a and group-b — and give me a quality audit plus numeric row ordering by reviewed_records so I can see which entries had the most records reviewed?"}],"resultDescription":"Returns three independent analytical reports: (1) a record quality audit flagging data issues in the supplied rows, (2) a string normalisation report cleaning dataset_group and related string fields, and (3) a numeric row ordering report ranking rows by the selected field (reviewed_records or changed_labels). All computed locally with no external lookups.","failureModes":["Submitting more than 200 rows returns a validation error","Missing required fields (row_id, date, reviewed_records, changed_labels) causes row-level rejection","Dates not matching YYYY-MM-DD pattern are rejected","Numeric values outside ±1,000,000,000,000 bounds cause schema validation failure","Empty rows array returns an error","Invalid field enum value (not reviewed_records or changed_labels) causes a bad request error"],"whenToPreferThis":"Choose this endpoint when you have up to 200 rows of label review data and need all three of record quality auditing, string normalisation, and numeric ordering in a single low-cost call ($0.01 USDC). It is ideal for ML data ops teams validating annotation batches before ingestion, where no live prediction, external lookup, or professional assessment is needed — purely local analytical computation on supplied data.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:37:34.141Z","isFirstParty":false,"canonicalSlug":"label-review-analytics-record-quality-audit-string-normalisation-5c094dd7"}