{"uid":"cap_jxNN2IE-tFbpvlwretJyN","slug":"label-review-analytics-string-normalisation-exact-row-deduplication-0a5c7881","name":"Label Review Analytics: String Normalisation + Exact Row Deduplication","description":"Label review — String normalisation + Exact row deduplication: String normalisation + Exact row deduplication for supplied label review records (reviewed_records, changed_labels). 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-12-020?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}}},"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_UzR6_o3W2AAtqNzB8rIhe","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 two local analytical reports on label review data: string normalisation and exact row deduplication, for up to 200 rows of reviewed_records and changed_labels data.","exampleAgentPrompt":"Can you run string normalisation and exact row deduplication on my label review data? I have rows with row_id, dataset_group, date, reviewed_records, and changed_labels fields — here are up to 200 rows I need both reports for.","exampleUseCases":[{"title":"ML annotation pipeline data cleaning","prompt":"I have 150 rows of label review records from our annotation pipeline with columns row_id, dataset_group, date, reviewed_records, and changed_labels — can you run string normalisation and exact deduplication on them and give me both reports?"},{"title":"Detecting duplicate label review submissions","prompt":"Our labelling team submitted review records and I suspect there are exact duplicate rows. Can you deduplicate them and also normalise any inconsistent string values across the dataset_group and row_id fields?"},{"title":"Multi-group label audit data quality check","prompt":"I've got label review data across two dataset groups covering October 2026, about 80 rows total with reviewed_records and changed_labels counts — please run both the string normalisation report and the exact row deduplication report on it."}],"resultDescription":"Two analytical reports per call: (1) a string normalisation report identifying and standardising inconsistent string values in the label review fields, and (2) an exact row deduplication report identifying and flagging fully duplicate rows across the supplied data. No external lookups or predictions are made; all analysis is performed locally on the supplied rows.","failureModes":["More than 200 rows submitted — request will be rejected or truncated","Missing required fields (row_id, dataset_group, date, reviewed_records, changed_labels) cause row-level validation errors","Invalid date format (not YYYY-MM-DD) triggers schema validation failure","Numeric values for reviewed_records or changed_labels outside allowed range cause rejection","Empty rows array returns an error as minItems is 1"],"whenToPreferThis":"Choose this endpoint when you need lightweight, offline data quality analysis specifically for label review records — no external API, no ML prediction, just fast local string normalisation and exact deduplication for batches up to 200 rows. Ideal for annotation pipeline auditing, label tracking cleanup, or pre-processing before model training data ingestion. Prefer this over full data warehouse deduplication tools when you have a small, well-structured label review batch and want two targeted reports at minimal cost.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:38:56.230Z","isFirstParty":false,"canonicalSlug":"label-review-analytics-string-normalisation-exact-row-deduplication-0a5c7881"}