{"uid":"cap_SPc_wn2m5iLjHhX-XJcE-","slug":"label-review-analytics-record-quality-audit-string-normalisation-6e4ffbb0","name":"Label Review Analytics: Record Quality Audit + String Normalisation + Numeric Interval Filter","description":"Label review — Record quality audit + String normalisation + Numeric interval filter: Record quality audit + String normalisation + Numeric interval filter 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-12-197?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"},"maximum":{"type":"number","default":100,"maximum":1000000000000,"minimum":-1000000000000},"minimum":{"type":"number","default":0,"maximum":1000000000000,"minimum":-1000000000000}}},"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_Oho2bhw_S8PI2CVLdbhHY","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 on label review data: record quality audit, string normalisation, and numeric interval filtering for reviewed_records or changed_labels fields across up to 200 rows.","exampleAgentPrompt":"Can you run a quality audit, string normalisation, and numeric interval filter on my label review data? I have up to 50 rows with fields like dataset_group, date, reviewed_records, and changed_labels — filter on the reviewed_records field between 0 and 100.","exampleUseCases":[{"title":"Annotation pipeline data quality check","prompt":"I have a batch of 120 label review records from two dataset groups collected last month — can you audit their quality, normalise the dataset_group strings, and flag any reviewed_records values outside the range 5 to 500?"},{"title":"Changed labels outlier detection","prompt":"Run an interval filter on the changed_labels field for my 80-row annotation review dataset, keeping only values between 0 and 50, and include the quality audit and string normalisation reports too."},{"title":"Pre-ingestion label data validation","prompt":"Before I load this label review CSV into our warehouse, can you do a full quality audit, normalise the string columns, and filter out any reviewed_records outside 10 to 200 for these 200 rows?"}],"resultDescription":"Three independent analytical reports: (1) a record quality audit flagging missing, malformed, or suspect entries; (2) a string normalisation report standardising dataset_group and other string fields; (3) a numeric interval filter report identifying rows where the chosen field (reviewed_records or changed_labels) falls within or outside the specified minimum/maximum range. All computed locally with no external calls.","failureModes":["Fewer than 1 or more than 200 rows submitted — request rejected","Invalid date format (not YYYY-MM-DD) — row fails validation","Missing required field (row_id, reviewed_records, or changed_labels) — row excluded or error returned","Non-numeric value in reviewed_records or changed_labels — treated as null","minimum greater than maximum — interval filter may return empty results","Payment not included or insufficient — 402 response, no reports returned"],"whenToPreferThis":"Choose this endpoint when you need three simultaneous analytical passes (quality audit, string normalisation, numeric filtering) on label review data in a single $0.01 call, without needing live lookups, ML predictions, or external API calls. Ideal for pre-ingestion validation of annotation or label review datasets up to 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:35:42.651Z","isFirstParty":false,"canonicalSlug":"label-review-analytics-record-quality-audit-string-normalisation-6e4ffbb0"}