{"uid":"cap_F8l2ZuHF355tNxl1nbq3f","slug":"feature-availability-analytics-quality-audit-deduplication-interval-9c194c48","name":"Feature Availability Analytics: Quality Audit + Deduplication + Interval Filter","description":"Feature availability — Record quality audit + Exact row deduplication + Numeric interval filter: Record quality audit + Exact row deduplication + Numeric interval filter for supplied feature availability records (populated_features, expected_features). 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-10-214?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","populated_features","expected_features"],"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},"expected_features":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"populated_features":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","dataset_group":"group-a","expected_features":1,"populated_features":10},{"date":"2026-10-02","row_id":"row-2","dataset_group":"group-b","expected_features":2,"populated_features":20},{"date":"2026-10-03","row_id":"row-3","dataset_group":"group-a","expected_features":3,"populated_features":15},{"date":"2026-10-04","row_id":"row-4","dataset_group":"group-b","expected_features":4,"populated_features":30}],"maxItems":200,"minItems":1},"field":{"enum":["populated_features","expected_features"],"type":"string","default":"populated_features"},"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_OwlWb4sbNAzjTU99qpZAG","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 feature availability records: record quality audit, exact row deduplication, and numeric interval filtering for populated_features or expected_features values.","exampleAgentPrompt":"Can you run a quality audit, deduplication check, and filter for populated_features between 0 and 50 on these feature availability rows I have for group-a and group-b across October 2026?","exampleUseCases":[{"title":"Audit ML feature store data quality","prompt":"I have up to 200 rows of feature availability records with row IDs, dataset groups, dates, and populated vs expected feature counts — can you run a record quality audit plus deduplicate exact rows and filter populated_features between 5 and 100?"},{"title":"Deduplicate feature availability exports","prompt":"My feature availability export for dataset groups 'train' and 'test' has some suspected duplicate rows — can you run exact row deduplication along with a quality audit and a range filter on expected_features from 1 to 500?"},{"title":"Filter and validate feature coverage metrics","prompt":"Can you check these feature availability records for group-a — I want a quality audit, dedup check, and only keep rows where populated_features is between 10 and 200?"}],"resultDescription":"Returns three independent analytical reports computed locally from the supplied rows: (1) a record quality audit summarizing data completeness and anomalies across populated_features and expected_features, (2) an exact row deduplication report identifying and removing duplicate records, and (3) a numeric interval filter report returning only rows where the selected field (populated_features or expected_features) falls within the specified minimum–maximum range. All reports are derived from the input data only — no external lookups are performed.","failureModes":["Rows array empty or missing — minimum 1 row required","More than 200 rows submitted — batch size limit exceeded","Invalid date format (must be YYYY-MM-DD)","row_id missing or empty string — required field","Numeric values for populated_features or expected_features out of allowed range (±1 trillion)","minimum greater than maximum for interval filter — may return empty filter results","field enum value not recognized — must be 'populated_features' or 'expected_features'","Payment of 0.01 USDC not provided or rejected"],"whenToPreferThis":"Choose this endpoint when you have up to 200 feature availability records and need all three of: record quality auditing, exact duplicate detection, and numeric range filtering — in a single cost-efficient call ($0.01 USDC for all three reports). Ideal for ML/data engineering pipelines that need lightweight, self-contained analytics without external data lookups, predictions, or side effects. Not suitable for large datasets exceeding 200 rows, live data enrichment, or probabilistic deduplication.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T12:45:26.391Z","isFirstParty":false,"canonicalSlug":"feature-availability-analytics-quality-audit-deduplication-interval-9c194c48"}