{"uid":"cap_v1eKV3Y2CfsP1-RtcznE1","slug":"feature-availability-record-quality-audit-numeric-interval-filter-799ae210","name":"Feature Availability — Record Quality Audit + Numeric Interval Filter","description":"Feature availability — Record quality audit + Numeric interval filter: Record quality audit + Numeric interval filter for supplied feature availability records (populated_features, expected_features). 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-10-008?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_yQ5zyyFvCrhRgFNzg27yl","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 feature availability records: a record quality audit and a numeric interval filter for populated_features or expected_features fields, covering up to 200 rows.","exampleAgentPrompt":"Can you run a record quality audit and numeric interval filter on my feature availability data — I have rows with row_id, dataset_group, date, populated_features, and expected_features, and I want to filter on the populated_features field between 0 and 100, up to 200 rows?","exampleUseCases":[{"title":"ML feature store data quality check","prompt":"I need to audit the quality of my feature availability records and flag any rows where populated_features falls outside 0 to 500 — here are my rows with row_id, dataset_group, date, populated_features, and expected_features. Run both the quality audit and the interval filter for me."},{"title":"Expected vs populated feature gap analysis","prompt":"Can you check my feature availability dataset for quality issues and filter the expected_features field to only show rows between 1 and 50? I have about 150 rows with date, row_id, dataset_group, populated_features, and expected_features."},{"title":"Dataset pipeline completeness validation","prompt":"I'm validating a pipeline output — please run a record quality audit and a numeric interval filter on these feature availability rows, filtering populated_features between 10 and 1000, and flag any records that look problematic."}],"resultDescription":"Returns two independent analytical reports: (1) a record quality audit highlighting data issues in the supplied feature availability rows, and (2) a numeric interval filter report showing which rows fall within the specified minimum/maximum range for the chosen field (populated_features or expected_features). Results are based entirely on the supplied data with no external lookups.","failureModes":["Fewer than 1 row submitted — request rejected","More than 200 rows submitted — exceeds row limit","Missing required fields (row_id, date, populated_features, expected_features) — validation error","Date field not in YYYY-MM-DD format — schema rejection","Minimum value greater than maximum value — ambiguous interval","Null values in numeric fields may affect interval filter results"],"whenToPreferThis":"Choose this endpoint when you need two simultaneous analytical passes on feature availability data — a quality audit and a numeric interval filter — within a single low-cost ($0.01 USDC) call, without requiring any external lookups or live data sources. Ideal for batch data pipeline validation, ML feature store QA, or dataset completeness checks where the data is already available locally.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:37.474Z","isFirstParty":false,"canonicalSlug":"feature-availability-record-quality-audit-numeric-interval-filter-799ae210"}