{"uid":"cap_ucThYxQ3Tgb43FTLtVVqK","slug":"feature-availability-record-quality-audit-numeric-distribution-e33e0a74","name":"Feature Availability — Record Quality Audit + Numeric Distribution","description":"Feature availability — Record quality audit + Numeric distribution: Record quality audit + Numeric distribution 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-10-004?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"}}},"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_RnFVLkYl58Zb7LlzK0Q02","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 (record quality audit and numeric distribution summary) on up to 200 feature availability records containing populated_features and expected_features fields.","exampleAgentPrompt":"Can you run a record quality audit and numeric distribution report on my feature availability data — here are 50 rows with row_id, dataset_group, date, populated_features, and expected_features — and analyze the populated_features field?","exampleUseCases":[{"title":"ML feature store completeness check","prompt":"I have 150 rows of feature availability records from my ML pipeline with populated_features and expected_features per date and dataset group — can you run the quality audit and distribution report on populated_features to see how complete my feature store is?"},{"title":"Daily dataset group comparison audit","prompt":"Run a record quality audit and numeric distribution on these 80 feature availability records across group-a and group-b for the past month, focusing on the expected_features field so I can see how our target feature counts are distributed."},{"title":"Data pipeline health monitoring","prompt":"Here are 200 rows of feature availability records from our data pipeline — each has a row_id, date, dataset_group, populated_features, and expected_features. Run the quality audit and distribution summary on populated_features so I can spot any anomalies before our weekly review."}],"resultDescription":"Returns two independent analytical reports: (1) a record quality audit flagging issues such as null values, out-of-range values, or malformed entries across the supplied rows, and (2) a numeric distribution summary including quantiles, min, max, mean, and spread statistics for the selected field (populated_features or expected_features), covering up to 200 rows processed entirely with local analytical engines.","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, date, populated_features, expected_features) causes rejection","Malformed date strings not matching YYYY-MM-DD pattern fail schema validation","Numeric values outside ±1,000,000,000,000 are rejected","Empty rows array is not accepted (minItems: 1)","Invalid field enum value other than 'populated_features' or 'expected_features' causes error"],"whenToPreferThis":"Choose this endpoint when you need to validate and understand the numeric distribution of feature availability data (populated vs expected features) for up to 200 rows in a single low-cost call. It is ideal for data quality pipelines, ML feature store audits, and dataset completeness checks where you want both a quality audit and a distribution summary together without any external lookups or live data dependencies. Prefer it over general-purpose analytics when your data fits the specific feature availability schema (populated_features, expected_features, dataset_group, date).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:43.512Z","isFirstParty":false,"canonicalSlug":"feature-availability-record-quality-audit-numeric-distribution-e33e0a74"}