{"uid":"cap_mzJxZ1N3nTexnDeoQilLp","slug":"feature-availability-analytics-quality-audit-deduplication-grouped-c610579d","name":"Feature Availability Analytics — Quality Audit, Deduplication & Grouped Summary","description":"Feature availability — Record quality audit + Exact row deduplication + Grouped numeric summary: Record quality audit + Exact row deduplication + Grouped numeric summary 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-10-211?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_OdBABtMJDmNCYIIHsvbZl","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: a record quality audit, exact row deduplication, and a grouped numeric summary of populated_features or expected_features values.","exampleAgentPrompt":"Can you run a quality audit, exact deduplication check, and grouped numeric summary on these feature availability records — up to 200 rows with row_id, dataset_group, date, populated_features, and expected_features — and focus the summary on the populated_features field?","exampleUseCases":[{"title":"Feature completeness audit before ML pipeline","prompt":"I have a batch of feature availability records with populated_features and expected_features columns. Can you run a record quality audit plus exact row deduplication and then give me a grouped numeric summary by dataset_group? I want to make sure the data is clean before feeding it into my ML pipeline. Focus the summary on populated_features."},{"title":"Detecting duplicate feature tracking entries","prompt":"We're getting suspect duplicate entries in our feature tracking table. Can you take these rows — each has a row_id, dataset_group, date, populated_features, and expected_features — and run exact deduplication along with the quality audit and a grouped summary on expected_features to see what's going on?"},{"title":"Summarizing feature fill rates by dataset group","prompt":"I need a quick grouped numeric summary of how populated_features varies across my dataset groups, plus a quality audit to flag any bad records and a dedup check. Here are about 150 feature availability rows with dates ranging through October 2026 — can you process them?"}],"resultDescription":"Three independent analytical reports: (1) a record quality audit flagging nulls, format errors, and data issues; (2) an exact row deduplication report identifying and removing duplicate records; and (3) a grouped numeric summary (e.g. sum, mean, count) of the selected field (populated_features or expected_features) broken down by dataset_group and/or date. All computed locally with no external calls.","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, date, populated_features, expected_features) causes row-level rejection","Invalid date format (non-YYYY-MM-DD) triggers pattern validation failure","Numeric values outside ±1,000,000,000,000 boundary are rejected","Empty rows array returns an error","Invalid field enum value (not populated_features or expected_features) causes schema rejection"],"whenToPreferThis":"Choose this endpoint when you need all three of quality audit, exact deduplication, and grouped numeric summarization on feature availability data in a single $0.01 call (up to 200 rows), without requiring any external data lookups, live APIs, or prediction services. It is ideal for pre-processing feature store records, validating ML training data, or auditing feature tracking logs entirely offline.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T12:46:59.405Z","isFirstParty":false,"canonicalSlug":"feature-availability-analytics-quality-audit-deduplication-grouped-c610579d"}