{"uid":"cap_W5sCwPxFFZJFNc0pFm22Q","slug":"feature-availability-base-100-series-keyed-dataset-comparison-c841b5e7","name":"Feature Availability — Base-100 Series + Keyed Dataset Comparison","description":"Feature availability — Base-100 series + Keyed dataset comparison: Base-100 series + Keyed dataset comparison 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 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a Base-100 indexed series and a keyed dataset comparison for supplied feature availability records (populated_features vs expected_features) across up to 200 rows.","exampleAgentPrompt":"I have two sets of feature availability records for groups 'train' and 'test' across October 2026 — can you run a Base-100 series and a keyed dataset comparison on populated_features for up to 50 rows to see how feature completeness trends and where the two datasets diverge?","exampleUseCases":[{"title":"ML pipeline feature completeness audit","prompt":"I have daily feature availability logs for my ML pipeline across two dataset groups, 'features_v1' and 'features_v2', for the past 30 days — run a Base-100 indexed trend and a keyed comparison on populated_features so I can see which group has better feature fill rates."},{"title":"Data warehouse completeness benchmarking","prompt":"Compare expected_features vs populated_features across my 'warehouse_prod' and 'warehouse_staging' dataset groups for Q3 2026 — I need a Base-100 series to spot trends and a keyed comparison to flag mismatches, up to 200 rows."},{"title":"Feature drift detection across experiment groups","prompt":"I'm running an A/B experiment and want to check if the control and treatment groups have similar feature availability — can you index populated_features to Base-100 and do a keyed dataset comparison across groups 'control' and 'treatment' for the last two weeks?"}],"resultDescription":"Returns two analytical reports: (1) a Base-100 normalized index series showing feature availability trends over time, and (2) a keyed dataset comparison identifying differences between the two supplied datasets, both computed from the user-supplied populated_features and expected_features values across up to 200 rows.","failureModes":["More than 200 rows submitted — request exceeds maxItems limit and will be rejected","Missing required fields (row_id, date, dataset_group) cause validation errors","Dates not matching YYYY-MM-DD pattern will fail schema validation","Null values in both populated_features and expected_features may produce incomplete analytics","Empty rows array (minItems:1 violated) returns an error"],"whenToPreferThis":"Choose this endpoint when you have pre-collected feature availability data (populated vs expected feature counts) and need both a Base-100 trend index and a keyed cross-dataset comparison in a single call, without requiring live data lookup or external enrichment. Ideal for data quality monitoring, ML pipeline audits, and dataset benchmarking workflows where local analytical computation on supplied data suffices.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-20T07:19:36.923Z","isFirstParty":false,"canonicalSlug":"feature-availability-base-100-series-keyed-dataset-comparison-c841b5e7"}