What problem does it solve? Measuring whether a Cortex Analyst semantic view generates correct SQL is hard to do systematically. This Skill runs Snowflake's native Analyst Evaluations against a semantic view's own verified queries, producing an accuracy score, surfacing regressions, and validating before/after improvements. ## Core Features & Use Cases - Verified-Query-Based Evaluation: Uses the semantic view's own verified queries as ground truth with the sql_correctness metric, with no separate dataset required. - Automated Run Management: Generates the YAML evaluation config, uploads it to a stage via PUT, starts the run with EXECUTE_AI_EVALUATION, and polls status until completion. - Results Analysis: Retrieves per-query results with GET_ANALYST_AI_EVALUATION_DATA, computes accuracy summaries, and inspects generated SQL versus verified SQL for incorrect rows. - Use Case: After refining a semantic view's instructions, re-run the evaluation to confirm the accuracy score improved and check that no previously correct verified queries regressed. ## Quick Start Ask the assistant to evaluate your Cortex Analyst semantic view by providing its database, schema, and view name, then follow the guided steps to review verified queries and run the evaluation.