Database query plan review for agent changes

Database query plan review helps validate whether coding-agent SQL changes improve performance under realistic conditions, since unit tests may miss costly shifts in join order, row estimates, index usage, or sorting. Effective reviews establish a clear baseline using the exact query, parameter patterns, schema and PostgreSQL versions, representative statistics, and a specific performance objective, while documenting whether evidence comes from production telemetry, staging, or synthetic data. Reviewers should compare estimated plans with measured execution carefully, using EXPLAIN for non-executing analysis and EXPLAIN ANALYZE only in isolated environments, with repeated controlled runs to account for cache effects and variability. Estimation errors may reveal outdated or unrepresentative statistics rather than a query defect, so agents should report uncertainty instead of overstating fixes. Proposed indexes and rewrites should also be assessed for write, storage, maintenance, locking, ordering, migration, and transaction implications, while pull requests remain narrowly focused on a measured regression. Controlled tools such as Factory’s Droid Exec and automated code review can support this process, provided credentials are protected and plan comparisons, integration tests, dataset characteristics, commands, results, and remaining variance are clearly recorded for database reviewers.

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