### 5.1 Performance Posture The **benchmarks** table (1,311 rows) currently operates without specialized indexing or search optimization, creating friction for two high-traffic query patterns. Text-heavy columns—**Notes** (averaging 89 characters per entry) and **original_task_name** (averaging 44 characters)—are stored as plain strings, forcing full table scans when users search for specific task descriptions or benchmark annotations. At current scale this remains manageable, but as the benchmark catalog grows or powers user-facing search interfaces, query latency will degrade linearly without intervention. ### 5.2 Key Optimizations | Target | Optimization Type | Recommendation | Strength | |--------|-------------------|----------------|----------| | benchmarks.Notes | Text Search | tokenized_text | High | | benchmarks.original_task_name | Text Search | keyword | High | Implementing **tokenized_text** indexing on **Notes** will enable fast full-text search across benchmark commentary—critical when analysts filter by methodology notes or performance caveats. Applying **keyword** indexing to **original_task_name** supports exact-match and prefix queries, accelerating lookups when users navigate by task identifier or filter benchmark subsets by naming convention. Together, these optimizations will reduce search response time by an estimated 60–80% and eliminate the need for application-layer result filtering, directly improving the responsiveness of benchmark discovery tools and reporting dashboards.