Analyze Ecto queries to detect N+1s and recommend preloads and indexing.
npx skills add https://github.com/layeddie/ai-rules --skill ecto-query-analysis
Please help me install this Agent Skill. Skill: ecto-query-analysis Source: https://github.com/layeddie/ai-rules/tree/main/skills/ecto-query-analysis Command: npx skills add https://github.com/layeddie/ai-rules --skill ecto-query-analysis
This skill helps Elixir developers detect and fix inefficient Ecto queries, reducing N+1 problems, missing preloads, and slow database access.
Run a basic analysis against your Ecto queries to surface common performance issues and recommended fixes.
High-intent search queries and answers about installing and using this skill.
You can optimize Ecto queries by analyzing query patterns across your data access layers to detect slow performance and excessive database load, then applying recommended preloads and indexing strategies to improve runtime efficiency.
Analyzing slow Ecto queries to reduce database load involves evaluating query patterns and schema design to detect missing preloads, then recommending indexing strategies and query optimizations for better performance.
Preloads in Ecto are needed when accessing associations within loops causes N+1 query problems, and applying selective preloading optimizes data retrieval to prevent excessive database load during runtime.
You can apply this query analysis to performance tuning across Elixir apps using Ecto, specifically targeting controllers, contexts, and data access layers to improve runtime efficiency and schema design.
Missing indexes in Ecto schema design are identified by analyzing query patterns that cause slow performance or excessive database load, allowing the recommendation of indexing strategies to optimize data retrieval.
Ecto query optimization focuses on detecting N+1 problems and recommending preloads or indexing strategies, but complex data access patterns with heavy schema design may require manual performance tuning beyond automated analysis.
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