Convex Performance Patterns
Helps with performance optimization, patterns as part of agent workflows workflows.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add convex-performance-patterns npx -- -y @trustedskills/convex-performance-patterns
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"convex-performance-patterns": {
"command": "npx",
"args": [
"-y",
"@trustedskills/convex-performance-patterns"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
This skill applies performance optimization patterns specifically designed for Convex, a backend-as-a-service platform. It helps AI agents generate code that minimizes database queries and improves runtime efficiency within Convex applications.
When to use it
- Optimizing data fetching logic in Convex functions to reduce latency.
- Refactoring inefficient query structures before deployment to production environments.
- Implementing caching strategies or indexing solutions for high-traffic Convex schemas.
- Improving the scalability of real-time subscriptions and mutations in Convex projects.
Key capabilities
- Applies proven performance patterns tailored for the Convex architecture.
- Generates optimized code snippets to enhance backend efficiency.
- Focuses on reducing unnecessary database operations and improving query speed.
Example prompts
- "Refactor this Convex function to use better performance patterns for fetching user data."
- "How can I optimize my real-time subscription logic using convex-performance-patterns?"
- "Generate a Convex mutation that follows best practices for minimizing database writes."
Tips & gotchas
Ensure your project is already initialized with Convex before applying these patterns, as they rely on specific platform features. While this skill optimizes code structure, it does not replace the need to test performance metrics in your actual production environment.
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