Convex Performance Patterns

Name: Convex Performance Patterns
Author: fluid-tools

Checked

fluid-tools·vlatest·backend·MIT

Helps with performance optimization, patterns as part of agent workflows workflows.

Repository

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terminal

$ npx skills add op0ai/claude-skills --skill convex-performance-patterns -a claude-code

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Publisher

fluid-tools

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Live repository

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Automated safety checks

scanned 29 Sept 2026

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

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Commit: 4d09914bf5
Manifest: skills/convex-performance-patterns/SKILL.md
Scanned: 3 files, 1,781 lines
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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.