Convex Helpers Patterns
Identifies recurring patterns in complex data using convex hull analysis to reveal underlying structures and relationships.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add convex-helpers-patterns npx -- -y @trustedskills/convex-helpers-patterns
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"convex-helpers-patterns": {
"command": "npx",
"args": [
"-y",
"@trustedskills/convex-helpers-patterns"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
This skill provides a collection of helper functions and patterns designed to streamline development workflows within the Convex framework. It enables AI agents to efficiently implement common architectural solutions, reducing boilerplate code and ensuring consistency across applications.
When to use it
- Accelerating the setup of new Convex projects by leveraging pre-built utility patterns.
- Standardizing data handling logic to maintain uniformity in backend services.
- Reducing development time when implementing recurring features that require specific Convex configurations.
- Ensuring best practices are followed during rapid prototyping or production builds.
Key capabilities
- Provides reusable helper functions tailored for the Convex ecosystem.
- Implements established design patterns to solve common backend challenges.
- Simplifies complex logic by abstracting repetitive tasks into manageable utilities.
Example prompts
- "Generate a new Convex function using the standard helpers from this pattern library."
- "Refactor this existing code block to utilize the recommended helper patterns for better maintainability."
- "Create a utility function that follows the established conventions found in the convex-helpers-patterns collection."
Tips & gotchas
Ensure your project is initialized with the Convex framework before attempting to use these specific helpers. While these patterns optimize common tasks, always verify they align with the latest version of the Convex documentation to avoid compatibility issues.
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