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convex-functions

Enforce input validation and predictable return shapes for Convex functions.

Updated Aug 27, 2026
Search Tags:#validation#queries#reliability#best-practices#mutations#actions#convex
One-click install
npx skills add https://github.com/lemessdavi/ia-prev --skill convex-functions-lemessdavi
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: convex-functions
Source: https://github.com/lemessdavi/ia-prev/tree/main/skills/convex-functions
Command: npx skills add https://github.com/lemessdavi/ia-prev --skill convex-functions-lemessdavi

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill provides a structured approach to implementing Convex functions by enforcing explicit input validation, separation of domain rules from transport concerns, and predictable return shapes to reduce runtime errors and improve maintainability.

Core Features & Use Cases

  • Explicit function types: supports query, mutation, and action patterns with clear intent.
  • Validation-first design: mandates input validation and defensive coding to prevent invalid state changes.
  • Separation of concerns: keeps domain rules isolated from transport or serialization logic.
  • Predictable outputs: standardizes return shapes for client usage and error handling.

Quick Start

Follow these guidelines to implement a Convex function with explicit input validation and predictable return shapes.

Frequently Asked Questions about convex-functions

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I validate inputs in Convex queries and mutations to prevent runtime errors?▼

Separate domain rules from transport code in Convex by isolating business logic from serialization concerns. This structured approach keeps domain rules isolated, reducing coupling and improving maintainability for query, mutation, and action patterns.

What is the best way to structure Convex actions to ensure predictable response shapes?▼

Standardize Convex actions by mandating predictable return shapes for client usage and error handling. This validation-first design provides consistent outputs, simplifying client-side consumption and error management across typical workflows.

How do I separate domain rules from transport code in Convex functions?▼

Separate domain rules from transport code in Convex by isolating business logic from serialization concerns. This structured approach keeps domain rules isolated, reducing coupling and improving maintainability for query, mutation, and action patterns.

Does this validation approach support idempotent patterns for Convex mutation retries?▼

Yes, this validation approach supports idempotent patterns for Convex mutation retries. It enforces robust validation and predictable return shapes, ensuring retried mutations do not produce duplicate side effects or invalid state changes.

Do I need explicit tests for critical branches when implementing Convex actions?▼

Yes, you need explicit tests for critical branches when implementing Convex actions. The validation-first design mandates clear tests to verify input validation, error handling, and predictable outputs across your function workflows.

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