data-validation

Validate input data against JSON Schema, Zod, or Pydantic schemas.

53|1|Updated Dec 18, 2025

Search Tags:#validation #schema #sanitization #zod #encoding #data-validation

Ready to run

npx skills add https://github.com/cosmix/claude-code-setup --skill data-validation

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: data-validation
Source: https://github.com/cosmix/claude-code-setup/tree/main/skills/data-validation
Command: npx skills add https://github.com/cosmix/claude-code-setup --skill data-validation

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Data validation patterns including schema validation, input sanitization, output encoding, and type coercion. Use when implementing form validation, API input validation, JSON Schema, Zod, Pydantic, sanitization, XSS prevention, or custom validators.

Core Features & Use Cases

Schema Validation: JSON Schema, Zod, or Pydantic-based validation with robust error handling.
Sanitization & Encoding: Clean inputs and prevent injection attacks.
Transform & Coerce: Type coercion and normalization for safe processing.

Quick Start

Choose a schema library (e.g., Zod) and validate a sample API payload against a defined schema.

Frequently Asked Questions about data-validation

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

FAQPage Schema

How do I validate API input data against a schema?▼

Validate API input by defining a schema using Zod, JSON Schema, or Pydantic, then check incoming payloads against it before processing. This prevents invalid or unsafe data from entering your system and provides structured error reporting for client feedback.

What's the best way to prevent XSS attacks in form submissions?▼

Sanitize and encode form inputs using validation and output encoding techniques to remove malicious scripts and unsafe content. Schema validation combined with sanitization blocks injection attacks while preserving legitimate user data.

Can I use Zod or Pydantic for type coercion and default values?▼

Yes. Both Zod and Pydantic support type coercion to convert input types, apply default values, and remove unknown properties while validating against your schema, ensuring consistent data transformation across your application.

How do I handle validation errors in a user-friendly way?▼

Schema validators like Zod and Pydantic generate comprehensive, structured error messages that map field paths to specific validation failures. Format and return these errors to clients so they understand exactly which fields failed and why.

When should I validate data on the backend versus the frontend?▼

Always validate on the backend as your security boundary, regardless of frontend validation. Backend validation prevents malicious or malformed data from entering your system; frontend validation improves user experience but cannot be trusted alone.

Does schema validation work with JSON, form data, and API payloads?▼

Yes. Schema validation applies across JSON payloads, form submissions, and API request bodies. A single schema library handles all formats, enabling consistent validation rules throughout your application.