✅ Schema Validator
Validate data structures against schemas with comprehensive error reporting, multiple schema format support, and custom validation rules.
Validation Configuration
Schema Definition
Data to Validate
Custom Validation Rules (Optional)
🚀 Key Features
✅
Multi-Format Support
Support for JSON Schema, Borsh Schema, and custom validation rules
🔍
Detailed Errors
Comprehensive error reporting with exact location and suggestions
⚡
Batch Validation
Validate multiple data objects against schemas simultaneously
🛠️
Custom Rules
Create and apply custom validation rules for specific use cases
📋 Supported Schema Types
JSON Schema
- • Draft 7 and Draft 2019-09 support
- • Type validation (string, number, object, array)
- • Format validation (email, date, uri, etc.)
- • Custom keywords and validators
- • Conditional schemas (if/then/else)
- • Reference resolution ($ref)
Borsh Schema
- • Struct and enum validation
- • Primitive type checking
- • Array and vector validation
- • Option and nullable types
- • Custom serialization rules
- • Anchor IDL compatibility
Custom Schemas
- • Program-specific validation rules
- • Account data structure validation
- • Instruction parameter checking
- • Cross-field validation
- • Business logic constraints
- • Multi-step validation workflows
📖 Usage Examples
Validation Workflows
- 1. Choose schema type (JSON Schema, Borsh, Custom)
- 2. Input or upload your schema definition
- 3. Provide data to validate (JSON, binary, etc.)
- 4. Run validation and review detailed results
- 5. Export validation report for documentation
Best Practices
- • Start with built-in schema templates
- • Test validation with sample data first
- • Use batch validation for large datasets
- • Implement progressive validation strategies
- • Document custom validation rules clearly