JSON Schema Validator
This tool validates a JSON instance against a JSON Schema and reports precise, human-readable errors when the data does not conform. It helps you confirm that incoming or generated JSON matches an expected structure, types, and constraints before the data is used elsewhere.
JSON Schema is commonly used to define API contracts, validate configuration files, and enforce data quality at system boundaries. By validating early, you can catch breaking changes and malformed data before they cause downstream failures.
How JSON Schema Validation Works
Validation compares a JSON instance against a schema that describes allowed properties, required fields, data types, and additional constraints such as ranges or string patterns. Each rule is evaluated independently, and violations are collected and reported together.
The validator supports multiple JSON Schema drafts. When auto-detection is enabled, the tool inspects the schema to determine the most appropriate draft and applies the matching validation rules.
- Only validation is performed; no data is modified
- Draft-specific behavior follows the selected schema version
Inputs and Options Explained
The inputs reflect the two parts of schema validation: the rules (schema) and the data being checked (instance).
- JSON Schema — The schema definition that describes valid structure and constraints.
- JSON Instance — The data to validate against the schema.
- Schema draft — Auto-detects or manually selects the JSON Schema draft to use.
- Fail on additional properties — Treats undeclared object properties as validation errors.
- Strict tuple validation — Enforces exact array shapes when tuple validation is used.
Examples and Edge Cases
A JSON instance may be syntactically valid yet fail schema validation due to missing required properties or incorrect data types. These errors are reported with clear paths pointing to the exact location in the data.
When strict options are enabled, schemas that previously passed may start failing if the instance includes extra fields or arrays with unexpected lengths. This is intentional and helps enforce tighter contracts.
Who Should Use This Tool
This tool is useful wherever JSON is exchanged between systems or validated against a formal contract.
- Backend developers enforcing API request and response shapes
- Frontend developers validating configuration files
- QA engineers testing schema compliance
- Anyone learning or debugging JSON Schema rules
Related Concepts
JSON Schema validation is often part of a larger data-quality workflow.
- Schema evolution — Managing changes to data contracts over time.
- Strict vs permissive validation — Deciding how tolerant systems should be to extra or missing fields.
- Draft compatibility — Differences in behavior between schema versions.
If your instance JSON needs cleanup or inspection before validation, formatting it with the JSON Formatter can make errors easier to spot. For generating test data that matches a schema, converting tabular inputs using the CSV to JSON Converter can be helpful.