Step 1
Import
Paste JSON, upload a sample file, or fetch an API response. schema-probe analyzes structure, detects nested objects, arrays, and optional fields automatically.
App by idyllicabundantpika1
AI Schema Probe Generator: Validate Data Online
Use schema-probe to generate, inspect, and validate JSON Schema with AI. Detect errors fast, improve data quality, and export clean schema online.
Prompt Text
Run the app to see your first output
How to use schema-probe
Generate and validate schemas in minutes
Learn how to create a JSON Schema from real data, validate new payloads against it, and export a clean schema for APIs, pipelines, and documentation—using schema-probe’s AI workflow.
Step 2
Validate
Run AI-assisted checks to find type conflicts, missing required fields, and unexpected properties. Tune constraints like enums, formats, and minimum/maximum values.
Step 3
Export
Download the generated JSON Schema for tooling and CI. Re-run validation on new payloads to keep contracts stable as data evolves.
Features
Schema generation and validation, streamlined
schema-probe turns example data into a usable JSON Schema with AI, then validates incoming payloads to catch issues early. Inspect types, required fields, and constraints in one place, and iterate quickly as models change. Export standards-friendly schemas to support API contracts, ETL pipelines, testing, and documentation.
AI-powered schema inference
Generate JSON Schema from sample payloads with smart detection of types, nested structures, arrays, and optional fields. Reduce manual mapping and get a solid baseline schema fast.
Fast validation and debugging
Validate data against your schema and surface clear, actionable errors for mismatched types, missing keys, and invalid formats. Iterate quickly to keep integrations stable and predictable.
Export-ready, standards friendly
Export clean JSON Schema for use in API tooling, CI checks, and data pipelines. Keep contracts consistent across environments and reduce downstream data quality surprises.
About
What is schema-probe?
schema-probe is an AI-powered schema generator and validator for JSON Schema and structured data. Paste a sample payload or point to an API response to infer fields, types, and constraints, then flag mismatches, missing properties, and formatting issues. Get clean, export-ready schemas that improve data quality and reduce integration bugs across pipelines and services.
Why choose schema-probe?
schema-probe combines AI schema inference with practical validation to keep structured data consistent. It reduces manual schema work, surfaces clear errors quickly, and produces export-ready JSON Schema for tooling, CI, and documentation workflows.
Getting started
Paste a sample JSON payload, let schema-probe infer the schema, then validate new data instantly. Refine constraints and export the JSON Schema to use in your pipeline or API checks.
Use cases
Who is schema-probe for?
Discover how different creators use this app in their workflow.
API contract validation
Infer schemas from real responses, validate requests and responses, and keep API contracts consistent to reduce breaking changes and integration errors.
Data pipeline quality checks
Validate incoming events and batch files against JSON Schema to catch malformed records early and prevent downstream failures in ETL and analytics.
Schema documentation and sharing
Generate exportable schemas from examples, then share a single source of truth for field types, constraints, and required properties across teams.
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Frequently asked questions
Common questions about AI schema generation, JSON validation, and exporting schemas with schema-probe.
schema-probe generates JSON Schema from sample data and validates new payloads against it. It helps detect type mismatches, missing fields, and formatting issues so data contracts stay reliable.
Yes. Provide a representative JSON payload and schema-probe infers fields, data types, nested objects, and arrays. You can then refine requirements, constraints, and formats before exporting.
AI-assisted validation highlights inconsistencies like mixed types, unexpected properties, and missing required values. This speeds up debugging and helps you enforce consistent schemas across services and pipelines.
Yes. schema-probe detects nested structures, arrays of objects, and optional fields. It generates appropriate schema definitions so complex payloads can be validated accurately and consistently.
Absolutely. Use it to infer schemas from responses, validate requests and responses, and export JSON Schema for automated checks. It helps reduce regressions when endpoints evolve.
You can export a clean JSON Schema suitable for tooling, CI validation, and documentation workflows. This makes it easy to reuse the schema across environments and projects.
schema-probe suggests required fields based on observed data, then lets you adjust requirements explicitly. Fine-tune required lists and constraints to match your real contract and edge cases.
Yes. Validate training and inference inputs for consistent structure and types. This reduces silent data drift, prevents parsing errors, and improves reliability in machine learning pipelines.
Generate and validate schemas with AI
Create JSON Schema, validate payloads, and export clean contracts online with schema-probe in minutes.