SchemaFit
Lint JSON schemas for compatibility across major LLM providers to avoid runtime failures.
Open SourceCoding & Dev
Visit website Free to browse · updated 2026-06-29
What is SchemaFit?
SchemaFit addresses inconsistencies in how different LLM providers handle JSON schemas and tool definitions. By encoding each provider's documented constraints into versioned rule sets, the tool identifies problematic elements such as unsupported keywords or complex type unions. This allows developers to catch issues during the build phase rather than discovering them through trial and error after deployment. The utility includes dedicated commands for linting schemas against selected providers and generating corrected variants that preserve original intent. It operates without any network access or API credentials, making it suitable for integration into continuous integration pipelines where a failing check can block merges. Additional capabilities focus on maintainability through features like SARIF output for code scanning tools and optional verification steps that keep rule packs aligned with evolving provider specifications. This approach complements runtime libraries by enforcing schema validity at the source level.
Key features
Lints JSON schemas and tool definitions against OpenAI, Anthropic, Gemini, Mistral, and Cohere rule packs
Static offline analysis with zero runtime dependencies and no API calls
Reports exact violations using JSON-Pointer paths, keywords, and reasons
Auto-repair emits provider-valid schema variants while preserving intent
CI-enforceable with non-zero exit codes and optional SARIF output
Versioned declarative rule packs with automatic drift detection
CLI commands for lint, repair, listing providers, and hermetic demo runs
What you can use SchemaFit for
Pre-Production Schema Validation
Lint JSON schemas and tool definitions statically against OpenAI, Anthropic, Gemini, Mistral, and Cohere rule packs to identify violations such as unsupported keywords or type unions before runtime errors occur.
Automated Provider-Specific Repair
Generate best-effort valid schema variants for a chosen provider by rewriting or stripping incompatible keywords while preserving original intent.
CI Pipeline Enforcement
Fail builds on schema incompatibilities using non-zero exit codes, JSON-Pointer violation reports, and optional SARIF output for GitHub code scanning.
How to use SchemaFit
- 1Install via pip install schemafit
- 2Prepare your JSON schema or tool definition file
- 3Run schemafit lint with desired providers
- 4Review reported violations at exact JSON-Pointer locations
- 5Use schemafit repair to generate a provider-valid variant
- 6Add the lint command to your CI pipeline for enforcement
SchemaFit pricing
Pricing model: Open Source. Plan details are indicative — check the site for current prices.
Open Source (MIT)
Free
- Static & offline linting
- Zero runtime dependencies
- CI-enforceable
- PyPI install
- Supports OpenAI, Anthropic, Gemini, Mistral, Cohere
Editor's verdict
Pros
- +Fails builds in CI before schemas reach production APIs
- +Fully offline, auditable, and MIT-licensed with no external dependencies
- +Grounded rules citing real provider constraints
Cons
- –CLI-only interface with no GUI or IDE integration
- –Limited to the five listed providers
- –Repair is best-effort and may require manual review
Our take: SchemaFit is a solid coding & dev choice. It's valued for fails builds in ci before schemas reach production apis and fully offline, auditable, and mit-licensed with no external dependencies. The main trade-off is cli-only interface with no gui or ide integration. A good pick if you want capable AI without a high upfront cost.
Frequently asked questions
It supports OpenAI, Anthropic, Gemini, Mistral, and Cohere with versioned declarative rule packs encoding each provider's documented constraints.
Summary
SchemaFit is a solid coding & dev choice. It's valued for fails builds in ci before schemas reach production apis and fully offline, auditable, and mit-licensed with no external dependencies. The main trade-off is cli-only interface with no gui or ide integration. A good pick if you want capable AI without a high upfront cost.
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