schemafit 0.2.0

Provider-aware structured-output / JSON-Schema CI linter — fail CI before your schema 400s on OpenAI, Anthropic, or Gemini

schemafit

Provider-aware structured-output / JSON-Schema CI linter. Catch the schema incompatibilities that make one provider 400 while another succeeds — before they hit production, as a fast, offline CI check.

A JSON Schema / tool definition / response_format that works on OpenAI can 400 on Anthropic or Gemini (and vice-versa): nested oneOf, a missing additionalProperties: false, a default in a property, Anthropic-rejected validation keywords (minLength, format, pattern, …), Gemini's lack of anyOf/dict support. The API tells you it failed but not which constraint violated it, so teams hand-port schemas and debug by trial-and-error at runtime.

schemafit encodes each provider's documented constraint surface as a versioned, declarative rule pack and lints your schema statically — pointing at the exact JSON-Pointer path, the keyword, and why — with a non-zero exit code so CI fails the PR instead of prod.

Every rule is grounded in a real, cited provider issue (see schemafit/rules/). It is not a runtime client: it makes no model calls, needs no API key, and has zero runtime dependencies.

Why this and not Instructor / BAML / LiteLLM / Vercel AI SDK?

Those are excellent runtime clients — they normalize, repair, or constrain a schema at call-time. schemafit fills the gap they leave: a static, pre-ship CI lint that fails the build before the schema ever reaches a provider, over the raw schemas you already ship, with no DSL or codegen buy-in.

Install

# From source (works today):
pip install "git+https://github.com/OrionArchitekton/schemafit"
# or build and run the container:
docker build -t schemafit . && docker run --rm schemafit demo

Once the first release is tagged (v0.1.0), pip install schemafit (PyPI) and docker run --rm ghcr.io/orionarchitekton/schemafit demo (GHCR) become available — both are published by the release workflow on a v* tag (PyPI via Trusted Publishing; image to GHCR).

Usage

# Lint one schema against several providers (exit 1 if any error):
schemafit lint my-schema.json --provider openai,anthropic,gemini

# Machine-readable output for CI annotations:
schemafit lint my-schema.json --provider anthropic --format json

# SARIF 2.1.0 for GitHub code-scanning / the Security tab:
schemafit lint my-schema.json --provider openai,anthropic --format sarif > schemafit.sarif

# Confirm against the live provider (opt-in; MOCK unless a key is in the env):
schemafit lint my-schema.json --provider openai --live-verify

# Also fail on warnings (e.g. Gemini $ref recursion risk):
schemafit lint my-schema.json --provider gemini --strict

# Emit a best-effort provider-valid variant (lossy transforms are flagged):
schemafit repair my-schema.json --provider anthropic --out fixed.json

# List supported providers / run a hermetic end-to-end proof:
schemafit providers
schemafit demo

Example:

$ schemafit lint order.json --provider anthropic
[anthropic] FAIL — 2 error(s), 0 warning(s)
  ERROR   #/properties/sku/pattern  (anthropic-no-pattern)
          Anthropic rejects the 'pattern' validation keyword (400 Bad Request).
          ref: https://github.com/vercel/ai/issues/13355
  ERROR   #/properties/qty/minimum  (anthropic-no-minimum)
          Anthropic rejects the 'minimum' validation keyword (400 Bad Request).

Use in CI

GitHub Actions (this repo ships a composite action):

- uses: OrionArchitekton/schemafit@v0.1.0
  with:
    schema: schemas/tool.json
    providers: openai,anthropic,gemini

Or directly / as a pre-commit hook (.pre-commit-hooks.yaml is included):

- repo: https://github.com/OrionArchitekton/schemafit
  rev: v0.1.0
  hooks:
    - id: schemafit
      args: ["--provider", "openai,anthropic,gemini"]
      files: '^schemas/.*\.json$'   # scope to YOUR LLM schemas, not every .json

Scope the hook with files: to the directory holding your LLM schemas — the default types: [json] would otherwise lint every JSON file in the repo (package.json, tsconfig.json, lockfiles), which are not LLM schemas.

GitHub code-scanning (SARIF)

--format sarif emits SARIF 2.1.0 so lint findings show up as annotations in the Security → Code scanning tab, with the exact JSON-Pointer path, the rule id, and the primary-source helpUri. SARIF is written to stdout regardless of the exit code, so code-scanning still ingests the artifact even when the gate fails (a clean schema produces a valid run with an empty results array, which clears stale alerts):

- run: schemafit lint schemas/*.json --provider openai,anthropic,gemini --format sarif > schemafit.sarif
  continue-on-error: true            # let code-scanning ingest the report
- uses: github/codeql-action/upload-sarif@v3
  with:
    sarif_file: schemafit.sarif

Live verification (--live-verify, opt-in)

--live-verify turns "the docs forbid this" into "the provider actually accepted/rejected it" by sending a minimal structured-output probe to each provider and failing closed on a rejection. It is opt-in and key-gated:

• Default = MOCK — with no provider key in the environment it uses a deterministic, network-free client modeled on the static rule pack, so CI and the Docker image run it with no key and no network.
• Real call — only when the provider's key (OPENAI_API_KEY, ANTHROPIC_API_KEY, GEMINI_API_KEY) is present in the environment. Real calls use the standard library (no new dependency); the [live] extra is reserved for optional provider SDKs.
• Tri-state — confirmed_by_provider is true (accepted), false (rejected → exit 1), or null (abstained: no key / rate-limited / network error). Abstaining is not a rejection and never fails CI.

Never commit an API key. The real path reads keys only from the environment and never echoes their value. Leave --live-verify out of default CI.

Supported providers (v0.2)

Provider	Checks (grounded in)
openai	additionalProperties:false required; all properties required; no default; no oneOf in array items (openai-agents-python#474, claude-task-master#1522)
anthropic	13 rejected validation keywords on the strict structured-output surface: minLength/maxLength/pattern/format/minimum/maximum/exclusiveMinimum/exclusiveMaximum/minItems/maxItems/uniqueItems/minProperties/maxProperties (vercel/ai#13355, anthropic-sdk-python#1034). General Messages-API tool input_schema is more permissive — run this pack against schemas you send on the structured-output path.
gemini	Portability warnings (version-sensitive, non-failing by default): anyOf (rejected by ≤2.0 / old SDKs, supported by 2.5), oneOf, open dict (additionalProperties schema), $ref recursion. Gemini's schema support changed fast (anyOf Jan 2026, additionalProperties Nov 2025), so these warn — use --strict to gate on them. (python-genai#460, docs)

Exit codes

code	meaning
0	no errors (warnings allowed unless --strict)
1	at least one error (CI fail)
2	bad input (unreadable / invalid JSON)

Scope and roadmap

In scope now: the lint + repair core, three provider rule packs, human/JSON and SARIF 2.1.0 reporters, an opt-in --live-verify confirmation mode, Docker image, GitHub Action, pre-commit hook.

Shipped in v0.2: SARIF output for GitHub code-scanning; the --live-verify opt-in live-confirmation mode (MOCK by default, key-gated real calls, fail-closed).

Deferred (v0.3+): more provider rule packs (Mistral, Cohere, Bedrock, Vertex); automatic rule-pack drift detection (pairs with --live-verify over the live provider); a pydantic source-model auto-fix mode; and an npm/ajv port plus a Zod source-model for the JS/TS ecosystem.

License

MIT © 2026 Dan Mercede