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Is your prompt locked to one model?
Paste any prompt and get an instant portability score — every construct that would break or degrade when you switch providers, with the fix. No signup, nothing uploaded.
Paste a prompt to check it.
Heuristic checks — a human should confirm each. This mirrors the free Production Prompt Auditor prompt.
How the check works
- Paste a prompt you use in code (or click “Try a sample”).
- The linter scans for provider-specific constructs — JSON mode, tool schemas, XML tags, hard-coded model names, config leakage, special tokens.
- You get a portability score /100, each issue ranked by severity, and how to fix it.
- For a full rewrite + fallback chain, run the Production Prompt Auditor.
Why prompt portability matters
Most prompts are quietly welded to the model they were written for. When you switch — for cost, latency, availability, or a better model shipping next week — a locked-in prompt breaks or silently degrades. Portability is what lets you treat models as interchangeable. VernaOne goes one step further and makes the portable prompt a versioned endpoint with automatic fallback, so switching models is a config change, not a rewrite.
Make the fix permanent
Turn a portable prompt into a named, versioned endpoint that runs across every provider with automatic fallback and cost tracking.
Try VernaOne free →Frequently asked
How do I check if my prompt is locked to one LLM provider?
Paste it into the Prompt Portability Linter above. It scans for provider-specific constructs — OpenAI response_format/JSON mode, Anthropic-style XML tags, tool/function-call schemas, hard-coded model names, reasoning-effort assumptions, and special tokens — and returns a portability score out of 100 with the exact issues and fixes. Everything runs in your browser; the prompt is never uploaded.
What makes a prompt model-agnostic?
A model-agnostic prompt separates a clear system instruction from the user message, templatizes inputs as {{variables}}, states its output format as plain JSON (not a provider flag), and avoids single-vendor constructs like XML tags or tool schemas. Then the same prompt runs identically on OpenAI, Anthropic, Google, and others.
Is the linter accurate?
It uses conservative heuristics to surface likely lock-in signals for a human to confirm — fast and private, but not a substitute for testing across models. For a full rewrite and a recommended fallback chain, run the free Production Prompt Auditor prompt or use VernaOne.
Does my prompt get sent anywhere?
No. The linter runs entirely client-side in your browser. Nothing is uploaded, logged, or stored.