Confirm your tool schema actually triggers — with a real call
A function or tool schema that reads correctly can still misbehave: the model might not call it, might pick the wrong tool, or might produce arguments that miss a required field. The only way to know is to send a real request. This harness takes your tool schema and a test message, calls OpenAI or Anthropic directly with your own key, and shows exactly what the model did with your tool.
How it works
You paste a single tool definition as JSON — name, description, and a JSON Schema parameters object — plus a user message that should trigger it. The harness rewrites your definition into the shape each provider expects: OpenAI’s tools array with a type of function, or Anthropic’s tools array with an input_schema. It sends the request straight from your browser to the provider endpoint using your key, then inspects the response for a tool call. It reports the tool name the model chose, pretty-prints the argument JSON, validates that the arguments parse, and checks that the required top-level properties declared in your schema are present.
Tips and notes
Write a test message that a real user would actually send, not one that quotes the tool name — you are testing whether the description is clear enough for the model to choose the tool on its own. If the model ignores your tool, tighten the description and make the parameter names and descriptions unambiguous. Your key is used only for the direct provider request and is never stored; use a scoped test key. Real API calls cost a small amount per request, so this is a debugging tool rather than something to loop. Run it whenever you change a schema to catch regressions before they reach production.