Output parser code generator
LLMs are unreliable at returning clean structured output. Even when you ask for JSON, you may get a markdown fence around it, a “Sure, here’s the data:” preamble, or a trailing explanation. This tool generates a small, dependency-free parsing function — in JavaScript or Python — that strips that wrapping, parses the payload for the format you expect, validates the basic shape, and fails in the way you choose. Pick your format, language, and error style, then copy the code.
How it works
You tell the generator what your prompt asks the model to produce: a JSON object
or array, a CSV table with a header row, key-value lines, or JSON wrapped in a
fenced code block. It emits a function that first isolates the relevant slice of
the response (for example, extracting the contents of a ```json block
or trimming preamble), then parses it with the language’s native tools, and
finally runs a lightweight shape check. The error-handling style you pick decides
whether the function throws or returns a structured error result, so it drops
cleanly into either a try/catch flow or a branch on the return value.
Tips and notes
- Match the parser to the prompt. If your prompt says “return only valid JSON,” generate the JSON parser; if it returns a markdown block, use the fenced variant so the fences get stripped.
- Keep validation honest. The generated shape check is intentionally minimal — add field-level type or range checks for production data.
- Return-error mode for pipelines. When parsing many responses in a loop, return-error mode avoids try/catch noise and lets you collect failures.
- No dependencies. The output uses only the standard library so you can paste it anywhere without an install step.