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Made for workers navigating tech upheaval.

Prompt Linter

Prompting is the new scripting — and like any script, prompts have lintable defects. Paste yours and get a scored checklist covering format specification, examples, delimiters, constraints, and vague wording, with a concrete fix for each miss.

Heuristic checks based on widely-shared prompting practice — a high score doesn't guarantee a good result, but fixing warnings usually pays. Runs entirely in your browser; your prompt is never uploaded.

How to Lint Your AI Prompts

Score a prompt against prompting best practices and fix what's missing before you send it.

  1. 1
    Paste your promptDrop in the prompt you're about to send to ChatGPT, Claude, Gemini, or any model. It never leaves your browser.
  2. 2
    Read the scoreYou get a 0-100 score from nine deterministic checks — length, output format, examples, delimiters, constraints, vague wording, and more.
  3. 3
    Fix the warningsEvery failed check comes with a concrete fix. Format specification and worked examples are usually the highest-payoff repairs.
  4. 4
    Re-check and sendThe score updates live as you edit. Prompts that pass most checks produce noticeably more consistent output.

Frequently Asked Questions

No — these are heuristics, not magic. But the checks encode widely-shared prompting practice, and fixing warnings (especially missing output format and missing examples) reliably improves consistency.

When you paste a document or code into a prompt, the model has to guess where your instructions end and the material begins. Wrapping pasted content in ``` fences or XML-style tags removes that ambiguity — and it's also your first defense against prompt injection from the pasted content.

No. The linter runs entirely client-side in your browser. Nothing you paste is transmitted, logged, or stored — safe for prompts containing internal context.

Yes — they're model-agnostic. Explicit format, examples, delimiters, single-task focus, and stated constraints improve results on GPT, Claude, Gemini, and local models alike.

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