Error Message Set — Developer Tool

Variables to fill in: {{flow_context}}{{product_voice}}{{constraints}}

You are a UX writer who makes interfaces feel effortless through words users barely notice. I need your help in the context of a technical product whose users live in code and hate hand-holding.

TASK: Write error messages that help instead of alarm.

DELIVERABLE: Produce rewritten error copy for the scenarios given: what happened + what to do in each, tone calibrated to severity, with the generic-error fallback and the never-say list.

PROCESS:
1. Review the inputs below. If anything critical is missing or ambiguous, ask me up to three clarifying questions before producing the deliverable.
2. Establish where the user is, what they're trying to do, and what they're worried about at this exact moment from the inputs.
3. Write for the interface: front-load the key word, match the platform's conventions, respect the space constraints.
4. Draft in volume, then converge: multiple options with the trade-off each makes.
5. Produce the deliverable in a clean, skimmable format I can use directly.

QUALITY BAR:
- Clear beats clever everywhere except where delight is free.
- Consistent terminology — the same thing is never called two names.
- Error and edge copy tells users what happened and what to do, never blames them.

INPUTS:
- The screen/flow, what the user is doing, and their likely state of mind: {{flow_context}}
- The product's voice and any terminology rules: {{product_voice}}
- Space limits, platform, and localization considerations: {{constraints}}

Run this prompt on a real model without leaving the page. Every run is saved to your history for this prompt.

How to use

1. 1Fill in the {{flow_context}}, {{product_voice}}, {{constraints}} variables with your real details — specifics in, specifics out.
2. 2Paste the prompt into ChatGPT, Claude, Gemini, or any capable model.
3. 3Answer the clarifying questions it asks; that step is what makes the output fit your situation.
4. 4Iterate on the deliverable: ask for alternatives, tighter versions, or a different angle on any section.

Pro tips

• If the output feels generic, add more concrete detail to the inputs — names, numbers, and constraints sharpen everything.
• Works well in a thread: keep the conversation going to refine rewritten error copy for the scenarios given.