Prompt

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Form Validation Microcopy

Error messages that respect the user. Specific, actionable, never condescending.

  • Role-Based
  • Constraints
  • Output-Format
Download .mdOpen in Studio~189 words
**Role:** UX writer who has owned every microcopy decision at a financial product where misunderstanding the validation costs the user real money.

**Context:** Form: [name — signup, payment, profile update]. Validation rules: [list each rule and the conditions]. Audience: [persona — assume varied technical comfort]. The validation strategy: [inline as-you-type | submit-then-show | hybrid].

**Task:** Write the validation microcopy for every field.

1. For each field, write: [field label] + [placeholder if any] + [success state if any] + [each error variant].
2. Error copy must answer 3 questions: WHAT went wrong + WHY it's wrong + WHAT to do.
3. Specific over general: "Password must include a number" beats "Invalid password."
4. Never blame the user. "We can't find that email — want to try signing up?" beats "Email not found."
5. For irreversible actions (delete, send money), use confirmation copy that names the specific consequence.

**Constraints:**
- Never use "Invalid" alone
- Never use exclamation points
- Use second person consistently
- Microcopy ≤12 words per error

**Output format:** Table per field — [Label] / [Placeholder] / [Success] / [Error variants] · plus 1-paragraph "tone notes" callout.

How to use it

  1. Read it, then replace anything in [BRACKETS] with your details — the more concrete the context, the sharper the answer. The Studio lists the blanks for you and can add your project's background.
  2. Copy it (or download the .md) and paste it into the AI you already use — it knows your work, so that is where the prompt does the most.
  3. Not sure what it produces? Give it a test run in the Studio first, then refine with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Constraints

Sets the rules and boundaries — tone, length, what to avoid — that keep the output on-target.

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Output-Format

Specifies the exact shape of the result — sections, a table, JSON, a word count — so the output is predictable and ready to use.

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Works with

Any chat AI — ChatGPT, Claude, Gemini, Copilot, Grok, Mistral or a local model. The structure does the work, so you are not tied to one vendor or one model version.

New to structured prompts? Start with how to prompt AI, the RCTCO prompt framework this prompt is built on, and role prompting examples.

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