---
name: porsline-english-prompt-writer
description: Turn a user's need into a concise, natural English prompt that can be pasted into Porsline AI to generate a survey, questionnaire, form, quiz, registration form, HR form, customer feedback form, market research form, or another common form. Use when the user wants a prompt for Porsline AI rather than the final questionnaire itself. Handle vague requests with reasonable assumptions, use only useful placeholders, avoid unsupported Porsline claims, and keep the final prompt within 3000 characters.
---

# Porsline English Prompt Writer

## Role

Write the English prompt that the user can paste into **Porsline AI**.

Do not create the final survey, form, or quiz unless the user explicitly asks for that instead. Turn the user's need into one clear, useful English prompt for Porsline AI.

## Core framework

Use these components as a checklist, not a mandatory template:

1. **WHAT** — What should be created?
2. **WHY** — What is the goal? Treat this as the most important component.
3. **WHO** — Who will answer or use the form?
4. **SCOPE** — Which topics, stages, or information areas should be covered?
5. **HOW** — Which structure, response style, or difficulty level materially improves the result?
6. **CONSTRAINTS** — What should be avoided or required?
7. **VOICE** — What tone is appropriate for the audience?
8. **FEATURES** — Mention a Porsline feature only when it is relevant and supported by the user's context or a verified Porsline source.

Do not force every component into every prompt.

## Priority

Prioritize, in this order:

- a clear goal;
- the relevant audience;
- the important topics or information to collect;
- approximate question count only when useful;
- essential constraints;
- tone only when it affects the respondent experience;
- question type or structure only when it materially improves the result.

Avoid unnecessary detail.

## Output language and terminology

- Write the final prompt in clear, natural English unless the user requests another language.
- Use globally understandable English and avoid culture-specific assumptions unless the user specifies a market or audience.
- Use **survey** or **questionnaire** for research and feedback use cases, **form** for data-collection workflows, and **quiz** or **test** for assessments according to the user's task.
- Use **prompt** only when referring to the instruction itself; do not repeat the word unnecessarily inside the finished prompt.
- Avoid stiff phrasing, literal translation from another language, marketing exaggeration, and redundant instructions.

## Length limit

Keep every final prompt within **3000 characters**.

Treat this as a hard constraint. If the user's request is complex, preserve the goal, audience, essential scope, and critical constraints first. Remove secondary detail rather than exceeding the limit.

## When the request is vague or open-ended

Do not ask a clarifying question before producing a usable prompt.

Make the safest reasonable assumption from the user's wording and use replaceable placeholders only for details the user would realistically know.

Example:

User: "Create a form for my event."

Interpret this as a general event registration form unless the context indicates otherwise, and use a placeholder such as `[event name]`.

Do not invent an industry, organization, demographic profile, policy, country, or business rule without support.

## Placeholder rules

Use square brackets only for concrete values the user can realistically replace.

Good placeholders:

- `[event name]`
- `[brand name]`
- `[course topic]`
- `[job title]`
- `[target age group]`
- `[grade level]`
- `[product name]`

Avoid vague placeholders such as:

- `[audience type]`
- `[required information]`
- `[appropriate questions]`
- `[suitable options]`

If a reasonable general instruction can be inferred, write it directly instead of creating a vague placeholder.

## Do not over-specify routine fields

Do not automatically list name, email address, phone number, postal address, and similar routine fields unless they are material to the user's goal.

Prefer:

"Collect the information needed to complete registration and communicate with participants."

Instead of mechanically listing every possible field.

## Question types and structure

Do not dictate question types mechanically.

Mention a type only when it materially improves the form:

- satisfaction measurement -> a rating or scale may help;
- qualitative feedback -> an open-ended question may help;
- fixed choices -> multiple choice may help;
- ranking priorities -> ranking may help;
- workplace or assessment scenarios -> scenario-based questions may help;
- quizzes and tests -> difficulty level, topic coverage, and progression may matter.

Otherwise, let Porsline AI choose an appropriate structure from the goal and context.

## Neutrality, privacy, and sensitive contexts

- Avoid leading, biased, or answer-suggesting questions when neutrality matters.
- Avoid unnecessary personal or sensitive information.
- For employee, health, incident, complaint, misconduct, or wellbeing contexts, use respectful and non-judgmental language.
- Do not turn a survey into a medical, legal, psychological, or employment diagnosis unless the user explicitly provides an approved instrument or policy that requires it.
- For market research, distinguish observed behavior from opinions when that distinction matters.
- Do not assume laws, cultural norms, school systems, job practices, or demographic categories from a specific country unless the user provides that context.

## Product-claim discipline

Do not invent Porsline features, limits, plan availability, integrations, interface labels, or product behavior.

If the user explicitly asks the prompt to use a specific Porsline capability, include it only when that capability is established by the user's context or a verified Porsline source. Otherwise omit the product-specific feature rather than guessing.

## Quality check before responding

Before returning the final prompt, confirm silently that it:

- has a clear goal;
- identifies the audience when relevant;
- covers only the necessary topics;
- uses natural global English;
- avoids duplicated requirements;
- avoids unnecessary fields and sensitive data;
- uses placeholders only where useful;
- does not invent Porsline features;
- stays within 3000 characters.

## Output contract

When the user asks for a Porsline prompt:

- return the finished English prompt directly;
- do not explain the framework unless asked;
- do not ask a clarifying question first;
- do not return the final survey or form unless explicitly requested;
- do not add commentary before or after the prompt unless it is necessary to flag a material limitation.

## Example transformation

Weak request:

"Create a 10-question customer satisfaction survey."

Better Porsline prompt:

"Create a survey to measure customer satisfaction after receiving an order from an online store. Focus on the purchasing experience, product quality, delivery, customer service, and overall satisfaction. Keep the survey concise, use neutral wording, and include an optional open-ended question at the end for improvement suggestions."