Product

Prompt Builder

A six-step wizard that forces you to articulate what you actually want. Role, context, task, thinking pattern, output format, final instructions — the Live Preview updates as you go. Save the result to your library and reuse it everywhere.

Who it's for

Marketers

Reuse campaign briefs, email flows, and ad copy prompts across clients and channels — without rewriting them every time.

Founders

Turn one-off ChatGPT sessions into a repeatable library your team can run, share, and improve together.

Anyone who reuses prompts

If you copy-paste the same prompt more than twice, save it once with structure and deploy it everywhere.

Anatomy of a structured prompt

Before you open the wizard, feel the shape of a good prompt. Click a part to see why it is there and how it reads in the final XML.

Anatomy of a prompt

Click a part to see why it matters

<role>You are a senior backend engineer with 10+ years building distributed systems. You favor boring, battle-tested technology over novelty.</role><context>We are a 3-person SaaS startup pre-Series A. Our stack is Next.js + Supabase. We have 40k MAU and growing 15% month over month.</context><task>Review the attached Postgres schema for a multi-tenant billing table. Flag any design that will cause contention at 10x current volume.</task><thinking>Think step by step. First enumerate every table and index. Then identify hot rows. Then estimate lock contention under concurrent writes.</thinking><format>Return a markdown table with columns: concern, severity (low/med/high), affected tables, suggested fix. Keep each row to one sentence.</format><instructions>If a concern is speculative, mark it with a ⚠ and keep it to one row. Do not invent tables that are not in the schema.</instructions>

Why role assignment matters

Who is the AI speaking as? A role gives it a point of view — vocabulary, priorities, blind spots. "Act as an engineer" is too vague; "Act as a senior engineer who favors boring tech" sets a bar.

You never start from scratch

Each step ships with researched presets — 104 roles, 1,560 task suggestions, preset thinking patterns, and quick format options. The wizard asks the questions you would forget.

The six steps

Every saved prompt walks through the same six stages. You can go back at any point — the Live Preview reflects changes instantly.

Prompt Builder setup — Area cards, Category and Subcategory chips for choosing an ontology preset — Setup: pick an area → category → subcategory to get role and task presets. Subcategory is optional; skip to start blank.

Step 1·
Role Assignment
Req
Define expertise and perspective
Tell the AI who it is — expertise, seniority, specialization. "Senior React architect" gives fundamentally different answers than a generic "developer". Pick from 104 researched roles or write your own.
Step 2·
Context Setting
Establish background and situation
The AI starts with zero knowledge of your project. Write what it needs — what you are building, who it is for, constraints, decisions already made. Without context, the model falls back to a generic baseline.
Step 3·
Task Specification
Req
Define clear objectives
Tell the AI exactly what to produce. "Analyze X, then generate Y in format Z" works; "help me with X" does not. 1,560 task suggestions across subcategories are available as presets.
Step 4·
Thinking Steps
Step-by-step reasoning process
Guide the AI's reasoning before it answers. List the stages you would think through yourself — it skips every step you do not name. Chain-of-thought beats one-shot for anything non-trivial.
Step 5·
Response Format
Define structure and presentation
How should the answer look? Bullet points, tables, headers, word count. Without format rules you get walls of text. Quick-format chips cover the common cases.
Step 6·
Final Instructions
Req
Your last words before execution
Your final checklist. Priorities, tone, things the AI must never do. The instructions closest to the end are weighted most heavily — this catches what the earlier steps missed.

Prompt Builder format selector — Markdown, XML (Anthropic recommended), JSON cards with best-for tags — Output format lives upstream of the wizard. XML is recommended for Claude; Markdown for ChatGPT/Gemini; JSON for automation tools.

Variables and inputs

Variables let one prompt serve many situations. Wrap anything that changes per run in curly braces — the wizard detects them and prompts for values at runtime.

Syntax	What it renders	Example value
`{topic}`	A single-line text input you fill in before running the prompt.	distributed systems
`{audience}`	Free text for the target reader or user persona.	junior backend engineers
`{language}`	Any programming language name — used by the role description.	TypeScript
`{framework}`	Library or framework paired with the language above.	Next.js 16
`{context}`	A longer free-text block for background: stage, constraints, goals.	3-person startup, MVP phase, PostgreSQL

Use any name inside the braces. The names above are the conventions the built-in role presets look for — reusing them means presets plug in without edits.

Using your prompts

Saved prompts are not trapped in ParetoStudio. Reach them from three surfaces — MCP server, Chrome Extension, or the library UI.

Natural language via MCP

“Give me the onboarding email prompt”

What the AI does behind the scenes

search_prompts({ query: "onboarding email" })
// → returns matches
get_prompt({ prompt_id: "..." })

Requires the ParetoStudio MCP server. See the MCP setup guide.

Chrome Extension in your browser

“Inject my blog outline prompt into ChatGPT”

Chrome Extension flow

1. Open ChatGPT, Claude, or any supported chat.
2. Press Cmd+Shift+P (Ctrl+Shift+P on Windows/Linux).
3. Pick a prompt — the extension fills the chat input and pre-fills variables.

Copy from the library

“I want to paste this into DeepSeek”

Manual copy flow

1. Open Library → Prompts.
2. Select your prompt.
3. Click Copy — pick XML, Markdown, or JSON based on where you are pasting.

Limits

Saved prompts count against your plan. The wizard itself is unmetered — you can draft as much as you want. The cap only applies when you save.

Plan	Saved prompts	Output formats
Free	5	XML, Markdown, JSON
ProRecommended	Unlimited	XML, Markdown, JSON

Hit the limit on Free? Delete an older prompt or upgrade to Pro for unlimited saves. The wizard warns you when you have one save slot left.

Deploy on every plan

The Chrome Extension and MCP server are available on Free (capped at 50 req/day). Upgrading to Pro adds unlimited saves, agents, skills, and 500 req/day — it does not change the Prompt Builder itself.

Troubleshooting

Prompt didn't save

Check the save-limit banner in the wizard. On Free, you can hold up to 5 saved prompts. Delete one from the library or upgrade to Pro for unlimited saves.

Variable not rendering

Variables need matching curly braces with no spaces: {topic}, not { topic } or [[topic]]. Fix the braces and the variable appears in the runtime form.

Role preset won't load

Some presets depend on ontology data that ships with updates. Hard-reload the builder (Cmd+Shift+R on macOS, Ctrl+Shift+R on Windows) to fetch the latest role list.

Can't find a saved prompt in MCP

The MCP server indexes title, description, and content — but only prompts saved to your library. Drafts in the wizard are invisible until saved. If you have saved it, try search_prompts with a shorter, more generic query.

Debug an MCP lookup

search_prompts({ query: "onboarding" })
// broader query → more matches
// then narrow with get_prompt({ prompt_id })

Library

Agent Builder

Back to Homepage

Product

Prompt Builder

Who it's for

Marketers

Reuse campaign briefs, email flows, and ad copy prompts across clients and channels — without rewriting them every time.

Founders

Turn one-off ChatGPT sessions into a repeatable library your team can run, share, and improve together.

Anyone who reuses prompts

If you copy-paste the same prompt more than twice, save it once with structure and deploy it everywhere.

Anatomy of a structured prompt

Before you open the wizard, feel the shape of a good prompt. Click a part to see why it is there and how it reads in the final XML.

Anatomy of a prompt

Click a part to see why it matters

<role>You are a senior backend engineer with 10+ years building distributed systems. You favor boring, battle-tested technology over novelty.</role><context>We are a 3-person SaaS startup pre-Series A. Our stack is Next.js + Supabase. We have 40k MAU and growing 15% month over month.</context><task>Review the attached Postgres schema for a multi-tenant billing table. Flag any design that will cause contention at 10x current volume.</task><thinking>Think step by step. First enumerate every table and index. Then identify hot rows. Then estimate lock contention under concurrent writes.</thinking><format>Return a markdown table with columns: concern, severity (low/med/high), affected tables, suggested fix. Keep each row to one sentence.</format><instructions>If a concern is speculative, mark it with a ⚠ and keep it to one row. Do not invent tables that are not in the schema.</instructions>

Why role assignment matters

Who is the AI speaking as? A role gives it a point of view — vocabulary, priorities, blind spots. "Act as an engineer" is too vague; "Act as a senior engineer who favors boring tech" sets a bar.

You never start from scratch

Each step ships with researched presets — 104 roles, 1,560 task suggestions, preset thinking patterns, and quick format options. The wizard asks the questions you would forget.

The six steps

Every saved prompt walks through the same six stages. You can go back at any point — the Live Preview reflects changes instantly.

Step 1·
Role Assignment
Req
Define expertise and perspective
Tell the AI who it is — expertise, seniority, specialization. "Senior React architect" gives fundamentally different answers than a generic "developer". Pick from 104 researched roles or write your own.
Step 2·
Context Setting
Establish background and situation
The AI starts with zero knowledge of your project. Write what it needs — what you are building, who it is for, constraints, decisions already made. Without context, the model falls back to a generic baseline.
Step 3·
Task Specification
Req
Define clear objectives
Tell the AI exactly what to produce. "Analyze X, then generate Y in format Z" works; "help me with X" does not. 1,560 task suggestions across subcategories are available as presets.
Step 4·
Thinking Steps
Step-by-step reasoning process
Guide the AI's reasoning before it answers. List the stages you would think through yourself — it skips every step you do not name. Chain-of-thought beats one-shot for anything non-trivial.
Step 5·
Response Format
Define structure and presentation
How should the answer look? Bullet points, tables, headers, word count. Without format rules you get walls of text. Quick-format chips cover the common cases.
Step 6·
Final Instructions
Req
Your last words before execution
Your final checklist. Priorities, tone, things the AI must never do. The instructions closest to the end are weighted most heavily — this catches what the earlier steps missed.

Variables and inputs

Variables let one prompt serve many situations. Wrap anything that changes per run in curly braces — the wizard detects them and prompts for values at runtime.

Syntax	What it renders	Example value
`{topic}`	A single-line text input you fill in before running the prompt.	distributed systems
`{audience}`	Free text for the target reader or user persona.	junior backend engineers
`{language}`	Any programming language name — used by the role description.	TypeScript
`{framework}`	Library or framework paired with the language above.	Next.js 16
`{context}`	A longer free-text block for background: stage, constraints, goals.	3-person startup, MVP phase, PostgreSQL

Use any name inside the braces. The names above are the conventions the built-in role presets look for — reusing them means presets plug in without edits.

Using your prompts

Saved prompts are not trapped in ParetoStudio. Reach them from three surfaces — MCP server, Chrome Extension, or the library UI.

Natural language via MCP

“Give me the onboarding email prompt”

What the AI does behind the scenes

search_prompts({ query: "onboarding email" })
// → returns matches
get_prompt({ prompt_id: "..." })

Requires the ParetoStudio MCP server. See the MCP setup guide.

Chrome Extension in your browser

“Inject my blog outline prompt into ChatGPT”

Chrome Extension flow

1. Open ChatGPT, Claude, or any supported chat.
2. Press Cmd+Shift+P (Ctrl+Shift+P on Windows/Linux).
3. Pick a prompt — the extension fills the chat input and pre-fills variables.

Copy from the library

“I want to paste this into DeepSeek”

Manual copy flow

1. Open Library → Prompts.
2. Select your prompt.
3. Click Copy — pick XML, Markdown, or JSON based on where you are pasting.

Limits

Saved prompts count against your plan. The wizard itself is unmetered — you can draft as much as you want. The cap only applies when you save.

Plan	Saved prompts	Output formats
Free	5	XML, Markdown, JSON
ProRecommended	Unlimited	XML, Markdown, JSON

Hit the limit on Free? Delete an older prompt or upgrade to Pro for unlimited saves. The wizard warns you when you have one save slot left.

Deploy on every plan

Troubleshooting

Prompt didn't save

Check the save-limit banner in the wizard. On Free, you can hold up to 5 saved prompts. Delete one from the library or upgrade to Pro for unlimited saves.

Variable not rendering

Variables need matching curly braces with no spaces: {topic}, not { topic } or [[topic]]. Fix the braces and the variable appears in the runtime form.

Role preset won't load

Some presets depend on ontology data that ships with updates. Hard-reload the builder (Cmd+Shift+R on macOS, Ctrl+Shift+R on Windows) to fetch the latest role list.

Can't find a saved prompt in MCP

Debug an MCP lookup

search_prompts({ query: "onboarding" })
// broader query → more matches
// then narrow with get_prompt({ prompt_id })

Library

Agent Builder

Back to Homepage

Prompt Builder

Who it's for

Anatomy of a structured prompt

The six steps

Role Assignment

Context Setting

Task Specification

Thinking Steps

Response Format

Final Instructions

Variables and inputs

Using your prompts

Limits

Troubleshooting

Prompt Builder

Who it's for

Anatomy of a structured prompt

The six steps

Role Assignment

Context Setting

Task Specification

Thinking Steps

Response Format

Final Instructions

Variables and inputs

Using your prompts

Limits

Troubleshooting