Perplexity Prompt Generator

What is the Perplexity Prompt Generator?

The Perplexity Prompt Generator is a free tool that turns a task into a prompt written for Perplexity's search-first answers. It comes with a persona, instructions, a format and constraints, framing the task as something with sources to verify rather than an opinion to give from memory, since Perplexity searches the web before answering.

How to use the Perplexity Prompt Generator

1. Describe what you want Perplexity to do in the first box. Name the companies, products, places and dates involved, because those are what it searches for.
2. Add the audience, format and anything the answer must not include in Context. It is optional.
3. Press Generate prompt.
4. Copy the prompt from Your Optimized Prompt, or press Open in Perplexity. The first time, sign up free to reveal it.

How does Perplexity use a prompt?

In two steps: it searches, then writes an answer from what it found, with numbered citations. A prompt that works on ChatGPT, such as "you are a strategist, write me a positioning brief", gives Perplexity nothing to search for, so it retrieves something generic and writes around it.

Perplexity's API documentation says the search step does not read the system prompt. Only the user message drives retrieval, so names, products, dates and places belong in the task, not in the persona.

What should a Perplexity research prompt include?

Searchable specifics: the entities, the timeframe, and what a source has to be before you will accept it. "Peer-reviewed or primary" is an instruction it can act on. "Reputable" is not.

Ask for attribution per claim rather than a list of links at the end. On the API, the domain and recency filters scope sources more reliably than asking in prose, and citations come back in their own field, so do not ask the model to write URLs into the text.

What is Perplexity bad at answering?

Anything with no answer on the open web. It searches anyway, so an opinion question comes back as somebody else's opinion with a citation attached. Creative writing, and reasoning over your own private documents, belong on a model that does not retrieve first.

What is a good Perplexity prompt template?

A good Perplexity prompt template names the subject, the timeframe, the sources you accept and the shape of the answer, in that order. For example: "Find [what you need] about [named company, product or topic] published since [date]. Use [primary sources, official documentation, peer-reviewed studies]. Present it as [a table, a short brief, five bullet points] with a citation on each claim, and say which points you could not find a source for."

Every bracket is something the search step can act on. The last sentence matters most: it gives Perplexity a way to report a gap instead of filling it with the nearest page it found.

The generator writes a fuller version of this for your task, with a persona and constraints. Keep the searchable specifics in the task line when you edit it, because those drive retrieval.

Ask for the format you will actually use. If the result goes into a spreadsheet, ask for a table with named columns; if it goes into a brief, ask for headings. And write timeframes as dates: "recent" means different things to different questions, while a stated month and year is something the search can act on.

For recurring research, keep the template and change only the brackets. That makes answers from different weeks comparable, which matters when the point of the research is to notice what changed.

How do you use follow-up questions in Perplexity?

Use follow-ups to narrow, not to restart. Perplexity keeps the thread's context, so after a broad first answer you can ask it to compare two of the options it found, to go deeper on one source, or to check a specific claim against a different kind of source.

Start a new thread when the subject changes. Earlier answers in a long thread keep steering what it searches for, which helps while you stay on topic and hurts once you move on.

A good pattern for research is one broad prompt from this generator, then two or three short follow-ups, each naming exactly what you want added, removed or checked.

Follow-ups are also the cheapest fact check. Ask "which of the sources you cited says this, and where?" for any claim you plan to reuse. If it cannot point to the passage, treat the claim as unsupported.

If the first answer leans on one type of source, such as vendor pages, ask a follow-up to repeat the search using a different type, such as independent reviews or official documentation, and compare the two. Where they disagree is usually where the useful answer is.

When should you use Perplexity's deeper research mode?

Use the deeper research mode when the answer needs many sources read and reconciled, such as a market overview, a literature scan or a comparison across a dozen products. It runs more searches and returns a longer report, at the cost of time. On the API this is a separate model, Sonar Deep Research.

For a single fact, a definition or a quick check, the standard answer is faster and usually enough. A deep research run with a vague prompt produces a long, vague report, so the prompt matters more there, not less: state the scope, the timeframe and the sections you want in the report before you run it.

Read the report's sources before its conclusions. A long report built on three press releases and a vendor blog is a summary of marketing, however well it is written. Put a source standard in the prompt, such as "prefer primary data and official documentation over news coverage", and check the source list against it.

It also helps to ask for the report's structure up front: the sections you want, the questions each should answer, and a closing list of what remains uncertain. A named structure keeps a long report from drifting into whatever the first sources happened to cover.

What are the best Perplexity prompts for SEO and market research?

The best Perplexity prompts for this kind of work are comparisons and checks with named entities. Some patterns that work: "Compare the pricing pages of [three named competitors] as of this month, in a table, citing each page." "List the main complaints about [product] in reviews and forum threads from the last six months, grouped by theme, with a citation per theme." "What does [official documentation] currently say about [specific feature]? Quote the relevant passage."

Each one names what to search, limits the time window and asks for a citation per point. Perplexity is also useful for seeing which pages it cites for a buyer's question in your category. The AI search query generator writes those buyer-intent queries for you.

Prompts to avoid: open opinion questions such as "what is the best strategy for", anything about your private data, and requests for long creative pieces. Perplexity will still answer, but the search step adds little and can pull in irrelevant pages.

For AI visibility checks, do not optimize the prompt at all. Run the question your buyer would type, unchanged. A polished research prompt shows what Perplexity can find, not what it shows a typical buyer.