How to add prompts to a project

Adding prompts in LLM Pulse is intentionally simple.

You can create them in several ways, depending on how structured or exploratory you want to be.

You do not need to overthink it. The goal is to start collecting real AI visibility data as quickly as possible.

Every method lives in one place: Prompt Research. From a single topic search box you can add prompts manually, in bulk, or generate them from People Also Ask questions, Google Search Console, Reddit Insights, topics, Keyword to Prompts, translations, and reputational angles.

You can mix any of these methods within the same project. The sections below explain when each one is the right choice.

1. AI-generated prompts

When you create a new project, LLM Pulse automatically suggests an initial set of prompts based on the project context, so you can start tracking AI visibility immediately.

Prompt discovery continues over time. New ideas are regularly suggested in the Prompts tab, under Suggestions, allowing you to expand and refine what you monitor as the project evolves.

This makes prompt research an ongoing process, ensuring your visibility analysis stays relevant as your focus changes.

2. Manual prompts (single or bulk)

You can also add prompts manually whenever you need to. This is useful when you already know what you want to track and prefer full control over the setup. Choose "Add Manually" to create prompts one by one, or "Add in Bulk" to paste a list at once. This makes it easy to reuse existing prompt lists, migrate setups from other tools, or scale your projects without friction.

When you add a prompt manually, you can also pick the target countries and languages it should run in, so your tracking reflects the markets that matter to you.

To add many prompts at once, choose "Add in Bulk", pick the target country and language, and paste one prompt per line. You can optionally assign a tag before importing them all together.

If your prompts live in a spreadsheet or another AI visibility tool, choose "Import from CSV" instead. Upload a .csv file with a prompt column and, optionally, country, language and tags columns (separate multiple tags with a pipe). You can download a ready-made template from the modal, and country or language cells left empty fall back to the project defaults. Tags that do not exist yet are created automatically, and duplicate prompts are skipped, so migrating a fully tagged prompt set from another tool takes a single upload.

3. Google PAA (People Also Ask)

You can generate prompts directly from Google People Also Ask questions. This helps connect traditional search intent with the way users phrase questions in AI assistants.

You can do this using one or multiple keywords. It is especially useful if you already work with SEO data, since it lets you extend existing research into LLMs without changing your workflow.

This is done from Prompt Research, then selecting "People Also Ask".

4. Keyword-based prompts

Keyword to Prompts can start from a topic, brand, keyword, full query, complete prompt, or domain. LLM Pulse keeps that exact input as the main subject, finds the most closely related search terms for the selected country and language, and converts them into natural prompts that reflect how users search in LLMs. When you start from your own domain or a configured competitor, the generated prompts stay non-branded.

This is ideal when you want tightly focused variations around a specific idea without letting the broader project context take over. If you want to focus on queries that already drive organic visibility, use "Google Search Console" instead. You can access both options from Prompt Research.

When you connect Google Search Console you can choose to keep the connection (recommended) so your Search Console data stays synced and is available through the API and MCP connector, or run a one-time read that stores nothing. Keeping connected is available on the Growth plan and above.

5. Topic-based prompts

You can create prompts by defining specific topics. LLM Pulse will generate natural-language prompts related to those topics, giving you broad coverage around a subject.

This approach works well when you want to monitor a concept, product category, or problem space. You can do this from "Topic Prompts" in Prompt Research. You can also use "Reddit Insights" to surface questions real people are asking, "Translate Prompts" to extend your tracking into other languages, and "Reputational Prompts" to monitor how AI models talk about your brand.

Adding a new market (country and language)

A common question is where to add a market or a country to an existing project. There is no market list in Project Settings, because in LLM Pulse a market is a country and language pair on each prompt, not a project-level setting.

That means one project can track as many markets as you want. The country and language shown on the project itself are only the defaults applied to new prompts and to the GEO tools. Changing them does not move the prompts you already have.

To open a new market:

1. Go to Prompts and choose Translate Prompts in Prompt Research. Pick the source locale (the market you already track), then the target country and language. Your prompts are localized for the new market, with brand names preserved. This is the fastest route when you want to mirror an existing set.
2. Or add the prompts directly with Add Manually, Add in Bulk or Import from CSV, selecting the new country and language in the configuration step. With CSV you can set a different country and language per row.
3. Assign a tag per market (for example "France" or "Mexico") so you can compare markets later on the dashboard and in reports.

Two things worth knowing before you start:

• Each country and language combination is a separate prompt and uses a prompt slot. The same question tracked in Spain and in France counts as two prompts against your plan allowance. The review step always shows the exact number of prompts that will be created.
• Once the prompts exist, you can filter by country and language on the Overview, Prompts, Responses and Sources views, so each market can be analyzed on its own.

Conclusions

You can mix all these methods within the same project. There is no "correct" setup. Start simple, review the data, and iterate as you learn what really matters for your use case. Each prompt you add is automatically monitored across every AI model you track (ChatGPT, Perplexity, Gemini, Google AI Mode and Google AI Overviews), so you get consistent and comparable visibility data from day one, without any extra setup.

Once added, every prompt appears in the Prompts tab with its own mention rate, citations, and week-over-week change, so you can see at a glance which queries you already win and where there is room to grow.

Adding prompts should never be a bottleneck. LLM Pulse is built to remove friction from the process, so you can spend your time analyzing insights and making decisions, not configuring the tool.