> ## Documentation Index
> Fetch the complete documentation index at: https://docs.atomicagi.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Prompts

> Manage tracked prompts, identify ranking gaps, and prioritize the questions that need optimization first

<Frame>
  <img src="https://mintcdn.com/atomicai/2EwXzkqhhawPmJOp/images/data/ai-search/app-ai-search-prompts.png?fit=max&auto=format&n=2EwXzkqhhawPmJOp&q=85&s=d5a397947221d46294361faf9efcaf71" alt="AI Search Prompts page with top cards and prompt-level performance table" width="1720" height="1100" data-path="images/data/ai-search/app-ai-search-prompts.png" />
</Frame>

Use this page to decide whether your tracked prompt set matches real buyer demand.

<div className="atomic-info-callout">
  <p>
    <strong>Important:</strong> Better prompt coverage beats higher prompt
    count. Focus on business-critical prompts first.
  </p>
</div>

## Questions this page should answer

1. Are we tracking the prompts that matter most for pipeline?
2. Which prompts are underperforming right now?
3. Which prompt gaps should become this sprint's content work?

## Before you analyze

* Review the active prompt list before judging performance.
* Keep the same reporting window used in other AI Search pages.
* Compare by intent category, not only by total rows.

## What this page gives you

* Top prompt health indicators like average visibility and average position.
* Prompt-level table with position, mention frequency, top results, and category.
* `Add prompts` flow with two options: AI-suggested prompts and manual entry.
* A decision layer to connect prompt gaps to page updates.

## How prompt data is collected

Atomic runs your tracked prompts daily across the AI platforms shown in your `Generative engines` report (for example ChatGPT,
Claude, and Perplexity). We then compare patterns over time, because AI responses naturally vary day to day.

These tracked prompts should be written as conversational questions (for example `What's the best CRM for marketing agencies under
50 people?`), not short keyword fragments.

To mirror real buyer behavior, Atomic collects prompt results through AI product interfaces, not only via API outputs. This helps
you measure what users are likely to see in real interactions.

Why this matters:

* `Authentic experience`: data reflects the same interface-level outputs users interact with.
* `Real-world accuracy`: results are less abstract than API-only snapshots.
* `Broader coverage`: you can track platforms and model flows with limited public API access.

## How to read the top cards

* `Avg. visibility percentage`: average inclusion across tracked prompts.
* `Your avg position`: average placement quality.

Use both:

* Better position with low visibility means narrow coverage.
* Visibility up with weak position means presence without competitiveness.

<div className="atomic-highlight-card">
  <p>
    <strong>Key signal:</strong> Prioritize prompts where mention frequency is
    high but your average position is weak. Those are usually your fastest
    visibility gains.
  </p>
</div>

## How these metrics are calculated (simple)

### Avg. visibility percentage

```text theme={null}
Avg. visibility percentage = (Number of tracked prompts where your brand is present / total tracked prompts) x 100
```

### Your avg position

```text theme={null}
Your avg position = Sum of your placement indexes / Number of prompt responses where your brand appears
```

Lower value is better (closer to top placement).

### Mention frequency

```text theme={null}
Mention frequency = (Responses mentioning your brand for that prompt / Total sampled responses for that prompt) x 100
```

## How to read the prompt table

* `Your position`: current placement for that prompt.
* `Mention frequency`: how often your brand appears.
* `Top results`: recurring sources shown in answers.
* `Category`: funnel context.

Prioritize prompts that are high intent, high frequency, and weak in position.

## How to add new prompts

Use the top-right `Add prompts` button on this page.

`Add prompts (x/y)` shows how many tracked prompt slots are currently used versus your plan limit.

You have two options:

1. `Suggested prompts`: pick from AI-generated suggestions.
2. `Manual entry`: add your own prompt directly.

### Suggested prompts (AI-generated)

<Frame>
  <img src="https://mintcdn.com/atomicai/2EwXzkqhhawPmJOp/images/data/ai-search/app-ai-search-prompts-add-suggested.png?fit=max&auto=format&n=2EwXzkqhhawPmJOp&q=85&s=885a97c6bd29e837ccecad96bc322448" alt="Add prompts modal on Suggested prompts tab with generated prompt ideas, confidence, and save selected action" width="1536" height="1024" data-path="images/data/ai-search/app-ai-search-prompts-add-suggested.png" />
</Frame>

How suggestions are generated:

* Atomic analyzes your project domain plus top AI search pages from the last 30 days.
* The system generates prompt ideas across funnel categories (`awareness`, `consideration`, `decision`, `branded`).
* Each suggestion includes a confidence score to help you prioritize.

How to use suggested prompts:

1. Click `Add prompts`.
2. Keep `Suggested prompts` selected.
3. Review prompt text, category, and confidence.
4. Check the prompts you want, then click `Save selected`.
5. Use `Generate new` when you want a fresh set of ideas.

### Manual entry

<Frame>
  <img src="https://mintcdn.com/atomicai/2EwXzkqhhawPmJOp/images/data/ai-search/app-ai-search-prompts-add-manual.png?fit=max&auto=format&n=2EwXzkqhhawPmJOp&q=85&s=06d9cacaf1e78c8bc42092ccee4aab87" alt="Add prompts modal on Manual entry tab with prompt textarea and Add prompt button" width="1536" height="1024" data-path="images/data/ai-search/app-ai-search-prompts-add-manual.png" />
</Frame>

Use manual entry when you already know the exact prompt to track (for example from sales calls, campaign briefs, or competitor monitoring).

How to add manually:

1. Click `Add prompts`.
2. Switch to `Manual entry`.
3. Enter one prompt in natural language.
4. Click `Add prompt`.

## Quick weekly checklist

1. Review decision-intent prompts first.
2. Remove low-signal prompts that do not map to business goals.
3. Add missing high-intent prompts from sales conversations.
4. Assign one action per priority prompt.

## How to use filters

* Use category filters to separate awareness and decision queries.
* Use date range to confirm trend stability.
* Change one filter at a time when diagnosing.

## What to fix first

| Pattern in prompt data                  | What it usually means      | Recommended action                             |
| --------------------------------------- | -------------------------- | ---------------------------------------------- |
| Decision prompts rank poorly            | Commercial relevance gap   | Improve service-page fit and proof depth       |
| Awareness strong, decision weak         | Funnel imbalance           | Add decision-stage prompt coverage             |
| Mention frequency low across categories | Authority and coverage gap | Improve citations and topical breadth          |
| Good positions, weak traffic impact     | Prompt set too narrow      | Expand strategically similar prompt variations |

## Team routine

1. Weekly: refresh priority prompt backlog.
2. Bi-weekly: audit category balance.
3. Monthly: align prompt coverage with pipeline goals.

## Keep in mind

* Prompt quality is more important than prompt count.
* One viral query can distort short windows.
* Repeated gaps are more important than one-off misses.

## Where to go next

* [Pages](/data/ai-search/pages)
* [Competitors](/data/ai-search/competitors)
* [Citations](/data/ai-search/citations)
* [Overview](/data/ai-search/overview)