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

# Quickstart

> Add prompts, confirm competitors, and read your first measured number within a day.

The fastest path to a real number is four moves: add the prompts your buyers ask, confirm the competitors you want compared, wait for the first daily readings, then read the board. Setup takes a few minutes. The first answers land within a day, because readings run on a daily cadence.

<Steps>
  <Step title="Add your prompts">
    A Prompt is one question phrased the way a buyer phrases it, not a keyword. `best invoicing software for freelancers` is a prompt; `invoicing` is not.

    Start with ten to twenty prompts that map to how people actually shop for what you sell: category questions, comparison questions, and problem questions. Group related ones into a Topic so you can read a whole buying question as a single line later.

    Your plan sets how many Prompt slots you have: 50 on Starter, 150 on Growth, 350 on Business. A slot is occupied for as long as the prompt is tracked, and freeing one is as simple as removing the prompt.
  </Step>

  <Step title="Confirm your competitors">
    Attensira reads every answer for your brand and for each competitor you track. Add the names buyers would put in the same sentence as yours, and check the spellings — a competitor named differently from how models write it will look absent when it is not.

    Competitor rates share the same denominator as yours, which means they will not add up to 100%. Two brands can both appear in the same answer, and often do.
  </Step>

  <Step title="Wait for the first readings">
    An hourly in-process ticker enqueues work, but each prompt × model × country combination runs **at most once per workspace-local calendar day**. So the first answers arrive within a day of setup, not within minutes, and adding a prompt after today's run has already fired means its first reading lands tomorrow.

    A new workspace tracks two model surfaces: ChatGPT and Perplexity. Add more from settings if you want them.

    Sampling depth is the number of times each prompt × model is asked per day: `n = 1` on Starter, `n = 3` on Growth and Business, issued concurrently. Failed runs are stored for inspection but excluded from `n`, so a bad day lowers your sample size rather than faking a zero.

    <Warning>
      Do not read the first day as a trend. With `n = 1` a single day is one coin flip per prompt; rates only mean something once several days have accumulated.
    </Warning>
  </Step>

  <Step title="Read the board">
    Two numbers matter first. **Mention rate** is the share of successful runs that named your brand. **Citation rate** is the share of successful runs that attached a link to your own domain. They answer different questions: whether the model knows you, and whether it sends readers to you.

    Every rate arrives as a value plus `n`, the number of successful runs behind it. A value of `0` with `n > 0` is a real measured zero. A **null** value means not measured — no successful run exists for that cell, and it is not a zero.

    Per-model numbers also carry `tracked` and `readable`. `tracked: false` means that model is not configured for this workspace and was never queried, so reading it as 0% invents a failure that did not happen. `readable: false` means no reader exists for that surface.

    Changes over time pass a two-proportion z-test at 95%. Below that noise floor you get `{real: false, value: null}`, which means "no change we can prove" — never zero.
  </Step>
</Steps>

## What next?

Ask the agent why a number looks the way it does, then hand the recurring parts to an Automation. If you want your own tooling to read the same data, the [MCP server](/mcp/overview) exposes fifteen tools over Streamable HTTP.

<Tip>
  Word-to-field mapping, and why the wire format still says `keyword_id` and `group_id`, is on [Concepts](/start/concepts).
</Tip>