> For the complete documentation index, see [llms.txt](https://helpdocs.conducttr.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://helpdocs.conducttr.com/feature-documentation/designing-and-running/channels/information-based-channels/graph.md).
# Graph
The Graph channel provides a **feedback mechanism** to players based on the choices they take. It's a tool that allows you to **visualise and communicate key data trends** during an exercise. It can be used for stock prices, website views, campaign donations etc.
| Benefit | Feature |
| ------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------ |
| Monitor data in real-time | Create dynamic, interactive charts (line chart) that track metrics throughout the exercise |
| Provide a feedback mechanism to players based on the choices they take | Update graphs via the MEL |
| Increase immersion by showing changes of a time-based metric such as visitors to a website, campaign donations etc. | Use static value, variables or formula |
## Running
This is what the Graph channel looks like to players
***
## Designing
### How to (Injects)
{% stepper %}
{% step %}
### Create a new inject
Change the channel to Graph.
{% endstep %}
{% step %}
### Select the audience
Who do you want to send the inject to? This may be role or team orientated.
{% endstep %}
{% step %}
### Select which number the Graph should chart
To work with a Variable you'll need to use Calculations somewhere else in the scenario but adding a number is the simplest way.
{% endstep %}
{% endstepper %}
{% hint style="success" %}
Send Graph injects to respond to player choice throughout the exercise to develop the graph.
{% endhint %}
### How to (Configuration)
Go to `Configuration` > `Player desktop` > `Graph` > see Chart type to choose a *Line* or *Bar* chart and to label the axis.
---
# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.
## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.
Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:
```
GET https://helpdocs.conducttr.com/feature-documentation/designing-and-running/channels/information-based-channels/graph.md?ask=&goal=
```
`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.
Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
