> For the complete documentation index, see [llms.txt](https://mycroft-ai.gitbook.io/docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://mycroft-ai.gitbook.io/docs/mycroft-technologies/adapt/adapt-examples.md).

# Adapt Examples

{% hint style="info" %}
If you are looking to use Adapt in a Mycroft Skill, please see [Skill Development > Intents](/docs/skill-development/user-interaction/intents.md)
{% endhint %}

## Single intent Parser

[See the Single Intent Parser code on GitHub](https://github.com/MycroftAI/adapt/blob/master/examples/single_intent_parser.py)

This sample **Intent Parser** uses a fixed vocabulary to extract entities for an **Intent**. This type of intent parser is useful when the parameters of the **Intent** are well-bounded; that is, the possible **Utterances** are well known.

## Multi-intent Parser

[See the Multi-intent Parser code on GitHub](https://github.com/MycroftAI/adapt/blob/master/examples/multi_intent_parser.py)

This sample **Intent Parser** uses multiple **Intents**, and disambiguates between them using intent confidence. For example, if one **Intent** has a higher confidence than the second, the **Intent Parser** will assume the first **Intent**.

## Regular Expression (regex) Intent Parser

[See the Regex Intent Parser code on GitHub](https://github.com/MycroftAI/adapt/blob/master/examples/regex_intent_parser.py)

This sample **Intent Parser** uses a regular expression entity to extract location from a query. This type of **Intent Parser** is useful where a parameter needs to be extracted from a query and it takes a form that can be expressed in regex. Other parameters that are often expressed in regex are IP address, names of people and colors.

...