# Code

A task's code is a [**Liquid**](/platform/liquid.md) template. In the same way that a Shopify storefront might use a Liquid template to receive requests and render HTML, a task uses its Liquid code to receive events, and render a series of JSON objects. These JSON objects define [**actions**](/core/tasks/code/action-objects.md), [**logs**](/core/tasks/code/log-objects.md), and [**errors**](/core/tasks/code/error-objects.md).

{% hint style="info" %}
In Mechanic, actions are performed after their originating task run concludes. Actions are not performed inline during the task's Liquid rendering.

To inspect and respond to the results of an HTTP action, add a task subscription to mechanic/actions/perform, allowing the action to re-invoke the task with the action result data.

Learn more: [Responding to action results](/techniques/responding-to-action-results.md)
{% endhint %}

Task code always has access to a set of [**environment variables**](/core/tasks/code/environment-variables.md), which can be used to make decisions about what JSON objects to render.

A task must purposefully consider its [**preview**](/core/tasks/previews.md), so as to accurately communicate its intent to users and to the Mechanic platform.

{% hint style="info" %}
To find many examples of task code, browse <https://github.com/lightward/mechanic-tasks>.
{% endhint %}

## See also

* [Liquid basics](/platform/liquid/basics.md) — syntax, data types, variables, filters, and control flow
* [Mechanic filters](/platform/liquid/filters.md) — Mechanic-specific filters for data manipulation
* [Mechanic tags](/platform/liquid/tags.md) — `{% raw %}{% action %}{% endraw %}`, `{% raw %}{% log %}{% endraw %}`, `{% raw %}{% error %}{% endraw %}`, and more
* [Mechanic objects](/platform/liquid/objects.md) — event, task, options, cache, and action objects available in your code
* [Writing a high-quality task](/techniques/writing-a-high-quality-task.md) — patterns and practices for reliable Mechanic tasks


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://learn.mechanic.dev/core/tasks/code.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
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.