> For the complete documentation index, see [llms.txt](https://docs.avonnicomponents.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.avonnicomponents.com/lwc-components/getting-started/product-tour.md).

# Product Tour

## What is the LWC Components library?

**LWC Components** is a library of ready-to-use Lightning Web Components for Salesforce. It ships **50+ components** across two families:

* **Core Components** — base UI building blocks (avatars, badges, cards, pickers, menus, sliders, media players, and more) that you drop into any LWC.
* **Data Driven Components** — higher-level, data-aware components (data table, kanban, scheduler, pivot table, timeline, tree, map, list, image list, chat, and more) that render a dataset automatically. Point them at a query or hand them static data and they take care of the rest — filtering, sorting, search, pagination, and drag-and-drop included.

Every component is documented with a live example, its attributes, events, and slots. Browse them under [**Core Components**](/lwc-components/core-components/core-components.md) and [**Data Driven Components**](/lwc-components/data-driven-components/data-driven-components.md).

## Who is it for?

The library is built for **developers and admins alike**:

* **Developers** compose the `avonni-*` components directly in their own LWCs and Aura components for pixel-perfect, reusable UI.
* **Admins** assemble data-driven experiences declaratively — configuring a query, a field mapping, and a few attributes — without writing custom Apex or JavaScript.

## Built for AI-assisted development

The components are designed to be **AI-tooling friendly**. Whether you build with **Salesforce Vibes**, **Claude Code**, **Codex**, or another AI coding assistant, the assistant can discover each component's API and generate correct markup for you — so you go from idea to working UI in minutes.

{% hint style="info" %}
The library exposes a component catalog (names, attributes, events, slots, and styling hooks) that AI assistants can read to scaffold and configure components accurately.
{% endhint %}

## Installation

Install the Avonni LWC Components from the Salesforce AppExchange. See the [Installation & Licenses Management](/lwc-components/getting-started/installation-and-licenses-management.md) guide for the full step-by-step instructions and requirements.

{% embed url="<https://appexchange.salesforce.com/appxListingDetail?listingId=a0N4V00000FiERkUAN>" %}
View the Avonni LWC Components listing on AppExchange
{% endembed %}

## Next steps

* [Installation & Licenses Management](/lwc-components/getting-started/installation-and-licenses-management.md) — install the package and set up licenses.
* [Core Components](/lwc-components/core-components/core-components.md) — browse the base UI components.
* [Data Driven Components](/lwc-components/data-driven-components/data-driven-components.md) — browse the data-aware components.


---

# 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 dynamically by asking a question.

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

```
GET https://docs.avonnicomponents.com/lwc-components/getting-started/product-tour.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

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.
