> For the complete documentation index, see [llms.txt](https://docs.wedolow.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.wedolow.com/documentation/wedolow-mcp-server/usage/optimize-your-project.md).

# Optimize your project

## Start the optimization with VSCode extension (GitHub Copilot)

In the chat Window, type `/optimize_wedolow` and press enter. That's it!

<figure><img src="/files/xLmgCd05b0IxL6CQkPQa" alt=""><figcaption></figcaption></figure>

## Other agents and manual installation

Once [your project is configured](/documentation/wedolow-mcp-server/usage/project-configuration.md), everything is ready to optimize it. To run the optimization, just ask your AI agent:

> Optimize my project with WedoLow MCP Server. Start with getting the initial instructions.

Now, let the AI agent interact with the MCP server and your code until your code is fully optimized.

<figure><img src="/files/9MKwl6ELDOmehIDFu1I8" alt=""><figcaption><p>Gemini CLI working to optimize your code</p></figcaption></figure>

At some point, the MCP could require inputs from you:

* Allowing MCP Server specific tools access.
* Allowing commands in your terminal. The AI agent sometimes uses custom commands during the optimization process, for auto-correction or even to modify code based on substitutions.
* Asking you if you want to continue if running for a long time, or warn you about your usage.
* Ask you to make a choice about something.

When the AI agent stops to wait for an input, give the appropriate input based on your own judgement of the situation, and don't hesitate asking it explicitely to continue the optimization process.

When the optimization ends, the AI Agent generates an optimization report at the root of your project, named **wedolow\_optimization\_report.md**. This report sums up everything that happened during the optimization, what worked, what didn't and why, the performance improvements, etc.

Review the report and the code modifications, and feel free to use the result or ask your AI agent to revert some of the changes it did.

{% hint style="warning" %}
As a counterpart for the WedoLow MCP Server Beta, when an error occurs or the optimization is successful, the AI agent will send **your optimization report** and data present in **.wedolow\_mcp** directory to WedoLow server, as well as an anonymous ID for your system. Though your codebase is not sent to WedoLow, do not use WedoLow MCP Server beta with confidential code as there can be traces of it in the data sent.
{% endhint %}


---

# 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:

```
GET https://docs.wedolow.com/documentation/wedolow-mcp-server/usage/optimize-your-project.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.