In the notebook metadata set the `tags` and `description``front_matter` properties. For example:
```json
{
"...": "...",
"metadata": {
"...": "...",
"front_matter": {
"tags": ["code generation", "debugging"],
"description": "Use conversable language learning model agents to solve tasks and provide automatic feedback through a comprehensive example of writing, executing, and debugging Python code to compare stock price changes."
The `tags` field is a list of tags that will be used to categorize the notebook. The `description` field is a brief description of the notebook.
## Best practices for authoring notebooks
The following points are best practices for authoring notebooks to ensure consistency and ease of use for the website.
- The Colab button will be automatically generated on the website for all notebooks where it is missing. Going forward, it is recommended to not include the Colab button in the notebook itself.
- Ensure the header is a `h1` header, - `#`
- Don't put anything between the yaml and the header
### Consistency for installation and LLM config
You don't need to explain in depth how to install AutoGen. Unless there are specific instructions for the notebook just use the following markdown snippet: