# Here is an example of how you can give the LLM your own tools to use (loaded with the `-t` command line argument)

# For more examples, refer to the builtin toolsets - https://github.com/robusta-dev/holmesgpt/blob/master/holmes/plugins/toolsets/

toolsets:

# Name of the toolset (for example "mycompany/internal-tools")

# Used for informational purposes only (e.g. to print the name of the toolset if it can't be loaded)

switch_clusters:

# Description of the toolset. Used for display in the UI

description: "Set of tools for switching between kubernetes clusters"

# Documentation URL. Used for display in the UI

docs_url: "https://kubernetes.io/docs/home/"

# Icon URL. Used for display in the UI

icon_url: "https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcRPKA-U9m5BxYQDF1O7atMfj9EMMXEoGu4t0Q&s"

# Tags for categorizing toolsets, 'core' will be used for all Holmes features (both cli's commands and chats in UI).

# The 'cluster' tag is used for UI functionality, while 'cli' is for for command-line specific tools

tags:

- core

# Prerequisites is a list of conditions checked by Holmes before using the toolset

prerequisites:

- command: "kubectl version --client"

# List of tools the LLM can use - this is the important part

tools:

# Name is a unique identifier for the tool

- name: "switch_cluster"

# The LLM looks at this description when deciding what tools are relevant for each task

description: "Used to switch between multiple kubernetes contexts(clusters)"

# A templated bash command using Jinja2 templates

# The LLM can only control parameters that you expose as template variables like {{ this_variable }}

command: "kubectl config use-context {{ cluster_name }}"