Using CodeCompanion

CodeCompanion continues to evolve with regular frequency. This page will endeavour to serve as focal point for providing useful productivity tips for the plugin.

Apply an LLM's edits to a buffer/file

The @insert_edit_into_file tool, combined with the #buffer editor context or /buffer slash command, enables an LLM to modify code in a Neovim buffer. This is especially useful if you do not wish to manually apply an LLM's suggestions yourself. Simply tag it in the chat buffer with @files or @insert_edit_into_file.

Code review an LLM/agent's changes

You can review an LLM or agent's changes like a pull request. :CodeCompanionCodeReview opens every change in the quickfix list, one entry per hunk. You can step through them, leave in place comments with :CodeCompanionCodeReview Comment and then share the review in a chat buffer with the #{code_review} context.

To navigate to the files an agent has edited or created, use :CodeCompanionChat Changes to open them in the quickfix list. Every file the LLM touches in your Neovim session is tracked, across chats and the CLI.

Copying code from a chat buffer

The fastest way to copy an LLM's code output is with gy. This will yank the nearest codeblock.

Navigating between responses in the chat buffer

You can quickly move between responses in the chat buffer using [[ or ]].

Quickly accessing a chat buffer

The :CodeCompanionChat Toggle command will automatically create a chat buffer if one doesn't exist, open the last chat buffer or hide the current chat buffer.

When in a chat buffer, you can cycle between other chat buffers with { or }.

By default, opening or cycling to a chat hides whichever chat is currently visible. If you'd rather keep chats per tab — so a chat opened in tab A is never closed or stolen by activity in tab B — set display.chat.window.pertab = true in your config. With that enabled, { / } only cycles through chats that are visible in the current tab or not currently visible anywhere, and :CodeCompanionChat Toggle jumps to the existing tab when the chat lives there.

Run tests from the chat buffer

The run_command tool enables an LLM to execute commands on your machine. This can be useful if you wish the LLM to run a test suite on your behalf and give insight on failing cases. Simply tag the @run_command in the chat buffer and ask it run your tests.