Using GitHub Copilot CLI

The command-line interface (CLI) for GitHub Copilot allows you to use Copilot directly from your terminal. For more information, see À propos de GitHub Copilot CLI.

Prerequisite

Install Copilot CLI. See Installation de GitHub Copilot CLI.

Using Copilot CLI

In your terminal, navigate to a folder that contains code you want to work with.
Enter copilot to start Copilot CLI.

Copilot will ask you to confirm that you trust the files in this folder.

Important

During this GitHub Copilot CLI session, Copilot may attempt to read, modify, and execute files in and below this folder. You should only proceed if you trust the files in this location. For more information about trusted directories, see À propos de GitHub Copilot CLI.
Choose one of the options:

1. Yes, proceed:

Copilot can work with the files in this location for this session only.

2. Yes, and remember this folder for future sessions:

You trust the files in this folder for this and future sessions. You won't be asked again when you start Copilot CLI from this folder. Only choose this option if you are sure that it will always be safe for Copilot to work with files in this location.

3. No, exit (Esc):

End your Copilot CLI session.
If you are not currently logged in to GitHub, you'll be prompted to use the /login slash command. Enter this command and follow the on-screen instructions to authenticate.
Enter a prompt in the CLI.

This can be a simple chat question, or a request for Copilot to perform a specific task, such as fixing a bug, adding a feature to an existing application, or creating a new application.

For some examples of prompts, see À propos de GitHub Copilot CLI.
When Copilot wants to use a tool that could modify or execute files—par exemple, touch, chmod, node ou sed—it will ask you to approve the use of the tool.

Choose one of the options:

1. Yes:

Allow Copilot to use this tool. The next time Copilot wants to use this tool, it will ask you to approve it again.

2. Yes, and approve TOOL for the rest of the running session:

Allow Copilot to use this tool—with any options—without asking again, for the rest of the currently running session. Any pending parallel permission requests of the same type will be auto-approved. You will have to approve the command again in future sessions.

Choosing this option is useful for many tools—such as chmod—as it avoids you having to approve similar commands repeatedly in the same session. However, be aware of the security implications of this option. For example, choosing this option for the command rm would allow Copilot to delete any file in the current directory or its subdirectories without asking for your approval.

3. No, and tell Copilot what to do differently (Esc):

Copilot will not run the command. Instead, it ends the current operation and awaits your next prompt. You can tell Copilot to continue the task but using a different approach.

For example, if you ask Copilot to create a bash script but you do not want to use the script Copilot suggests, you can stop the current operation and enter a new prompt, such as: Continue the previous task but include usage instructions in the script.

When you reject a tool permission request, you can also give Copilot inline feedback about the rejection so it can adapt its approach without stopping entirely.

Tips

Optimize your experience with Copilot CLI with the following tips.

Stop a currently running operation

If you enter a prompt and then decide you want to stop Copilot from completing the task while it is still "Thinking," press Esc.

Use plan mode

Plan mode lets you collaborate with Copilot on an implementation plan before any code is written. Press Shift+Tab to cycle in and out of plan mode.

Include a specific file in your prompt

To add a specific file to your prompt, use @ followed by the relative path to the file. For example: Explain @config/ci/ci-required-checks.yml or Fix the bug in @src/app.js. This adds the contents of the file to your prompt as context for Copilot.

When you start typing a file path, the matching paths are displayed below the prompt box. Use the arrow keys to select a path and press Tab to complete the path in your prompt.

Work with files in a different location

To complete a task, Copilot may need to work with files that are outside the current working directory. If a prompt you have entered in an interactive session requires Copilot to modify a file outside the current location, it will ask you to approve access to the file's directory.

You can also add a trusted directory manually at any time by using the slash command:

/add-dir /path/to/directory

If all of the files you want to work with are in a different location, you can switch the current working directory without starting a new Copilot CLI session by using either the /cwd or /cd slash commands:

/cwd /path/to/directory

Run shell commands

You can prepend your input with ! to directly run shell commands, without making a call to the model.

!git clone https://github.com/github/copilot-cli

Resume an interactive session

You can use the --resume command-line option or the /resume slash command to select and resume an interactive CLI session, allowing you to pick up right where you left off, with the saved context. You can kick off a Agent de programmation Copilot session on GitHub, and then use GitHub Copilot CLI to bring that session to your local environment.

Conseil

To quickly resume the most recently closed local session, enter this in your terminal:

copilot --continue

Use custom instructions

You can enhance Copilot’s performance, by adding custom instructions to the repository you are working in. Custom instructions are natural language descriptions saved in Markdown files in the repository. They are automatically included in prompts you enter while working in that repository. This helps Copilot to better understand the context of your project and how to respond to your prompts.

Copilot CLI supports:

Repository-wide instructions in the .github/copilot-instructions.md file.
Path-specific instructions files: .github/instructions/**/*.instructions.md.
Agent files such as AGENTS.md.

For more information, see Ajout d’instructions personnalisées pour GitHub Copilot CLI.

Use agents personnalisés

A assistant personnalisé is a specialized version of Copilot. Agents personnalisés help Copilot handle unique workflows, particular coding conventions, and specialist use cases.

Copilot CLI includes a default group of agents personnalisés for common tasks:

Agent	Description
Explore	Performs quick codebase analysis, allowing you to ask questions about your code without adding to your main context.
Task	Executes commands such as tests and builds, providing brief summaries on success and full output on failure.
General-purpose	Handles complex, multi-step tasks that require the full toolset and high-quality reasoning, running in a separate context to keep your main conversation clearly focused.
Code-review	Reviews changes with a focus on surfacing only genuine issues, minimizing noise.

The AI model being used by the CLI can choose to delegate a task to a subsidiary subagent process, that operates using a assistant personnalisé with specific expertise, if it judges that this would result in the work being completed more effectively. The model may equally choose to handle the work directly in the main agent.

You can define your own agents personnalisés using Markdown files, called profils d’agent, that specify what expertise the agent should have, what tools it can use, and any specific instructions for how it should respond.

You can define agents personnalisés at the user, repository, or organization/enterprise level:

Type	Location	Scope
User-level assistant personnalisé	local `~/.copilot/agents` directory	All projects
Repository-level assistant personnalisé	`.github/agents` directory in your local and remote repositories	Current project
Organization and Enterprise-level assistant personnalisé	`/agents` directory in the `.github-private` repository in an organization or enterprise	All projects under your organization and enterprise account

In the case of naming conflicts, a system-level agent overrides a repository-level agent, and the repository-level agent would override an organization-level agent.

Agents personnalisés can be used in three ways:

Using the slash command in the CLI's interactive interface to select from the list of available agents personnalisés:
```
/agent
```
Calling out to assistant personnalisé directly in a prompt:
```
Use the refactoring agent to refactor this code block
```
Copilot will automatically infer the agent you want to use.
Specifying the assistant personnalisé you want to use with the command-line option. For example:
```
copilot --agent=refactor-agent --prompt "Refactor this code block"
```

For more information, see Création d’agents personnalisés pour Agent de programmation Copilot.

Use skills

You can create skills to enhance the ability of Copilot to perform specialized tasks with instructions, scripts, and resources.

For more information, see Création de compétences d’agent pour GitHub Copilot CLI.

Add an MCP server

Copilot CLI comes with the GitHub MCP server already configured. This MCP server allows you to interact with resources on GitHub.com—for example, allowing you to merge pull requests from the CLI.

To extend the functionality available to you in Copilot CLI, you can add more MCP servers:

Use the following slash command:
```
/mcp add
```
Fill in the details for the MCP server you want to add, using the Tab key to move between fields.
Press Ctrl+S to save the details.

Details of your configured MCP servers are stored in the mcp-config.json file, which is located, by default, in the ~/.copilot directory. This location can be changed by setting the XDG_CONFIG_HOME environment variable. For information about the JSON structure of a server definition, see Extension de l’agent de codage GitHub Copilot avec le protocole MCP (Model Context Protocol).

Context management

Copilot CLI provides several slash commands to help you monitor and manage your context window:

/usage: Lets you view your session statistics, including:
- The amount of premium requests used in the current session
- The session duration
- The total lines of code edited
- A breakdown of token usage per model
/context: Provides a visual overview of your current token usage
/compact: Manually compresses your conversation history to free up context space

GitHub Copilot CLI automatically compresses your history in the background when your conversation approaches 95% of the token limit, without interrupting your workflow.

Enable all permissions

For situations where you trust Copilot to run freely, you can use the --allow-all or --yolo flags to enable all permissions at once.

Toggle reasoning visibility

Press Ctrl+T to show or hide the model's reasoning process while it generates a response. This setting persists across sessions, allowing you to observe how Copilot works through complex problems.

Find out more

For a complete list of the command line options and slash commands that you can use with Copilot CLI, do one of the following:

Enter ? in the prompt box in an interactive session.
Enter copilot help in your terminal.

For additional information use one of the following commands in your terminal:

Configuration settings:

copilot help config

You can adjust the configuration settings by editing the config.json file, which is located, by default, in the ~/.copilot directory. This location can be changed by setting the XDG_CONFIG_HOME environment variable.
Environment variables that affect Copilot CLI:

copilot help environment
Available logging levels:

copilot help logging
Permissions for allowing or denying tool use:

copilot help permissions

Commentaires

Si vous avez des commentaires à propos de GitHub Copilot CLI, veuillez nous en faire part en utilisant la commande à barre oblique /feedback dans une session interactive et en choisissant l’une des options. Vous pouvez remplir un questionnaire privé, soumettre un rapport de bogue ou suggérer une nouvelle fonctionnalité.

Next steps

Copilot CLI can operate as a conversational assistant, answering questions and helping you write code interactively. Beyond chat, Copilot CLI supports a range of agentic modes that allow you to delegate tasks with greater autonomy.

You can work with agents in Copilot CLI to support a full task lifecycle, from delegating work to reviewing results:

Delegate tasks autonomously: Run Copilot CLI in autopilot mode to complete multi-step tasks without requiring approval at each step. See Delegating tasks to GitHub Copilot CLI.
Invoke custom agents: Invoke specialized agents tailored to specific tasks, such as code review, documentation, or security audits. See Invoking custom agents.
Steer agents: Guide and refine agent behavior during task execution to keep work on track. See Steering agents in GitHub Copilot CLI.
Request a code review: Use Copilot CLI to get an AI-powered review of your code changes. See Requesting a code review with GitHub Copilot CLI.

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