tl;dr
GitHub Copilot CLI is a terminal-native, agentic coding assistant that brings GitHub Copilot’s AI into your shell. Instead of only offering completions in an editor, Copilot CLI lets you ask natural-language questions, plan and execute multi-step tasks, edit files, run tests, and operate on repositories without leaving the terminal. It’s designed for interactive use by developers and for programmatic automation in CI and other workflows.
Why it matters
- Agentic workflows in the terminal: Copilot CLI is more than a chat tool. It can propose multi-step plans, run commands, apply edits, run and re-run tests, and iterate until a stated goal is reached. You can choose manual approvals at each step or allow the agent to run autonomously. This reflects a broader trend toward “agentic” developer tools that orchestrate work across code, tests, and repository metadata.
- Deep GitHub integration: The CLI understands repository context (issues, pull requests, commits) so agents can perform end-to-end tasks—like triaging an issue, creating a branch, writing code and tests, and opening a PR—directly from your shell.
- Extensibility and embedding: Copilot CLI can be extended with custom “skills” or plugins, and GitHub provides a Copilot SDK so teams can embed the same agent runtime into programs and services in multiple languages.
Core capabilities (what you can do)
- Natural-language requests in the terminal: Ask questions, request new features/files, refactors, or tests using plain English.
- Plan & execute: Use a “plan” mode where the agent sketches multi-step actions. You can approve steps interactively or allow full automation.
- Edit and test: Apply edits to files, run your test suite, summarize test failures, produce diffs and patches, and undo changes if needed.
- Automation/CI friendly: Run the CLI in headless or programmatic modes (for example, in GitHub Actions) with flags like –no-ask-user and explicit model selection for deterministic behavior.
- Repository-aware actions: Reference issues, PRs, and commit history as part of tasks.
Real-world use cases
- Scaffolding or refactoring code: From one terminal command you can add a feature, refactor a module, and generate unit tests.
- Debugging workflows: Ask Copilot CLI to run your tests or commands, propose and apply fixes, and re-run until issues are resolved.
- CI automation: Use the CLI inside GitHub Actions or other CI to generate reports, update changelogs, or run routine repository tasks.
- Terminal-first workflows: For developers working remotely or on remote servers, Copilot CLI reduces context switching between terminal, editor, and web UI.
Security, governance, and practical considerations
- Authentication: The CLI uses GitHub accounts and supports browser- and device-code authentication flows. In CI you provide tokens. The tool will prompt for trust confirmation of files in the active folder before taking write actions.
- Subscription & licensing: It requires a Copilot subscription—confirm access before expecting availability.
- Secrets and permissions: Treat tokens, secrets, and write permissions carefully. The agent can edit files and run commands, so use approval modes and sandboxing for sensitive repositories. Enterprise controls and policies are emphasized in the docs and changelogs.
- Auditability: Because it can operate programmatically and make multiple edits, include logging and review checkpoints in automated runs to preserve traceability.
Getting started (quick)
- Install (example using npm; Node 22+): npm install -g @github/copilot
- Run the CLI and authenticate: copilot
- Try a simple prompt: copilot -p “Add unit tests for the OrderService” and follow the interactive plan
Example: calling Copilot CLI from a Python script
- Use subprocess to run Copilot in headless mode and capture its summary output. import subprocess, shlex cmd = [“copilot”, “-p”, “Run tests and summarize failures”, “-s”, “–no-ask-user”]
result = subprocess.run(cmd, capture_output=True, text=True)
print(result.stdout)
Example: calling Copilot CLI from C# (Process)
- Pseudocode to invoke the CLI from .NET and capture output. using System.Diagnostics; var startInfo = new ProcessStartInfo(“copilot”, “-p \”Write unit tests for MyService\” -s –no-ask-user”)
{
RedirectStandardOutput = true,
UseShellExecute = false
};
var p = Process.Start(startInfo);
string output = p.StandardOutput.ReadToEnd();
p.WaitForExit();
Console.WriteLine(output);
Where to read more (official resources)
