Skip to main content

Github Copilot on the command line (continued)

Yesterday I started exploring the Github Copilot CLI. Turned out that there was more to talk about than what would be good fit for one blog post. So here is a continuation of my previous post. In case you missed, go read that post first before continuing here.

Ready? Let's dive in again!

Let’s explore some features

Switching between models

The Github Copilot CLi was using Claude Code in my previous examples. I don’t know if that is the default or that there was a specific reason that this model was used by the CLI but you can easily switch between models through the /model command.

Hit enter to get a list of available models:

Select a mode and hit enter:

Extensibility with MCP servers

Copilot CLI ships with the GitHub MCP (Model Context Protocol) server built-in, enabling repository interactions and issue searches. But you can extend it further by adding any MCP server from the registry using /mcp.

Want to integrate Playwright for browser testing? Need to connect with your company's internal tools? Copilot CLI can be customized to match your specific workflow.

Add a new MCP server using /mcp add:

Use tab to navigate between the different input fields and hit CTRL-S to save the MCP server.

View the list of installed MCP servers through /mcp show:

Execute inline shell commands

A nice improvement I certainly want to mention is that with the latest update you can directly execute a command in the shell without making a call to the model:


More information

GitHub Copilot CLI: Enhanced model selection, image support, and streamlined UI - GitHub Changelog

Using GitHub Copilot CLI - GitHub Docs

Popular posts from this blog

Podman– Command execution failed with exit code 125

After updating WSL on one of the developer machines, Podman failed to work. When we took a look through Podman Desktop, we noticed that Podman had stopped running and returned the following error message: Error: Command execution failed with exit code 125 Here are the steps we tried to fix the issue: We started by running podman info to get some extra details on what could be wrong: >podman info OS: windows/amd64 provider: wsl version: 5.3.1 Cannot connect to Podman. Please verify your connection to the Linux system using `podman system connection list`, or try `podman machine init` and `podman machine start` to manage a new Linux VM Error: unable to connect to Podman socket: failed to connect: dial tcp 127.0.0.1:2655: connectex: No connection could be made because the target machine actively refused it. That makes sense as the podman VM was not running. Let’s check the VM: >podman machine list NAME         ...

Cache stampede: when our cache turned against us

While investigating some performance issues, we ran into an ASP.NET Core API that cached a fairly expensive aggregation query for 60 seconds. Under normal load, that was fine: one request rebuilds the cache, everyone else reads from it. Under peak load, dozens of requests would arrive in that same expiry window, all see a cache miss, and all fire the same expensive query in parallel. The database didn't like that. That was the moment when our caching layer stopped helping and started hurting. A burst of requests comes in at the same time, all miss the cache, and all go hammer the database or the downstream API at once. That's a cache stampede . The cache was supposed to protect our backend, and for a few hundred milliseconds it did the opposite. Why this happens IMemoryCache.GetOrCreate (and its async sibling) looks like it protects you, but it doesn't add any locking on its own. Look at the naive version: public async Task<Report> GetReportAsync(string key) ...

A complex system designed from scratch never works

A few years ago, I worked as an architect on a big mainframe rewrite. I still count it as one of my failures. Not because the technology was wrong, but because I couldn't convince the management team to simplify the approach. Years later, the organization is still struggling to get the new system up and running. I left the project at the time, because I couldn't put my name behind an approach that would take very long and cost a lot of money without a working system to show for it along the way. Gall’s Law That memory keeps coming back to me, because it's a textbook case of Gall's Law playing out in real life. Gall's Law , from John Gall's Systemantics , states it plainly: A complex system that works is invariably found to have evolved from a simple system that worked. A complex system designed from scratch never works, and it cannot be patched to make it work. You have to start over with a simple system that works. What does that mean in practice,...