Skip to main content

Awesome GitHub Copilot just got awesommer (if that’s a word)

If you've been following the GitHub Copilot ecosystem, you've probably heard of the Awesome GitHub Copilot repo. It launched back in July 2025 with a straightforward goal: give the community a central place to share custom instructions, prompts, and chat modes for tailoring Copilot's AI responses.

A lot of people contributed. As a result, the repo now contains 175+ agents, 208+ skills, 176+ instructions, 48+ plugins, 7 agentic workflows, and 3 hooks.

And now the maintainers took it one step further and created an Awesome GitHub Copilot website and Learning hub.


A website that actually helps you find things

The new site lives at awesome-copilot.github.com and wraps the repo in a browsable interface built on GitHub Pages. The headline feature is full-text search across every resource — agents, skills, instructions, hooks, workflows, and plugins — with category filters to narrow things down.


Each resource has its own page with a modal preview, so you can see exactly what you're getting before committing.


And if you find something that you like, there's a one-click install directly into VS Code or VS Code Insiders.

The Learning Hub: making sense of a fast-moving space

One of the more additions is the Learning Hub. If you've felt like the GitHub Copilot customization landscape moves faster than you can keep up with — you're not imagining it. 

The Learning Hub is designed to cut through that churn by focusing on fundamentals: what are agents, skills, and instructions, and how do they actually differ? What's a hook versus a plugin? And once you understand the concepts, how do you take an existing resource and adapt it for your own needs, or build something from scratch?


It's the kind of documentation that tends to get skipped in fast-growing open-source projects, so it's good to see it getting proper attention here.

Plugins and the new resource types

The plugin system is where things get practically interesting. A plugin bundles related agents, skills, and commands into a single installable package — think themed collections for frontend development, Python, Azure, or whatever your team's stack looks like. Awesome GitHub Copilot is now a default plugin marketplace for both GitHub Copilot CLI and VS Code, which means installing something is as simple as:

copilot plugin install <plugin-name>@awesome-copilot


Or search for agent plugins through the extensions in VSCode by typing @agentPlugins:

Check it out!

If you use GitHub Copilot regularly and haven't explored what's possible with custom agents and skills, the new website is a much friendlier starting point than diving into the raw repo. Browse at awesome-copilot.github.com, or head straight to the Learning Hub if you want the conceptual grounding first. And if you've built something useful for your own workflow, the repo is wide open for contributions.

More information

Awesome GitHub Copilot | Awesome GitHub Copilot

Learning Hub | Awesome GitHub Copilot

Awesome GitHub Copilot just got a website, and a learning hub, and plugins! - Microsoft for Developers

Finding inspiration for good custom instructions for GitHub Copilot

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         ...

Azure DevOps/ GitHub emoji

I’m really bad at remembering emoji’s. So here is cheat sheet with all emoji’s that can be used in tools that support the github emoji markdown markup: All credits go to rcaviers who created this list.

VS Code Planning mode

After the introduction of Plan mode in Visual Studio , it now also found its way into VS Code. Planning mode, or as I like to call it 'Hannibal mode', extends GitHub Copilot's Agent Mode capabilities to handle larger, multi-step coding tasks with a structured approach. Instead of jumping straight into code generation, Planning mode creates a detailed execution plan. If you want more details, have a look at my previous post . Putting plan mode into action VS Code takes a different approach compared to Visual Studio when using plan mode. Instead of a configuration setting that you can activate but have limited control over, planning is available as a separate chat mode/agent: I like this approach better than how Visual Studio does it as you have explicit control when plan mode is activated. Instead of immediately diving into execution, the plan agent creates a plan and asks some follow up questions: You can further edit the plan by clicking on ‘Open in Editor’: ...