The art of simplicity

With the change to token based billing, I pay a lot more attention on what my AI agents are doing. Although some info is available, I was missing the tools to evaluate my token consumption and have an in-depth understanding of what's going on. Until I discovered AgentsView. AgentsView is a local-first desktop and web app that reads those files and gives you a proper UI to work with them: browse sessions, search across all message content, see tool calls and thinking blocks, and get a quick health grade for each session. Let's install it and see what it actually looks like. Installation There are a few ways in, pick whatever fits your workflow. As a Windows user I decided to grab the latest .exe or .AppImage from the GitHub Releases page . The desktop app is fully bundled and auto-updates. Executing the downloaded executable will walk you through an installation wizard. Remark: There is also a CLI which uses the same data directory. Running it If you went the...

You built an MCP server in C#. It works great on your machine. Now you want to share it with colleagues, publish it to the community, or ship it as part of a product. The problem? Every time someone wants to use a local MCP server, they have to clone a repo, install runtimes, hand-edit a JSON config file, get the path wrong, edit it again... you know the drill. MCP Bundles ( .mcpb ) solve exactly that. They're the .vsix of the MCP ecosystem: a single file that a supporting app (like Claude for Desktop) opens with one click to present a guided install dialog. No terminal, no JSON editing, no "works on my machine." This post walks through taking a C# MCP server binary and packaging it into a distributable .mcpb file from scratch. What's inside a .mcpb file? Before touching anything, it helps to understand what you're building. A .mcpb file is just a ZIP archive with a specific structure: my-server.mcpb (ZIP file) ├── manifest.json ← required: ...

In previous posts, I covered how to customize the GitHub Copilot CLI statusline. First with the default options , then with a dynamic script . Today we're taking it a step further: integrating Oh My Posh to bring full prompt theming support to your Copilot CLI session. Oh My Posh has native support for GitHub Copilot CLI, so you get all its theming power (Nerd Font icons, color gradients, diamond-style segments,…) rendering right inside the Copilot CLI statusline. What Is Oh My Posh? Oh My Posh is a cross-shell prompt engine that lets you define richly styled prompts using a JSON (or YAML/TOML) configuration file. You probably know it from PowerShell or bash, but it also ships a dedicated copilot subcommand specifically for integration with GitHub Copilot CLI's statusLine feature. Prerequisites Oh My Posh installed ( winget install JanDeDobbeleer.OhMyPosh   see docs ) A Nerd Font installed and set as your terminal font (for icons to render correctly) Gi...

While reviewing an ASP.NET Core Razor page application that needed to share server-side configuration with client-side JavaScript, I noticed the following approach to inject a JSON object: <script> var featureFlags= @Html.Raw(Model.FeatureFlagsJson); </script> It works — until it doesn't. This post walks through the right way to do it, why the naive approach can blow up in your face, and what the production-safe pattern looks like. Why the naive approach is dangerous Directly interpolating server-side values into a <script> block creates an XSS (Cross-Site Scripting) vector . If any value in your config object contains characters like </script> , " , or ' , the browser can interpret that as the end of your script tag — or worse, execute attacker-controlled code. Consider this innocent-looking config value: public string FeatureFlags{ get; set; } = "My App </script><script>alert('pwned')"; Inlined naiv...

This final post continues on the multi-agent path: instead of one agent doing more things, we compose multiple agents doing the right things. Yesterday I demonstrated how to do this inside the Copilot SDK itself, today we look the broader ecosystem and I’ll show you how to integrate your Copilot SDK agent in the Microsoft Agent Framework. Microsoft Agent Framework The Microsoft Agent Framework(MAF) is the unified successor to Semantic Kernel and AutoGen. It provides a standard interface for building, orchestrating, and deploying AI agents. Dedicated integration packages let you wrap a Copilot SDK client as a first-class MAF agent — interchangeable with any other agent provider in the framework. The key distinction from Part 1: custom agents inside the SDK work within a single Copilot session, with the Copilot runtime as orchestrator. MAF operates at a higher level — it can compose a Copilot SDK agent with agents backed by Azure OpenAI, Anthropic, or any other provider, using st...

We've covered a lot of ground in this series: sessions and lifecycle, deployment and scaling, MCP integration, and skills. Each post added a new capability layer to a single agent. This post changes the shape of the problem: instead of one agent doing more things, we compose multiple agents doing the right things. There are two different levels at which you can do this. Inside the Copilot SDK itself, custom agents let the Copilot runtime orchestrate specialised sub-agents automatically within a single session. Beyond the SDK, the Microsoft Agent Framework lets you compose Copilot SDK agents with agents from any other provider in structured multi-agent workflows. In this post we stay inside the SDK. Our next and final post will look at the broader ecosystem and Microsoft Agent Framework integration. The problem with a single agent A single session with a broad system prompt is fine for many use cases. But as tasks grow more complex, the cracks show: A general agent need...