The art of simplicity

Note: this is a follow-up to my post on monitoring GitHub Copilot Chat with the Aspire Dashboard. Same idea, different agent. Some developers on the team have switched (part-time) from Copilot Chat to Claude Code for their agentic work. Same question came up again: how much are we actually using it, what does it cost, and where does the time go in a session? Claude Code has its own OTel support, separate from Copilot's, so it needs its own setup — but it plugs into the exact same Aspire Dashboard we already had running. What Claude Code exports Claude Code emits three kinds of OTel signals: Metrics — session counts, token usage, cost, lines of code changed, active time Events — one event per prompt, per API call, per tool result, per permission decision Traces (beta) — a claude_code.interaction span per prompt, with claude_code.llm_request and claude_code.tool spans nested underneath Remark: traces are still beta. Metrics and events are the stable path ...

When talking to developers I get wildly different opinions about how "good" GitHub Copilot actually was for them. Some love it, some find it slow, some weren't sure it was doing anything useful at all(just kidding). The problem: nobody had any data. We were talking about token usage, latency and tool calls purely from gut feeling. GitHub Copilot can export all of that as OpenTelemetry traces, metrics and events. And the easiest way to look at it locally, without spinning up a cloud backend, is the Aspire Dashboard. Let's set that up. Why do we need this? Copilot isn't just autocomplete anymore. Every agent turn is a small orchestration: it calls a model, the model asks for tools, the tools run, the model answers. If you want to know where the time and the tokens go, you need to see that orchestration, not just the end result. That's exactly what the Open Telemetry integration gives you. Every agent interaction produces a span tree: invoke_agent copil...

If you search for "GitHub Copilot budget policy", most posts point you to cost centers: assign a budget to a cost center, map the cost center to a team or business unit, done. Clean story, except for one detail nobody mentions upfront — cost centers require a GitHub Enterprise Cloud account. That's not the same thing as being on the Copilot Enterprise plan; user-level budgets already work fine on Copilot Business. It's about the account type; a standalone Organization account doesn't have cost centers, and neither does GitHub Enterprise Server if you're self-hosted. If you're not on Enterprise Cloud, cost centers are off the table. We ran into exactly this. No Enterprise Cloud account, no cost centers, but still a real need to keep Copilot spend under control across a growing user base. Remark: if you do have GitHub Enterprise Cloud, cost centers are probably still the better fit. This post is for the rest of us. The starting point We have two...

Recently I got lost setting up Renovate against an internal NuGet feed. Dependency updates kept coming back with a 401, even though I had hostRules configured with credentials right there in renovate.json . No error, no obvious warning in the log that jumped out at me. Just an anonymous request going out where an authenticated one should have. Turns out the config was fine. The location wasn't. The problem The error itself didn't point anywhere near the config file: { "message": "Request failed with status code 401 (Unauthorized): GET https://tfs.vlm.be/tfs/DefaultCollection/_packaging/VLMFeed/nuget/v3/index.json", "response": { "statusCode": 401, "statusMessage": "Unauthorized", "body": "{\"$id\":\"1\",\"innerException\":null,\"message\":\"TF400813: Resource not available for anonymous access. Client authentication required.\",\...

In my effort to adopt an 'AI first' philosophy, I spend a lot of time automating my day-to-day activities and transforming them to skills. It's not the most exciting activity: I know exactly how to do a task, I've done it a dozen times by hand, but writing it down as a clean SKILL.md for an agent takes almost as long as just doing the task again. Microsoft created an open-source a tool that skips that step entirely: Skill Recorder . The idea is simple: you record yourself doing the task once, and it generates the skill for you. Sounds good? Let’s give it a try… What it actually does Skill Recorder is a desktop app (Electron, macOS-first with Windows 11 support) that captures a real work session on your screen: clicks, app and window switches, the pages you visit, clipboard snippets, and optionally your spoken narration. Nothing leaves your machine while you're recording. Capture, storage, frame extraction, and narration transcription all happen locally. T...

Note: this post is part of a series. Part one covered packaging a skill in a plugin for Claude Code . Same idea, different tool, this time focussing on GitHub Copilot. After writing that first post I got the obvious follow-up question: does this also work for GitHub Copilot? Short version: yes, SKILL.md itself is portable, but the plugin wrapper isn't. Copilot CLI has its own plugin format, laid out slightly differently from Claude Code's. What's the same? A skill is still just a folder with a SKILL.md inside: YAML frontmatter ( name , description , optionally license ), then a Markdown body with instructions. Copy that file as-is between tools — nothing about the skill content needs to change. What's different? Where Claude Code wants the manifest tucked inside .claude-plugin/plugin.json , Copilot CLI puts plugin.json straight at the plugin root: api-testing-plugin/ ├── plugin.json # Required manifest, at the root ├── agents/ #...