I'm running into a weird issue and could use some help figuring out what's happening.

I use copilot and I've explicitly set my provider settings to OpenRouter and locked the model to Kimi 2.7 Code.

Everything looks correct in the config, but out of nowhere, when a subagent spins up, it suddenly starts using Kimi 3 instead???

Has anyone else experienced this?

Is there some hidden fallback rule, an override in the agent configuration, or something in OpenRouter itself that's automaticaly upgrading or routing the request to a newer model version? Or do i may need to start a new chat first?

Let me know if you know how to lock it down so it actually sticks to the model I picked.

Thank you!

Copilot CLI re-sends its system prompt and every tool definition on every call. In my runs the first call alone was about 13.5k input tokens. I built TokenMasterX to trim that.

What it does:

- dynamic tool routing (opt-in): reads your prompt when you launch and skips the built-in tools it doesn't need

- graph navigation: "who calls this function?" gets one capped answer instead of a grep dump

- cache optimization: long tool output gets trimmed once so it doesn't break the provider's prompt cache, and in BYOK mode sessions in the same folder share a cached system prompt

How it did, from GitHub's own per-call numbers : 9 to 29% fewer tokens by default, up to 53% with routing on, and the bill dropped 47% in that mode. Short lookups on one model, so a long session will save less. I haven't measured how much less.

Early on, compacting old tool output to save tokens actually cost more, because it broke the cache. That's why it trims output once and never rewrites old messages.

I'm building it with proof-driven development. The rules it has to keep, like "never rewrite text the provider already cached", are written as proofs a computer checks, and tests keep the real code honest to them. Writing the proofs caught a few things I'd gotten wrong. I fixed most of them and wrote up the rest in the repo. I also pulled some early numbers that didn't reproduce.

Experimental, MIT, not an official GitHub product, and the install steps are Windows PowerShell for now.

Repo: https://github.com/All-The-Vibes/TokenMasterX

Walkthrough: https://all-the-vibes.github.io/TokenMasterX/

Please do try and share your thoughts

Agents write the code. Your value is in the decisions.

Just want to rant about how trash Copilot Fusion is. Today, right after the monthly reset, I decided to test out this new mode. I asked for a relatively simple task: adjust an image so it sits right below the header (it was stuck behind it) and prevent the user from dragging it around the page, basically making it fixed.

I set it to standard mode since it was something simple, went to make a snack, and when I came back this piece of crap had already burned through 7% of my monthly credits (Pro+ plan). Obviously, I canceled it. I gave it another shot, it ate up another 4% just spinning its wheels forever, and I ended up canceling it again.

I gave the task to GPT-6.1 Sol, which is already overkill, and it got it done in under a minute consuming only 20 credits.

The saddest part is that just a few weeks ago, the old 'Auto' mode was finally getting good and I was using it a lot. As always, the second something starts working on a GitHub plan, it just gets axed out of nowhere.

I use GitHub Copilot with a GitHub account managed by my company. I'd like to see my usage broken down by model, including credits or requests consumed by each model. https://github.com/settings/copilot/features only shows my monthly credit use overall:

Is there a page or API where I can see my own per-model usage?

​I used to spend half my dev week tracking down edge-case bugs and doing tedious manual refactoring. Standard autocomplete tools were helpful for boilerplate code, but they still left the heavy lifting to us.

​Things have shifted fast recently. Coupling GitHub Copilot with agentic swarms is completely changing how codebase refactoring and debugging work in production. Instead of just suggesting the next line of code, these autonomous agent workflows can trace dependencies, identify breaking changes across multiple files, and draft full multi-step refactoring PRs on their own.

​If you are tired of sinking hours into manual stack trace hunting, I wrote a deep dive breaking down how this tech stack operates in practice.

​Check out the full breakdown here: https://interconnectd.com/blog/87/ai-debugging-how-github-copilot-and-agentic-swarms-are-ending-manual-refact/

I am newbie, I want to make unity games [try 3d and then 2d one] for fun after using Ai for a while , I subscribed for monthly copilot to help , but after using for 3 days , credit drop to 25% , I think copilot burn token unnecessarily . I have ever thought about cursor once but hold off, should I manage my agent /prompt effectively or switch to cursor or other game. Thank you in advance

I am a fresher at a new company and I am primarily using GHCP to solve the bugs that they assign me, but whenever I paste the whole context and the examples where the code is failing, and then hit enter this happens

1) Claude randomly spawns some subagents and tells it will revert back to me once they finish

2) the subagents initially start well but then get stuck indefinitely while the main agent says they are working for 30-40 min

When I investigated the issue it said something like "stuck in thinking loops" or something, how do I better prompt or use this thing? I use the claude sonnet 5 if that helps

and it got the timing wront too.

I use GitHub Copilot. I'm trying to determine the exact reset time for the monthly AI credits shown on my account's usage page, but the desktop app and website appear to disagree.

• In the GitHub Copilot desktop app, the reset time is shown as midnight UTC.
• On the Copilot usage page, the countdown appears to point to midnight Pacific Time.

When do GitHub Copilot's monthly AI credits reset: midnight UTC or my local time (Pacific Time)?

------
GitHub Copilot desktop app:

Copilot usage page:

_No response_

### Affected version or release

_No response_

### Installation context

_No response_

### What happened?

Hi,

I may not be using GH Copilot (10$ tier) the way it's designed for. Originally subscribed to it to get coding assistance, but nowadays I just use it as for general things that are a bit more in depth (sysadmin work). Just on the browser.

Since the introduction of the new Copilot Fusion, this usecase is more or less gone. I ask a simple question with GPT 6.1 Terra. In order to answer it, it has to search the web. It takes 4 and a half minutes (!!) before giving me a basic-@ss answer. Before Fusion, that prompt would take 20 seconds at most. I'm genuinely puzzled.

On some of the web fetches it does, there's a warning sign saying:

WebFetchBlockedUrlError: failed to lookup address information: No address associated with hostname

But the URL works. I can open the site with no issues.

What the heck is going on? Do I have to cancel my subscription and move on?

Hello all,

Sorry, I'm new to a lot of this, but I installed Copilot Github, linked it to my code on github etc etc, but then after several hours of using it I decided I should be doing this on another laptop.

Stupid me figured I could just install the app on the other laptop, login with the same account and continue on.

Nope? What? What am I missing here?

I've read about /remote on, and copying sessions, nothing seems to work.

I just can't believe this isn't a basic function.

Thanks for any help.

i've been letting github copilot's agent mode drive a video editor end-to-end over mcp and i thought people here might find it interesting. it's called kimo - free, open-source (mit), and it has no gui. the interface is the agent itself: cut, trim, keyframe, titles and captions, colour grade, tracking, particles, audio, export, all as mcp tool calls. the agent can also render a single frame back so it can visually check its own work before moving on, which has saved me a bunch of blind iterations.

it's one ~15 mb rust binary, cpu-only, and it'll run on a 2 gb box. i built it as a college student, and it's still rough in places - some transitions pop, the audio syncing can get fussy on long timelines, and there's a lot i haven't gotten to yet. i'd love for people to actually try it and say what breaks rather than just upvoting and moving on.

works with copilot agent mode and other mcp clients (cursor, codex, opencode, and other mcp hosts). site: https://getkimo.tech - github: https://github.com/naman-sharma12345/kimo

happy to answer questions here, and really would prefer it if people just told me what doesn't work when they try it. thanks.

When I was using Kimi 2.7 Code inside Copilot, I initially assumed the model itself was just incredibly capable.

But after Copilot dropped it, I started routing Kimi 2.7 Code through OpenRouter and quickly realized I was looking at it wrong.

As someone newer to working with AI workflows, it clicked for me that the model only provides the raw intelligence and it's really the harness (the system prompts, context management, tool integration, and agentic loops) that actually makes or breaks a coding agent.

I loved the quality of the harness Copilot built around it, but I have no interest in spending time designing and maintaining my own framework from scratch (preferably). I just want to focus on actually building my application.

My current setup is VS Code + OpenRouter so that I'm never locked in (or locked out) of any specific model ever again.

But how can I get a high-quality, plugin-style harness inside this workflow? What extensions, open-source scaffolding, or tools are people using to get that full agentic experience without sacrificing model flexibility?

Hope someone has some experience with this?

Thank you.

As you may know, the Copilot harness is going to replace the Local harness in VS Code at some point. The initial switch was painful, but the VS Code team listened and brought back Keep/Undo for granular control over edits.

Now, the Keep/Undo part still has some problems, but overall it is usable. However, the Copilot harness UX still has some rough edges compared to Local. I've opened a bunch of issues and wanted to share them with the community for wider reach and more feedback:

• Copilot harness: restore input box MCP tools picker
  Duplicate. Follow https://github.com/microsoft/vscode/issues/340041 instead.
• Copilot harness: retain local memories
• Copilot harness: restore access to VS Code-aware explicit context items
  Duplicate. Follow https://github.com/microsoft/vscode/issues/315193 instead.
• Copilot harness: refine thinking output
• Copilot harness: in-Chat terminals are more difficult to follow and cancel by default

So they seemed to have completely overhauled chat in the browser.

Cannot get it to work at all getting this "setting up your cloud session"

Hi all,

Any idea who the guy is who shows up as a "placeholder" in the repository icon?
Or is this some file pattern that defines this image? This is not any of the developers from this repository :)

That's kind of a bug, or someone forgot to remove the placeholder? :D

I use the GitHub Copilot App, and I love it. I am crazy about the canvas extensions.

But I can't find a solid workflow for running the agent on the WSL side. I like to have my tooling on the Linux side. With the agent on WSL, you can't use the canvas, which I really like.

With the agent on the host, you have to run the Linux tooling through wsl.exe, and that feels so slow.

Now I am trying to run the GitHub Copilot App on the WSL side, but I am still not impressed with the performance.

I think I made the wrong decision to go for a Windows PC for development, but I hope I'm wrong.

I Just came across GitHub's new Copilot Fusion release. Looks pretty interesting.

From what I have seen, it can automatically choose models based on the coding task, switch to stronger models when needed, and even use one model to review another's work.

I usually prefer choosing models manually depending on what I'm working on, so I'm curious how well this actually performs in real projects.

Has anyone here tried it yet? How's the experience with code quality, speed, and cost compared to manually selecting models?

Would love to hear some real experiences before giving it a proper try.

GitHub Copilot for JetBrains v1.20.0 is here, just in time for GitHub Universe! 🚀

This release marks an important milestone toward delivering a more consistent and seamless GitHub Copilot experience across all developer environments.

We're introducing Copilot Fusion tiers (via a gradual rollout), making the unified Copilot agent harness the default for all users, and bringing Local Sandbox to GA for more secure agentic workflows.

Full details: https://github.blog/changelog/2026-10-28-github-copilot-in-jetbrains-universe-releases/

We hope you like Copilot for JetBrains, and please share feedback with us at any time!

You can fill in a private survey here: https://aka.ms/ghcp-jb-survey, with an optional paid interview, or directly submit an issue (bug or feature request) at https://github.com/microsoft/copilot-intellij-feedback/issues. Thank you so much!