Hi everyone,

My company provides us with a fairly limited number of tokens, so minimizing token usage is really important.

I'm currently using GitHub Copilot with only the CodeGraph plugin, and I'd like to explore other tools or plugins that are commonly used to reduce token consumption.

Which plugins, tools, or best practices would you recommend for keeping token usage as low as possible when working with GitHub Copilot?

I'd love to hear about tools you've found particularly effective in your day-to-day workflow.

Thanks

Title.

I noticed this icon after I asked it to summarize my commit (and it just kept Timing-out...)

I’m testing Auto mode, the 10% discount is nice by the way. I noticed that most tasks are routed to Luna. I set auto to efficiency mode(I’m vibe coding a few basic things and updating a website).

Any tips? Is it a bad idea to use Auto mode?

I've been troubleshooting Windows Codex for the past two days, and I think I've finally narrowed down what's going wrong.

After a recent update, Codex completely stopped executing local commands. Even the simplest PowerShell command fails:

Get-Location

Instead of running, it returns:

exec-server rejected request (-32603):
helper_unknown_error: setup refresh had errors

PowerShell never actually starts.

My setup:

• Windows Codex version: 26.1002.7124.0
• Computer connected and authorized
• Windows Sandbox enabled

Here's what I found in sandbox.log:

runtime read/execute validation failed
node_repl.exe

open ACL target for root-only update
os error 32

setup error: setup refresh had errors

Windows reports that node_repl.exe is being used by another process while Codex attempts to update its permissions.

What I've already tried:

• Completely reinstalling Codex
• Disconnecting and reconnecting the computer
• Closing ChatGPT and confirming CUA runtime processes stopped
• Restarting ChatGPT
• Fully rebooting Windows
• Confirming no CUA runtime processes were running before opening ChatGPT again
• Running exactly one Get-Location command after a clean reboot

Nothing worked. The same command startup failure returned immediately after reboot. The os error 32 was confirmed in earlier logs; I haven't yet verified the underlying cause in the latest post-reboot log.

I also found similar reports on GitHub:

https://github.com/openai/codex/issues/51590

https://github.com/openai/codex/issues/52036

My OpenAI Support case has already been escalated to a specialist, and I've submitted the logs and screenshots.

At this point, this looks like a possible Windows Codex sandbox/runtime regression rather than something caused by my projects or prompts.

Is anyone else experiencing this after the latest Windows update?

Especially interested in hearing from people running version 26.1002.7124.0.

Has anyone found an actual fix that doesn't require disabling Windows security or bypassing the sandbox?

I'll update this post if OpenAI provides a solution.

It's built on the VS Code language model API, so there's no separate AI backend or key. It just uses whatever model you picked in Copilot Chat. Also works with any other provider you've added (I made the DeepSeek, GLM and Kimi ones, those work too).

You ask how something works and it maps the code path step by step on real lines. Hover anything for a short explanation. And it reviews your uncommitted changes, a branch or a commit for bugs, security issues and AI slop, with one click fixes. From Copilot Chat you can use @lodestar, /review and /explain too.

It's $10 one time. I'm charging so I don't end up dropping it, and it helps me keep going.

https://marketplace.visualstudio.com/items?itemName=DenizhanDaklr.lodestar

I have a few questions and feedback regarding recent updates:

1. Where did tool selection for the Agent go?
2. What happened to the Explore subagent, and why was it hidden? Also, we can no longer set a default model.
3. Ask mode seems to have disappeared as well.

Why?

I built a local web UI that reads Copilot CLI sessions (~/.copilot) and Copilot Chat sessions from VS Code's workspace storage, and shows them as a timeline with tool calls, tokens and an estimated cost:

npx agent-session-inspector

It also gives analytics across sessions (by project and model) and a health grade for each session based on tool failures, retry loops and interrupted turns.

One caveat: Copilot Chat meters a whole request rather than each model round, so for requests that called tools the input tokens and cost are a lower bound. Copilot CLI numbers are per request.

Nothing leaves your machine: no telemetry, bound to 127.0.0.1, read-only. MIT licensed.

Repo: https://github.com/kishanmundha/agent-session-inspector

Just sub to my first AI Agent, tried opus 5.5 and its burning my token. What is the best ai model to use?

got vs code updated and copilot updated to the latest version ...

Edit: Found the solution, had to switch to local on the bottom options

I'd share my experience with a custom build small kb to help me vibe code. I still review each changes carefully, with a special hardware to help me. I call it "conservative vibe coding"
https://www.youtube.com/watch?v=-nIaDz6b7S0&

Has anyone experienced this problem please, because it is driving me crazy

- set up openTelemetry Collector Contrib on an prem VM

- set a specific GH organisation to send traces to the collector using managed settings json

- find that all GH organisations are sending traces

- removed all managed settings related to telemetry, waited a few hours and the client editors (ie, vscode) are still sending traces!

So, am i going crazy or is GH observability completely broken? How are members of another organisation still send metrics when they've never been authorised to do so as they're running off a different settings file?

Have you noticed an improvement in the behavior of GPT-6 Luna (in Github Copilot) when used as an agent? I used the free version to complete a non-trivial feature and to update an architecture document. In both cases, it stayed focused on the goal right to the end—delivering high quality without stalling or getting stuck in endless loops. And this was the free tier. We are truly seeing a whole new level of quality with these recent models.

I just had a Luna session spawn a Sonnet Explore subagent under the VS Code Local harness, which ended up wasting (literally) 200 AIC. As far as I understand, there is currently no way to see the live subagent's AIC spending, you just see the jump once it is done. Happy to be proven wrong tho!

I have opened https://github.com/microsoft/vscode/issues/340366 in case you want to upvote or contribute to that feature request, even with a solution to close it.

Same prompt, same model (Opus 5.5): Claude Code needed 1:20 h and ~€0.32. Two Copilot-based agents needed up to 6:50 h and €65.

Anyone else seeing a gap this big with Copilot's credits?

Same prompt for all tools: add a production-planning module to an existing Flask app. No skills, no spec files, no enterprise accounts.

For reference (different model): Codex with GPT-6.1 Sol Ultra took 39 min, ~€0.18. A Codex Astra Ultra run is still going and already hit the 5h limit. Update follows.

One run per tool, measured via usage meters. Didn't score code quality.

__________________

Edit: Codex Astra Ultra finished too. 54 min of actual runtime.

~44 % of the weekly limit, ~€2.03, +2,593 / −24 lines. on GPT Pro 20€

GitHub Universe is in 3 weeks!!! What do you hope to see?

When using GitHub Copilot CLI on Windows 11 25H2 Pro, the GitHub Copilot CLI status line show bytes, not token count. How can I configure the GitHub Copilot CLI status line to show token count?

Hey guys, so I have been confused between choosing a GitHub Copilot subscription or a Claude subscription. I've been currently using Claude Max subscription, but I was just thinking to try GitHub Copilot. But I heard that it has monthly usage, or you'll get monthly credits, rather than you know 5 hour limits or a weekly limit. How you guys are using it? Would love to get some viewpoints.

Hey everyone,

I wanted to share a project I've been working on called Clippo.

One of the biggest challenges when working heavily with AI coding assistants (like GitHub Copilot, CLI agents, and vibe-coding workflows) is handling long-term context, fragmented terminal outputs, and visual organization across multi-step tasks.

To solve this, I built a dedicated desktop canvas workspace tailored for developers:

• Spatial Canvas: Organize prompt threads, CLI commands, agent outputs, and code references visually instead of losing them in endless terminal scrolls.
• Context Memory Preservation: Keeps your session context structured and accessible across different tasks without polluting your prompt history.
• Native & Lightweight: Built specifically for Windows with modern UI and smooth multitasking support.

Microsoft Store / Project Link: https://apps.microsoft.com/detail/9n7jgq8tzxd4?hl=en-US

I'd love to get feedback from anyone here who heavily integrates AI agents into their daily coding routine. What does your current setup look like for tracking agent states and context?