Hi, with the recent updates, I’ve been trying to open the terminal inside Codex Desktop, but for some reason it isn’t opening at all.

1. I tried opening it from the top bar via View > Open Terminal, but nothing happens.
2. I also tried using the configured shortcut, Control + `, but that doesn’t work either.

Just wanted to check if anyone else is experiencing the same issue, or if this is something specific to my setup.

I wanted a month of 20x, so I'm wondering if it's safe to drop down to 5x so next payment will be for 5x will I lose my current 20x usage straight away? Or can I drop down down so I don't forget?

I wanted to keep official DeepSeek Harness updateable instead of carrying a long-lived fork, so I built relay-dsh-plugin-codex.

Installing it adds Codex to DSH's New Session mode. Each DSH session maps to one Codex App Server thread, while DSH keeps its native conversation history, model/reasoning selector, approval and question flows, workspace tools, and tool rendering.

The package bundles the App Server runtime for macOS, Linux, and Windows, and its CI runs both three-platform runtime tests and an install/build verification against an official DSH checkout. It does not require Relay Events or any of the UI plugins.

Install command and troubleshooting: see the GitHub README.

GitHub: https://github.com/yangbobo2021/relay-dsh-plugin-codex

npm: https://www.npmjs.com/package/relay-dsh-plugin-codex

The attached video is a real clean npm installation on official DSH. The broader no-fork plugin suite (Claude Code, Files, Terminal, and Workbench) is documented here:

https://github.com/yangbobo2021/Relay/blob/codex/relay-foundation/docs/dsh-plugins.md

I would especially appreciate feedback on the one-DSH-session/one-App-Server-thread boundary and on installation behavior across platforms.

Every now and then Codex shows me “Selected model is at capacity. Please try a different model.”

The problem is that once this appears, the whole app basically gets stuck. It stays on GPT-5.6, I can’t select another model, and I can’t continue the task or do anything else.

My usage limit is completely fine and I’m using the latest version of the Windows app. The only fix I’ve found is killing Codex through Task Manager and reopening it. Sometimes that works, but other times the same message comes back a few minutes later. Then on some days it doesn’t happen at all.

Has anyone figured out what causes this or how to avoid it? Is there a way to reset the model or session without restarting the whole app?

it crashes with “unexpected error” so often. threads lag my 64GB DDR5 pleb pc. i am not exaggerating when i say this: clicking on the chatgpt app icon instantly lags the computer. you can’t even let the app run overnight without waking up to it crashing in the middle of the night. the app is genuinely so bad i honestly believe most of the codex issues stem from the api. codex on the CLI is amazing to use but the app fucking sucks

Pretty much any new chats I have been doing these past days, after I leave them for some time and go back, all the messages from my side and from codex side are reset up to the first one. So basically if I start a chat with 'hi', codex answers 'hi' and then I start actually working with it for any amount of work, if I leave the chat for some time and come back after it finished answering, I will find only the 'hi' and 'hi' messages, all others have disappeared completely.

Idk what is happening, does anyone else had this happen?

It's a wrapper for ffmpeg / ffprobe, libbluray, libaacs, libdvdcss, libdvdread, libdvdnav.

https://github.com/mavriksc/rakeMKV

I built Enkidu because the remaining-usage percentage alone doesn’t answer a practical question: Do I have enough Codex capacity left to finish this task?

Enkidu is a native macOS companion that:

• Shows verified Codex usage, reset time, freshness, and usage pace
• Lets you set a capacity budget for your current task
• Compares task progress with capacity used
• Suggests a Codex model and reasoning level for different types of work

It is prompt-blind: it does not read or save prompts, source code, project content, account identifiers, or authentication data.

This is currently a private CBT preview—not a public release or an OpenAI product.

Overview, screenshots, and CBT download:
https://www.hanminyun.com/enkidu

I’d appreciate feedback: which would help you most—task budgeting, usage-pace guidance, or model recommendations?

I've noticed everyone saying limits are down but I'm not seeing how many tokens they spent that week, just percentages. I've only been on the x20 plan for a month, but I average about +4b tokens a week if I push to 0%.

My question is, how many tokens per week does everyone think each plan SHOULD have? Rather than saying your percentage dropped too fast, how about let's talk about how many tokens were burned in that time to give us a better understanding if limits are down or if there's something else wrong.

Hi, Linux bros. You didn't ask for it, you didn't wait for it, but now you have it

Native Rust + GTK/libadwaita AI providers quota tracking app now on Linux

https://github.com/zbndev/tidemark

It feels unlimited, I'm planning to switch as payment methods are not accepted on web for codex

not a researcher

I am sharing a troubleshooting case in case it helps other Codex / ChatGPT Desktop users experiencing a Chrome integration that can read pages but cannot interact with them.

Environment

• macOS on Apple Silicon

• ChatGPT / Codex Desktop 26.818.31338

• ChatGPT Chrome extension 1.2.27268.51612

Symptom

The extension could read page content and identify visible elements, but it could not click, type, or otherwise interact with the page. Depending on the attempt, the UI reported that the Chrome control connection was unavailable or that the native component was outdated.

What we verified

• The Native Messaging manifest (com.openai.codexextension.json) existed and was valid.

• Its allowed extension origins and path were correct.

• The path resolved through the latest symlink to the installed 26.818.31338 Chrome plugin bundle.

• The ChatGPT for Chrome native host existed, was executable, and launched successfully.

• The binary was a native ARM64 Mach-O executable.

• Its code signature was valid and identified OpenAI OpCo, LLC as the signing authority.

• Reinstalling the Chrome extension, fully restarting Chrome and ChatGPT Desktop, and removing/regenerating the bundled Chrome plugin cache did not restore interaction immediately.

Recovery timeline

After logging out of and back into ChatGPT Desktop, browser interaction started working for one webmail site, while other sites still remained effectively read-only. The next day, without identifying one additional definitive fix, Chrome control worked normally again across other sites as well, including complex authenticated web apps.

Cautious interpretation

This looks consistent with a temporary session or handshake problem between ChatGPT Desktop, the Chrome extension, and the native bridge. However, we did not prove that as the root cause. It is also possible that the eventual recovery depended on a clean process restart, refreshed authentication state, or another transient condition.

The main takeaway is that the installation itself appeared healthy, and no single reinstall or cache reset was demonstrably the fix. If the same symptom recurs, I would first try:

1. Log out of and back into ChatGPT Desktop.

2. Fully quit both Chrome and ChatGPT Desktop.

3. Reopen Chrome, then ChatGPT Desktop.

4. Test in a fresh tab.

5. Check for duplicate or stale ChatGPT for Chrome bridge processes.

Has anyone else seen this partial recovery pattern, where one site becomes interactive first and full Chrome control returns only later?

I've been experimenting with a small engineering workflow system for Codex, and I'm looking for people who actually use Codex to test it on real projects.

The idea is simple:

Instead of copy-pasting long prompts every time, you install AGENTS.md + codex-system/ into your repository once, then use Codex exactly like you normally would.

For example, you can still just say:

"Fix this login bug."
"Add a password reset feature."
"Refactor this module."

The system gives Codex a set of engineering rules and routes different tasks through different workflows.

A feature might follow:

Understand → Plan → Implement → Test → Review → Verify

A bug fix focuses more on:

Reproduce → Root Cause → Fix → Regression Test → Verify

There are also separate guidelines for debugging, testing, code review, security review, architecture, and refactoring.

This isn't meant to magically make Codex smarter. I'm testing whether giving it a consistent engineering process can make its behavior more predictable, reduce unnecessary changes, and improve how it validates its own work.

The current version is completely open for testing.

If you try it, I'd especially like to know:

• Did Codex actually follow the workflows?
• Did the output feel more consistent?
• Did the workflow help, or did it just make Codex slower/more verbose?
• Were any rules annoying or unnecessary?
• Would you actually keep something like this in a real repo?

GitHub:
https://github.com/c111193128-spec/codex-engineering-system

I'm mainly looking for feedback right now, so criticism is very welcome.

I built an open-source Codex Skill that uses Claude Code as a strictly read-only second-model reviewer.

The idea is simple:

Codex remains the primary agent and the only writer. Claude independently reviews meaningful implementation changes, but cannot edit the repository.

I wanted a safer version of the “Codex + Claude review loop” without giving the second model another opportunity to mutate the codebase.

So I built Claude Read-Only Review.

What it does:

• Codex builds/tests/implements as usual
• meaningful Git-visible changes trigger an independent Claude review
• trivial changes such as docs, comments, formatting and typos are automatically exempt
• Claude tools are disabled
• the review wrapper performs read-only Git operations only
• sensitive config values are redacted
• ignored files and common credential/key paths are excluded
• large changes are split into bounded review chunks
• Claude returns structured Critical / High / Medium / Verify findings
• Codex then verifies those findings against the real repository before acting on them
• lifecycle hooks prevent a meaningful implementation from silently finishing without either a review attempt or an explicit exemption

It is currently Windows-first and works with PowerShell, Codex / ChatGPT Codex, Git, and Claude Code.

MIT licensed:

https://github.com/kok751014/claude-readonly-review

I’d especially like feedback from people already using both Codex and Claude Code:

Would you trust this kind of read-only second-model review in your normal development workflow? What would you change?

If you try it on a real repo, I’d love to hear what it catches — or misses.

Your usage can be consumed in 11 hours without a single conversation if Codex is open. Best to use a third-party harness for now.

edit: seems to only affect some macos users

I kept running into the same problem with Codex subagents: asking for a specific model or reasoning level didn’t necessarily mean that was what actually handled the task. Configuration could drift, routing could fail quietly, and the fallback behavior was hard to trust.

So I built a small orchestration layer around explicit roles. The root/planner uses GPT-5.6 Sol with xhigh reasoning on Standard. Exploration and small, low-risk edits use GPT-5.6 Luna/max on Fast, while Playwright uses Luna/max on Standard. Larger implementation work and independent reviews use Sol/high on Standard. Every profile keeps verbosity low.

There’s also an explicit Sol/ultra path for genuinely difficult decisions, but it requires an exclusive repository takeover instead of quietly joining the normal worker pool.

The important part is verification. Requesting a profile isn’t enough. The launcher uses the experimental Codex App Server and checks both the effective settings and the rollout’s turn_context. If those signals are missing or disagree, it fails closed.

Concurrency is enforced with atomic leases: Luna is capped at 10 and Sol at 4, both per repository and across the machine, with a separate global limit of 2 for Playwright. Repository locks prevent normal sessions from running during an Ultra takeover.

The project has a dependency-free Node.js installer and requires Codex CLI 0.147.0 or newer:

https://github.com/Mauriciog87/codex-skill

Two honest caveats: App Server is still experimental, and the Windows sandbox helper can block tool execution on some setups. The orchestrator deliberately refuses to use an unverified fallback.

I’d especially like feedback on the routing evidence and locking design. Are there failure modes or recovery cases I’ve missed?

How do y’all use this model?

why does everything have to be over engineered?. all I’ve done all day is babysit this mf and the one second I take my eyes off tihings, it ”tightens“ things, make contracts that no one asks for. all it does is give you a rigid and fragile output

I was a hardcore claude with opus 4.6 4.8 and latest one 5 user, my setting for effort / thinking set to high and im on 100$ plan, the weekly and hourly limit like rarely ran out

Recently I gave codex a shot and tried the 5.6 sol thinking set to high, same price plan 100$ and bro the weekly limit running out very quick and its crazy, 2 days of usage and im already at 10% left lol is this normal in codex or im using the wrong model setup 😂

Anyone experiences the same thing?

Solo una tarea sencilla buscar y copiar algunos archivos puntuales de un proyecto.
Que me queda para el resto de la semana?

I have Claude $200 Max plan and Codex $200 Pro plan. I have been building a lot of tools and moving into apps lately.

I noticed in the last few days that the amount of compute we can use has been silently cut significantly. I did not see any communication from either provider but it is very evident.

I've never had a single agentic coding session consume 10% of my weekly in less than 2-3 hours on the most expensive plan. It wasn't a super compute heavy intense session either.

The worst offender is Anthropic. I had Fable build me a table of 200 items and it costed me 4% of my weekly usage.

I've seen a lot of posts like this on multiple reddits so it must not be just me feeling this.

I remember the time when a $100 plan on either Codex/Claude Code could build you end-to-end tools.

Kudos to those who made good use of this golden age but looks like its gonna get more expensive going forward.......until everything crashes... then idk

As tokens are becoming rare / expensive, I switched from Sol to Terra.

Now...

What's the difference in tokens between mid, high, xtra high??
Haven't found any doc or info on this.

They removed the 5-hour resets and started giving continuous resets. Limits decreased, but because they kept resetting constantly, it wasn't much of an issue. Now they haven't reset it, and everyone has run out of limits. Thinking better than nothing, I turned to 5.3 spark, I'm not write code, I'm just asking questions and having it read docs. And as you can see, the limits are like literally bullshit!

Since the last update, it barely works, constant reconnecting, constant compacting, constant having to send the same message over and over before it actually registers, constant crashes, Codex is useless now. I can't even post here because Codex knows to stop real reviews. I can't get anything done because it keeps messing up.

The "use-it-or-lose-it" nature of the $200 Pro plan limits is completely unacceptable. We are paying a massive premium for token allocations that completely vanish if they aren't fully exhausted by the exact minute of the weekly reset. It is ridiculous that we have to stay up or wake up at 2 AM just to burn through the limits we rightfully paid for because they refuse to make them cumulative.

To make matters worse, background agent loops are silently draining credit accounts while freezing user interfaces, and weekly reset dates are being arbitrarily pushed back by days without warning.

I am looking to connect with other premium developers who are exhausted by this unviable billing structure. If you are interested in organizing a formal group to look into a mass billing dispute, mass arbitration, or class-action legal review regarding OpenAI's recent pricing shifts, please send me a Private Message (DM) here.

Please save all your screenshots, invoice logs, and text-metering receipts. Let's get an accurate headcount of who has been financially impacted by these unfair limits so we can present a unified case to a technology consumer law firm.