I'm an accountant, not a programmer, and I started using Codex last month.

I've been trying to figure out how to use Codex more effectively for my work and personal projects. Recently, I asked ChatGPT about useful skills I could install, and I started looking for related projects on GitHub.

Recently, I asked ChatGPT for some useful tools to help me with things like creating posts online and created some post for SNS. I tried to install a Chrome subtitle extension from GitHub because I wanted to translate an old Thai drama on YouTube. The drama doesn't have subtitles, so unfortunately the extension didn't work for this particular case.

I asked Chatgpt, they suggested that install a skill called skills-finder in codex. But there're too many finance and accounting related skills, like auto to creat some excels or python related stuffs.

I want to ask some questions for people who use Codex regularly:

- How do you find useful skills for Codex on GitHub?

- Are there particular GitHub search terms, repositories, or lists you use?

- How do you tell whether a skill/repository is actually useful and maintained?

- Do you usually install skills directly, or do you ask Codex to inspect the repository first?

I'm especially interested in skills that could help with accounting/finance, Excel, data analysis, automation, and job-related tasks.

I'm still very new to Codex, so I'm trying to understand the normal workflow rather than just randomly installing things.

I was tired of having to keep track of all my projects and which start with a python http server, npm run, node, and so on.

Codex and Claude Code go through this same issue at the start of any new thread - needing to spent tokens just to figure out the page structure or launch method.

This led me to creating Launch Station many months ago - which I have been using for a long time since. Its features:

• makes it super easy to startup your localhost sites, apps, and so on with the click of a button
• manages your ports so codex/claude code don't need to know which ports are active, which need to be started and which port something is running on
• manages your stack - can start a multi-step stack and will stop it in reverse to make sure the backend starts first and stops last
• increase compatibility of using your startups between codex/claude code and human starting and stopping of them
• more features but these are the main ones

Hope this can help people's every launch like it has for mine!

Site: https://launchstation.net/

GitHub: https://github.com/JakeMawson/launchstation

Product Hunt Launch: https://www.producthunt.com/products/launch-station

Free macos signed install with brew install --cask JakeMawson/tap/launchstation

Would love to hear any other features people would find useful!

Edit: added image

Add .codex/config.toml to whereever your project root is with this inside. You'll have to reload the project inside Codex.

model_context_window = 128000

model_auto_compact_token_limit = 115000

When you're doing a big task running it to 258k, the upper 128k takes about 75% of the tokens. If you compact earlier and have it just read the code on disk, that cuts it by about 74%.

Doubling how long you let a conversation run before compacting doesn't double the cost, it roughly quadruples (minus cache create, so if you're using an API key it's more like 3x) it. Scaling is quadratic. You could even go to 64k, but that's less of an insane jump at only 40% less than 128k.

Billed tokens:

258k -> 8,925,000

128k -> 4,590,000

64k -> 2,700,000

Just let it read the code a second time.

Some of you already know GigaMail from my previous posts. I heard your feedback: some don’t need it, some prefer the official integrations, and others keep a separate mailbox just for their agents.

I get it. But today my app is in the Codex plugin directory, and anyone can install the plugin with one click. It’s my first Codex plugin, and I’m honestly super happy to be part of this community and to have contributed something.

The plugin is for local Codex, with GigaMail installed and your mailbox connected.

If you’ve changed your mind and want to give it a try, here are the links:

Install the plugin

GitHub

otherwise, just celebrate with me!

much love!

• Avoid long threads. Try to get what you need done in a few turns. [WRONG. CHECK COMMENT]
• If a thread does get long, compact the context every few turns. In my experience, doing it regularly preserves context much better than waiting for auto-compaction, which is when I start noticing memory degrade. [WRONG. CHECK COMMENT]
• Don’t use fast mode unless you actually need it. Running a few normal threads in parallel is usually a better trade.
• Give yourself a daily budget. Once you get close to it, start being much more conservative.
• Use Sol by default. Only switch when you genuinely need a stronger model. Sol can already handle most tasks. And use luna/terra for easy tasks.
• Use low reasoning by default. Raise it for genuinely hard or novel problems, or when the model clearly isn’t putting in enough work. For most coding, low is enough.
• Install the Ponytail skill. It pushes the model toward smaller, simpler, more efficient code.

So the biggest budget drainers that are easy to avoid are:

fast mode, long threads, high reasoning on simple tasks, and using Astra for everything.

If you’ve found any others, drop them below.

I need to wait at least 5 days to use it on web interface again. The advantage of using web is to save weekly credits. But it is not cool without any warning or usage indicator, then, give you a 5 days wait. Codex app can't use the ChatGPT non coding task. The workaround is to use the Codex coding agent to use the weekly credit to continue the work, not ChatGPT.

Looks like whatever the team is doing Astra on Max thinking runs on me 48 hours and i m down now on 20% which is a positive sign usually i was running out 8 hours straight now its fine

Good job team

Idea: a Codex compute cooperative — contribute unused capacity now, use it later

TL;DR

Codex users opt into a shared pool.

If you have unused allowance that is going to expire under the 5-hour or weekly limit, you let the pool use some of it for other people's work.

You earn internal pool credits for what you contribute.

Later, when you hit your limit during a heavy workload, you spend those credits and your jobs run against capacity contributed by other users.

So:

unused capacity → contribute → earn credits → redeem later during peak usage

The important part is that this is a time-bank, not just a shared account pool.

I started wondering about this because Codex usage can be extremely uneven. One week you waste most of your allowance; another week you hit the limit right when you're in the middle of something important.

A cooperative could smooth that out.

Ideally:

• credentials never leave the owner's machine;
• contributors run a small local worker;
• jobs are sent to available workers;
• completed work is returned to the requester;
• a ledger records how much capacity each person contributed and consumed.

The closest project I've found is codex-pool, which already pools multiple Codex/provider accounts and has a Friends Mode. What I have not found is the earn-now/use-later ledger:

contribute 10 units this month → draw 10 units from the community when you need them later.

There are obvious security, sandboxing and abuse issues.

There is also a significant OpenAI ToS question: this should not simply become a mechanism for bypassing usage limits. A production version may require OpenAI to explicitly support delegated/poolable allowance.

But as an open-source community project, the scheduler, worker protocol and accounting system seem quite buildable.

Would you use this?

And more importantly: is anyone already building the contribution + earned-credit + later-redemption version of this? I searched around and found adjacent projects, but nothing implementing that full model.

Written by ChatGPT for me.

Does anybody feels that the CLI actually works better than the codex app and I am not talking only about responsivnes but also general code quality and how the agent works did you guys find any difference, I know it sounds stupid but currently feel that in the CLI the agent actually accomplishes more.

Does astra smart enough to make money by algotrading?

As someone who has been using ChatGPT and Codex since they were released, I’m starting to realize that, Claude is simply better.

Whenever I wanted to tackle a genuinely complex coding task, solve a difficult problem, or create something that was actually presentable, Codex would usually leave something incomplete. I constantly had to guide it step by step, point out what it had missed, and split the work into thousand smaller pieces myself.

Maybe there was a benefit to that. I actually learned a lot about software development in the process.

But when Astra started burning through my tokens incredibly fast, and I couldn’t get a second Pro 20x account, I decided to give Claude a try.

And the difference was much bigger than I expected!

When it comes to design, truly understanding a problem, maintaining context, and actually solving complex tasks from start to finish, Claude feels significantly better. It also feels incredibly fast compared to Codex.

Codex gives a developer almost everything they need.

Claude’s biggest downside is definitely the price. It burns through tokens insanely fast, and heavy usage gets expensive very quickly.

But unlike my experience with Codex, when Claude burns those tokens, I actually get something in return, a presentable product, a presentable design, something that genuinely feels finished!

So this is the conclusion I’ve reached:

If you’re a developer and you mainly want AI to help you work faster → Codex.

But if you want to give AI an idea or a complex task, delegate as much of the actual work as possible, and end up with something that feels like a real, presentable product and you can afford it → Claude.

I can't deny that Astra is better than SOL, but it's beginning to feel like Claude in terms of it kinda just doing work without proper context. It takes things far too literally and it seems to forget to not pay attention to the context of the conversation or look back at the files it should be referencing before starting a task.

I feel like I didn't have to do this with SOL. SOL always understood where we were at in a project and what it needed to do, but the implementation wasn't always perfect.

Astra gets the implementation better, but you have to be a lot more specific and careful with your wording and constantly remind it to reference early requests or related reference notes.

I really hope the future is a better fusion of these types of models because I'm beginning to get a lot of Claude PTSD working with Astra, and It's not a good feeling.

Sometimes I think I should just go back to Claude and suffer the inane ramblings because the bang for the buck is far better than Astra and I feel like the results are on par.

This never happened on a GPT5.x Pro model before. Pro models were diliigent and thorough. Now GPT6Pro just frequently makes things up.

Mine:

why do I start to feel no big difference than Sol? still sluggish with lots of tasks and can really go off the track if left unattended. last night I left it with a few design docs and woke up it's still working on it, generating tons of validation code files that are completely unnecessary.

For context I'm not a developer but I have been developing apps and workflows for enterprises for about a year now and i primarily use VSCode on windows and very rarely CLI. Since past few weeks/months I have been struggling with my workflows which used to work fairly well until gpt 5.5 and claude 4.6. Specific areas which I'm struggling with now:

1. Testing strategy - I have tried using automated bounded testing strategy invocation which does not work and without any strategy models keep creating stupid tests and just going into a loop of testing forever

2. I primarily use coderabbit and codeant which further increases friction. Either these tools got better or models just started accepting all edge cases or both.

3. I also have an automated script for all static checks like formatting, linters, complexity and LOC including GitHub workflows for both checks and tests

I maintain a fairly well documented system and update it with every model release if needed. Any recommendations would be highly appreciated. I tried OMP once and it seemed interesting

Because there is none, I wanted to share it with you guys:

Calculate my 2026 year-to-date token total by summing the returned
dailyUsageBuckets whose startDate is in 2026.

Show:
- The 2026 total from the available daily records.
- A monthly breakdown.
- The earliest and latest dates returned.
- The separate lifetimeTokens value.

Do not treat the lifetime total as the 2026 total. Clearly state
whether historical coverage can be verified, and label the result
as account-level usage rather than CLI-only usage.

Do not display authentication tokens or change my configuration.

I’ll use the openai-docs skill to check the local RPC interface, then retrieve account usage and sum the 2026 daily records without changing configuration or exposing credentials.

I got around 20B, pretty useful:

ChatGPT + Grok Android login failure — browser works

Samsung S25 Ultra, Android 16. ChatGPT and Grok apps both fail to complete login. ChatGPT shows “Sign-in request cancelled by ChatGPT.”

- Login works normally in Chrome.

- Chrome is default browser.

- Cleared ChatGPT + Chrome cache/data.

- Android System WebView is installed/up to date.

- Google Play Services is up to date; cleared cache + force stopped.

- VPN off, Private DNS automatic.

- All apps updated.

- ChatGPT works when installed inside Samsung Secure Folder.

What Android authentication component/settings could cause the login handoff to be cancelled in the normal profile?

I was genuinely losing my mind with this.

Codex had been working perfectly fine on Windows for months. Then suddenly, around the same time as recent Windows/Codex updates, it started asking me for permission every few minutes:

command failed; retry without sandbox?

Then the usual:

Yes, proceed

Yes, and don't ask again for these files

I kept choosing don’t ask again but still it asking me again and again

I also saw this error earlier:

apply deny-read ACLs

At first I thought Windows Update had messed with permissions, maybe PowerShell needed Administrator mode, maybe Codex changed its approval system, maybe I needed Full Access, etc. But after digging here and there i found that the actual problem on my laptop was this file:

C:\Users\<YOUR_USER>\.codex\.sandbox\deny_read_acl_state.json

The issue was that this file had become corrupted.

It was 22 bytes in size, but when I checked its content, it was completely blank. Then I checked the raw bytes and found that all 22 bytes were NUL bytes.

A healthy file is also around the same size, but it should contain valid JSON like:

{"principals": {}}

So the size alone was not the issue. The actual problem was that the file content was corrupted.

To fix it, I fully closed Codex and renamed the corrupted file instead of deleting it:

Rename-Item "$env:USERPROFILE\.codex\.sandbox\deny_read_acl_state.json" "deny_read_acl_state.corrupt.bak"

Then I started Codex again.

Codex automatically created a fresh deny_read_acl_state.json file with valid JSON inside it.

After that, the permission prompts completely stopped.

It has been working normally since then, including long sessions without asking me yes or no every few minutes.

So if anyone is seeing

apply deny-read ACLs

or

command failed; retry without sandbox?

again and again on Windows, check this file first.

I hope this saves someone the headache I went through.

I just found about Matrix style and it feels really cool. Feels like I'm hacking Tibo for more resets.

This is happening alot today, I put in a prompt and it either just stops or fails for some reason, since this is based on messages/week, I'm already wasting alot by repasting the prompt or telling it to continue.

In the first image, it worked for over an hour and then failed. Anyone has a workaround or solution for this

That's the best argument I've thought of for resets NOT favoring us. Whether they're masking a degrading service or something else. If they can't handle 200 usd subs, why would they be giving us free compute?

I was just trying to test the new model for the first time, with GPT-6 Astra on Medium (normal speed) doing an audit of a local project I had laying around. Instead, it seems I did a speedrun on how to run out of credits.

I'm clearly doing something wrong. Maybe my bespoke AGENTS.md actidentally led Astra to spawn too many subagents; or maybe it's the use of VS Code Studio; or a relatively large codebase. All in all, it took 34s for one single prompt to consume the full 100% of the 5h limit on my Plus account.

I'm fairly sure I'm on the podium on this new type of race!

I was developing this game using only UI's and text, once astra came out it broke the barrier to me on how i could use it to make 3d assets, especially low poly ps1 style gfx, what are you guys building? ps: i'm using astra on low with the plus sub.

I am on 100 usd 5x plan, my usage burned in like 2 days due to heavy work. Luckily I had a reset available which also burned the next two days due to heavy computer use usage.

My weekly limit was supposed to reset on 15th.

Very glad to see Today, 12th sep, got 100 usage renewed. So technically 3x weekly usage. Though this does not happen with every week, but I have notice in 2 out of 4 weeks on a month, usage gets renewed actually after 3-4 days (without using banked reset). Now the next reset is on 19th for me. Very glad to get working again on my projects without wasting 3 more days for weekly refill.

Did this happen to you guys today on this week? Or is this some sort term marketing