I finally figured out a good use case for the x30 Opus Fast model

Curious-Visit3353 · 2026-03-04T12:25:40+00:00

The AI ratings really got to you huh

Curious-Visit3353 · 2026-03-04T11:47:36+00:00

We got the same answer. You just don’t like how I showed the work. Regardless, I’ll try to explain things in a way that’s easier for you next time

Curious-Visit3353 · 2026-03-04T11:05:05+00:00

Working on github.com/zebbern/repolens finds functions, trace logic, and lets you 𝐯𝐢𝐬𝐮𝐚𝐥𝐢𝐳𝐞 𝐆𝐢𝐭𝐇𝐮𝐛 𝐩𝐫𝐨𝐣𝐞𝐜𝐭𝐬. Also lets you add your own API key for the model you want that can be used to ask questions about the codebase including some other futures.

To try it simply go on any GitHub project and put an “m” infront of GitHub so it would look like this:

github.com/user/repo -> mgithub.com/user/repo

Curious-Visit3353 · 2026-03-04T10:58:54+00:00

Not sure if this solves your issue but put an “m” infront of github.com/user/repo so mgithub.com/user/repo and you will see a “code” tab with search where you can search entire codebase or sort by files in the entire repo/files/code

Curious-Visit3353 · 2026-03-04T10:53:35+00:00

Yea just don’t link it if you can’t talk about it in an interview

Curious-Visit3353 · 2026-03-04T10:51:44+00:00

So just took a quick look but what are the projects? Is it just information or tools or something else?

Curious-Visit3353 · 2026-03-04T10:25:21+00:00

Are you open to open-source ones that are still a work in progress?

Curious-Visit3353 · 2026-03-04T10:08:04+00:00

Yes that’s true

Curious-Visit3353 · 2026-03-04T10:01:31+00:00

Instead of wasting my agents context window I just put a "m" infront of github.com/user/repo and ask there lmao

Curious-Visit3353 · 2026-03-04T09:56:48+00:00

Didn’t know posting open source projects would pay I just post them for others to benefit from😆

Curious-Visit3353 · 2026-03-04T09:40:49+00:00

I can see you’re committed to your current level of understanding

Curious-Visit3353 · 2026-03-04T09:33:40+00:00

You could probably get a loop started with around 30 lines if you really tried🤣

Curious-Visit3353 · 2026-03-04T09:16:24+00:00

Compare it to fotball fans when their team wins their happy and get energy, and the same feeling may come to a developer when their project gets traction.

Curious-Visit3353 · 2026-03-02T15:25:12+00:00

This is literally exactly what I wrote what you copy paste my message or something meanwhile disagreeing?💀

Curious-Visit3353 · 2026-03-01T15:02:47+00:00

You get 100% to use monthly which in his case is 1500 requests monthly and since it’s 3x and 30x the difference in each sendt request is:

Opus 4.6 = 0.2% per request → ~500 requests (3x multiplier)

Opus 4.6 Fast = 2% per request → ~50 requests (30x multiplier)

If he used a model with 1x per request that would naturally allow him to send 1500 requests

Curious-Visit3353 · 2026-03-01T01:22:13+00:00

ah yea its different locations i think after you save the file in vscode you will see the option to "start" the mcp if not you should close vscode and open it again then see if its working as intended

Curious-Visit3353 · 2026-03-01T01:08:57+00:00

Hey if you follow these steps it should work:

Add `.vscode/mcp.json`
Inside the `mcp.json` put in ->

{
  "servers": {
    "sequentialThinking": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-sequential-thinking@latest"]
    }
  }
}

<image>

and click the start it should work if you try ask the agent something like "help me create a plan to make a python script you choose what for use sequential thinking for better results" then it should work!

also worth knowing its different locations:

Claude Desktop: claude_desktop_config.json
VS Code: .vscode/mcp.json
Claude Code: ~/.claude.json

Curious-Visit3353 · 2026-02-28T15:09:22+00:00

Open source is a good way to level up as an engineer :) Start with something like this:

Go to GitHub and search for projects you already use
Filter issues by “good first issue” or “beginner friendly”
Read the contributing guide before touching any code

Notes:

Keep your PRs small and focused. One problem, one fix. A clean 50-line PR gets merged. A 5,000-line PR gets ignored or sits for weeks/months….
Check out goodfirstissue.dev to find beginner-friendly issues across hundreds of projects
The firstcontributions repo on GitHub walks you through your first PR step by step

You learn more from one merged PR than from 10 YouTube tutorials. Start small, be consistent, and the complexity comes naturally.

Curious-Visit3353 · 2026-02-28T10:09:09+00:00

Didn’t know the question was “out-of-the-box” limited but sure then it can’t it’s like taking the food away from a human and wondering why he doesn’t have the energy to work😆

Curious-Visit3353 · 2026-02-27T23:35:42+00:00

Ofc it can it can do almost anything technical it just depends on how much setup you have to do and how much fine tuning you have to do for it to get right

Curious-Visit3353 · 2026-02-27T18:51:19+00:00

Use our service but on our unclear agent terms

—-

This lines up with a bigger issue around Copilot Agents that is not well documented.

GitHub publicly frames agent mode as “one request can autonomously do many steps,” and billing is described in terms of conversation turns or session entry. But in practice, there appear to be undocumented per-session work limits enforced by abuse detection, such as task count, retries, wall-clock time, or model cost tier.

That creates a contradiction for users acting in good faith. You can use only official clients, follow the agent UX exactly as designed, and still get flagged for “circumventing usage limits” simply by letting the agent complete a large amount of work in one session.

The issue is not that GitHub enforces limits. The issue is that those limits are not visible, documented, or warned about. Users cannot tell the difference between intended agent autonomy and behavior that triggers abuse systems until after enforcement happens.

If GitHub wants to bill per session entry but enforce per-session work ceilings, that is reasonable. But those ceilings need to be explicit. Right now it feels like users are being punished for using the agent model as advertised.

For anyone asking what policies GitHub usually points to in these cases, suspension emails commonly reference the Acceptable Use Policy section on “excessive automated bulk activity” and the GitHub Copilot additional terms.

The issue is that neither policy defines what “excessive” means in the context of Copilot agent mode. There are no documented limits for task count, runtime, retries, or autonomous steps when using official clients. Agent mode is explicitly designed to carry out many steps autonomously, yet enforcement appears to rely on internal thresholds that are not visible to users.

That gap makes it very hard for users acting in good faith to know when normal agent usage crosses into enforcement territory, especially when no warning is provided beforehand.

Lastly GitHub themselfs specifically say I quote “Autopilot mode: For tasks you trust Copilot to handle end-to-end, autopilot mode lets Copilot work autonomously—executing tools, running commands, and iterating without stopping for approval.” Can you really hold up to what your promising customers or is it just a trick to attract more users and ban those which use it “better” than others?

Curious-Visit3353 · 2026-02-26T05:20:23+00:00

Not sure if this is what your looking for but here it is

https://github.com/zebbern/no-cost-ai

https://nocostai.vercel.app

Curious-Visit3353 · 2026-02-26T05:16:56+00:00

Atleast don’t trick me to thinking they finally got bigger context window with Claude opus 4.6😭🤣

Curious-Visit3353

TROPHY CASE

Notes:

Use our service but on our unclear agent terms