I've been spending way too much time hunting down custom skills, prompts, and MCP servers for AI coding tools, then manually setting up SKILL.md files or configuring local binaries.

To make this easier, I built OpenHub, a terminal app for discovering and installing AI agent skills and tools from one place.

What it does:

• Search indexed skills and repositories.
• Export prompt/rule-based skills as a SKILL.md file into your current workspace with one command.
• Install skills that require local binaries or MCP servers.
• Keyboard-driven terminal interface for searching, exporting, installing, and copying.

Install:

pipx install git+https://github.com/24KaratAu/openhub.git

Run:

openhub

GitHub: https://github.com/24KaratAu/openhub

I built this to scratch my own itch, but figured others might find it useful too. It's open source, and I'd love any feedback, bug reports, feature requests, or contributions.

I connect Github but without any effect? Any ideas?

I normally use the Go subscription, but I hit my weekly limit. During that time I only used DeepSeek V4 Pro and DeepSeek V4 Flash.

So I added $10 to my Zen balance, again using only V4 Pro and V4 Flash, but the credits were gone surprisingly fast.

Is this expected behavior? Has anyone else experienced this? I wasn't using GPT, Claude, or any of the more expensive models, just DeepSeek V4 Pro and Flash the entire time.

For some reason i simply can't find where to configure MCP servers from in this new ui

Earlier it were a simple text at top upon clicking it showed which MCP servers are chive and shi.

Now it's just nowhere to be found.

Also why is the usage limit all over the place? It shows user limit hit and I can simply send another prompt and it starts working again for some time. Either hit limit and stop working or just work bruv 😭

Subscriptions like Claude and Codex are currently heavily nerfed, and the companies behind them have never been very transparent about usage limits.

Whenever I look up whether OpenCode Zen is worth it, people usually say that subscriptions offer better value. But with the recent changes and tighter limits on those subscriptions, has Zen become a better option?

I’m currently subscribed to Codex and OpenCode Go. This is my first time using OpenCode Go, and I burned through 96% of my weekly allowance very quickly because of K3 and GLM-4.6 (beginner’s mistake I guess). I also occasionally add credits to my DeepSeek API account.

Codex used to be my main tool, but lately it has been letting me down.

Also... tips for the best cost/value models for Go and Zen?

and it has /plan-mode too

Which gives you more usage on MiMo models?

I like the new version except the session tabs being at the top. Previous version had them on the left is much easier to reach and glance.

I know we can toggle to enable the old layout, but we lose the new features like "open in" which is very useful.

Also is there any markdown viewer plugin for Opencode Desktop?

"You have insufficient permissions for this operation. Missing scopes: api.responses.write. Check that you have the correct role in your organization (Reader, Writer, Owner) and project (Member, Owner), and if you're using a restricted API key, that it has the necessary scopes."

The problem is that I'm using my monthly ChatGPT Plus subscription, not an API key.

I've already tried logging back in and clearing the cache but still nothing. Does anyone have any ideas?

Hej!

Jag fattar inget, hur använder jag Qwen 3.8 max i opencode?

Skulle någon kunna hjälpa mig och är den så bra som alla säger?

I just watched a video where some dude added a model to a provider, tested it, and then later added another model to the same provider.

I can't seem to find that option anywhere.

I know that when you first set up a provider, you can enter multiple models. But after the provider has already been created, I don't see any way to reopen that model list and add more. In the video, he simply opened the window with the provider again, the previously added models were still there, and then added another one.

What am I missing? Is this an older feature that was removed or is there another way to edit the models for an existing provider, in the gui...

Do you know why it's not implemented yet?

been working on a side project and keep hitting this wall where i know a piece of code is kind of messy/not ideal but it works, and i have to decide whether to stop and clean it up now or just keep moving and deal with it later.

curious how people who've been doing this longer actually make that call in practice. is there some rule of thumb (like "if i'll touch this file again soon, clean it now") or is it more just a gut feeling that builds with experience? also curious if this changes a lot depending on solo projects vs working with a team

not looking for a "it depends" answer lol, more curious about the actual heuristics people use day to day

I wanted my AI coding assistant to always follow a specific ethical framework, so I figured out how to embed my custom guidelines into every interaction with opencode. Here's how I did it—and how you can too.

### The Problem
I have a set of principles (based on 1 Corinthians 13) that I want all my AI interactions to follow—patience, kindness, humility, etc. But manually pasting these into every prompt is tedious and error-prone.

### The Solution
OpenCode has a built-in `instructions` feature that lets you automatically include custom guidance in **every** LLM interaction. Here's the step-by-step:

1. **Create your guidance file** (e.g., `agape-guidance.md`):
   ```markdown
   # System Directive – Agape-Aligned Assistance
   In all interactions, embody the spirit of 1 Corinthians 13:
   - Be patient: Give clear, step-by-step explanations...
   - Be kind: Use gentle, respectful language...
   - [Your full principles here]
   ```

2. **Add it to your OpenCode config** (`~/.config/opencode/opencode.json`):
   ```json
   {
   "$schema": "https://opencode.ai/config.json",
   "instructions": ["~/.config/opencode/agape-guidance.md"]
   }
   ```

3. **Done!** OpenCode now automatically includes your guidance in every prompt.

### Why This Works
- **Global application**: Affects all projects and interactions
- **Non-intrusive**: Doesn't modify OpenCode's core—just adds your layer
- **Flexible**: Use any text file (`.md`, `.txt`, etc.)
- **Official feature**: Uses OpenCode's [documented `instructions` config](https://opencode.ai/docs/config#instructions)

### Customization Ideas
- **Team-wide ethics**: Place the file in a shared location for your org
- **Project-specific**: Override with a local `opencode.json`
- **Multiple files**: Reference an array of guidance files

### My Experience
Since implementing this, my AI interactions feel more aligned with my values. The assistant naturally adopts the tone and approach I want, without me having to remind it every time.

**Question for the community:**
What ethical frameworks or guidelines do you wish your AI tools followed by default? Would you use something like this?

*(Cross-posting this because I think it's a useful pattern for anyone wanting more control over AI behavior. Not affiliated with OpenCode—just a happy user.)*

I need the 5$ for my opencode account 😇 dollahttps://opencode.ai/go?ref=ESVD7EK78S

OpenCode Go says models are hosted in the US, EU, and Singapore but not which region serves kimi k3.

So how are people concluding “it’s in Europe” or “China has access”?
From the client I don’t see a way to tell:
- Cloudflare edge ≠ GPU location
- latency is a weak signal
- Moonshot being a Chinese company ≠ servers in China
- open weights being unavailable is a separate issue (Go is an API gateway)

“China access” like some comments say...
- Inference in mainland China?
- Or a Chinese upstream (e.g. Moonshot) can still see prompts/logs even if GPUs are in US/EU/SG?

Update of my earlier post:

After mostly positive feedback, the tool now has about 500 legit users. However, I spent quite some time over the past few weeks fending off 300+ bot accounts trying to exploit the system in any way they could find.

The good news: this helped me make the entire system (api, library etc) a lot more robust and was definitely a great test now that the tool is in prod with real users.

Made me realize that certain things you cannot mock/test fully until the first users show up (especially the ones that want to game your system), no matter how complete your test coverage is.

Most spammers came from OpenCode installs for some reason, but legit users/installs are also mostly from OpenCode (>50%, despite being only one of four implementations).

OpenCode users (300+) have also earned the most, compared to Claude Code and Hermes, which I found interesting. Maybe overall coding time spent per day on OpenCode is higher per user than the other harnesses?

Most feedback I received via DMs was great and payouts are working with Stripe. Still working on adding other methods and improving the tool every day.

Thanks for all the support 🙏

I kept making the same decision in coding sessions: should Sol handle this, should Terra implement it, or is this inexpensive read-only work for Luna?

I turned that decision into an MIT-licensed OpenCode project called Open Harness.

Open Harness automatically routes coding work between GPT-5.6 Sol, Terra, and Luna inside OpenCode, with optional Kimi K3 agents through OpenCode Go.

You give /harness one normal task. Open Harness then chooses a role automatically:

• Sol for architecture, difficult judgment, review, and escalation

• Terra for implementation, debugging, tests, and repository research

• Luna for classification, extraction, summaries, and other inexpensive read-only work

The goal is not to use every model on every task. It is to select the smallest appropriate worker without making the user manually choose a model and reasoning level each time.

Open Harness discovers the available model IDs at runtime and installs the routing command, agents, and permissions while leaving OpenCode in charge of sessions and credentials.

This is an early developer preview, and I still use it with supervision. The public routing path is policy and instruction based; it is not an OS sandbox.

Repo: https://github.com/cwklurks/open-harness

I would really appreciate feedback from people who use multiple models in OpenCode: which routing choices should become automatic, and where would you still want manual control?

Is there any setting to use a default agent with plan and another default for build?
I see Big Pickle on each time and the first thing I do is change that.

Hello guys, I am facing this issue after the recent OpenCode update. Can somebody help me? I haven’t even used it much—just 10k tokens. Not just on Big Pickle, every mode is giving me this error.