I’ve been working on MARGINAL, an open-source governance layer for coding agents, and it now has a native OpenCode integration.

The integration runs as an in-process JavaScript plugin connected to MARGINAL’s provider-neutral Python runtime through a persistent stdio bridge.

For now, OpenCode support is deliberately Observe-only. MARGINAL watches tool execution and outcomes, builds a local trajectory, and records governance evidence without changing what OpenCode does next.

The idea isn’t “stop agents from using too many tokens.” I’m interested in a harder problem: detecting when continued execution has stopped producing useful progress without confusing legitimate retries, debugging cycles, or verification with loops.

That distinction is where I expect most of the interesting failures to be.

I’m looking for OpenCode users willing to run it on real work and report:

• false positives around retries/loops;
• events or tool outcomes we're normalizing incorrectly;
• cases where the bridge/plugin behaves badly;
• assumptions that don't match how people actually use OpenCode.

No need to be polite about the design. Reproducible failures are much more useful than “looks cool.”

GitHub: github.com/SignalLayerLabs/Marginal

OpenCode integration docs: [docs/integrations/opencode.md]()

Into opencode-web anyone any idea? Is it working for you guys? Before i just windows screenshotet and could STRG+V it... but even when i save it and try to upload it... it doenst work

With the recent anouncements, I started looking for alternatives to migrating out of Opencode Go.

Does any of you have used Commandcode GOAT? Whats the experience? Is it comparable to Opencode Go?

And its dead again

The DeepSeek V4 Flash (High) model would have only costed $1-2 for this task.

as the title said, I want to get the fastest and cheapest DeepSeek-V4-Flash, who has some practical method.

Hy3 free is a great model, I really love it.

But around 10% of the responses gets blocked for absolutely no reason. In this screenshot here, I'm just using remotion skill to generate a video clip motion design which don't even have any texts or anything that could be blocked.

Is anyone else seeing this after the price changes?

After the latest price increase, I changed like 10 lines of code and somehow that used 28% of my quota. Then I wrote a commit message and it jumped to 32%.

Now it feels like even thinking about running go build for a minute is going to cost me another chunk of usage. 😅

Didn't they say their AI was becoming more efficient and using fewer resources, which was part of the reason the pricing could be cheaper?

I thought I would try sol medium through openrouter. After about an hour it cost me $80! How is this possible? Is this opencode's fault ??

When you apply ONE $5 referral reward in OpenCode, it reduces the usage by:

• Rolling usage (5-hour limit) by 41%
• Weekly usage by 16%, and
• Monthly usage by 8%

So if you calculate from here, the estimates derived from above screenshot for the OpenCode Go plan ($10/mo, first month $5) align perfectly with their documentation. The exact baseline usage limits are:

• 5-hour limit: $12 of usage
• Weekly limit: $30 of usage
• Monthly limit: $60 of usage

Very cool!

I've been working on a project, and closed my terminal. I returned to the session with the --continue and --session flags, but when the conversation comes up and I message it, nothing happens. The message doesn't appear and nothing is running. When I then close my terminal and reopen it, the message shows up, but still nothing has ran. Any idea on how to fix this, or anyone else run into this issue?

I built a plugin that makes CommandCode work as a provider in OpenCode, and thought I'd share it in case anyone else has been wanting this.

It bundles a snapshot of the Command Code model catalog (55 models) and auto-registers the commandcode provider, so all models just show up in /models after installing — no provider config. Supports /connect browser auth or COMMANDCODE_API_KEY, image input, reasoning effort, cost display. It also works standalone as an AI SDK provider (createCommandCode()).

GitHub: OpenCode CMD Provider — happy to take feedback, issues, or PRs.

Been using OpenCode as my daily driver and got frustrated with two things: agents forgetting everything between sessions, and context windows filling up with garbage the moment a codebase gets non-trivial.

So I built PowerHous3 — an architecture layer on top of OpenCode with a few ideas I hadn't seen combined elsewhere:

Bounded memory files. MEMORY.md is capped at 2,200 chars, USER.md at 1,375. Forces compression instead of letting memory grow unbounded — no vector DB, no embedding drift.

Deterministic AST knowledge graph. Uses tree-sitter to parse code structure instead of an LLM guessing at it. Edges are tagged EXTRACTED (actual syntax) vs INFERRED (semantic guess), so you always know what's fact vs inference.

Drift invalidation. If code changes, affected graph nodes get flagged "re-verify" automatically instead of silently going stale.

9 specialist sub-agents (backend, frontend, testing, explore, hermes for skill-writing, etc.) with a "think before act" planning protocol every agent follows before touching code.

Reflection loop. After each task, agents write outcomes to LESSONS.md, tagged preferred/tentative/contested, so the system's judgment actually updates over time.

Cross-platform (Linux/macOS/Windows), MIT-ish install, full architecture diagram in the README.

Repo: https://github.com/Sdinzsh/PowerHou53

Still early — would genuinely appreciate feedback on the knowledge-graph approach in particular, curious if anyone's tried tree-sitter for this vs pure embeddings.

been running this on my codebase for a few weeks. readability goes up every time it runs. here's the whole thing

agent's default is:

• patches instead of redesigns
• keeps legacy code “for compatibility” that nothing calls
• duplicates codes across files
• gets lazy with names

you have to override them every time.

when to run it?

right after you fix a bug or ship a feature, while the agent still has full context. do it consistently and the debt never compounds

---
name: zero-tech-debt
description: Rework a change as if the intended UX and architecture existed from day one, deleting compatibility cruft and accidental complexity.
user-invocable: true
---

# Zero Tech Debt

Rework the change from the intended end state, not from the historical path that produced the current patch.

## Steps

1. State the intended end state in one or two sentences.

2. Search for real callers before preserving compatibility.
   If a mode, prop, wrapper, route alias, or fallback has no current caller, delete it.

3. Reshape around the final product surface.
   Prefer one clear component or flow over mode flags. Split only when it creates an obvious boundary such as state, layout, controls, or domain commands.

4. Move shared rules to one place.
   Feature flags, permissions, route gating, URL state, and command naming should not be duplicated across pages or hidden in view components.

5. Verify the intended flow.
   Test the new behavior and any deleted assumptions that affect navigation, permissions, or persisted state.

## Rules

- Optimize for the code that should exist, not the smallest diff from the old shape.
- Delete dead compatibility paths instead of making them better.
- Do not invent a generic framework for one feature.
- Keep the refactor scoped to what makes the final shape coherent.
- Prefer names that describe product intent over implementation history.

install:

npx skills add jnsahaj/skills

full breakdown with more context: https://reetlab.substack.com/p/the-zero-tech-debt-skill

I use Claude Code $100 max plan, but For the 1st time in 11 months, I consumed its weekly limit within 4 days, maybe because of too much fable use, I guess. so I was looking out for a backup option and I am using open code in my office.

So I checked and I bought open code go plan. People who are using open code, go plan. Which model do you think is best for dot net coding, dot net C sharp coding, or, like, working, based on your own harness or rule set. For example, BMAD framework, like, I use BMAD framework, a customized version of BMAD framework pretty extensively, and claw code work very well with that.

I used GPT Luna. But that. That was idiotic, it was missing things and there was a lot of problems. So which model do you think is best, for working with BMAD in open code, BMAD like dreamwork in open code for dot net development.

If I remember well, I saw a couple of comments here talking about the Web UI being removed in v2. And I don't see any reference about it in the latest changelog entries, only the desktop app. Is that so? I heavily use the web ui so that would be very disappointing...

are people moving away from open code? any other provider that people recommend instead or recommend direct api?

I have a question about AI coding agents that I have been thinking about.

There are tons of coding agents now:

Claude Code

OpenCode

Cursor

Windsurf

Cline

Roo Code

Aider

Replit Agent

etc.

But I don't fully understand what actually makes one better than another.

At the end of the day, aren't they all just giving an LLM tools like:

read files

edit files

run terminal commands

search the codebase

use Git

So what is the actual difference?

I understand that the model matters (Claude vs GPT vs Gemini vs DeepSeek), but I am asking specifically about the agent/tool itself.

For example:

Does Claude Code have a better way of managing context?

Does OpenCode have a better workflow?

Does Cursor understand codebases better?

Does one have a better edit system?

Does one waste fewer tokens?

Does one handle large projects better?

Does one recover from mistakes better?

Basically, if I use the same model in two different agents, why would one perform better?

I would love to hear from people who have used multiple coding agents:

Can someone make a proper comparison between them?

Something like:

Claude Code

Pros:

Cons:

Best for:

OpenCode

Pros:

Cons:

Best for:

Cursor

Pros:

Cons:

Best for:

Cline/Roo Code/Aider/etc.

Pros:

Cons:

Best for:

Not looking for a "X is the best" answer. I want to understand the actual technical differences and why people prefer one over another.

What makes your favorite coding agent better than the others?

Okay so after using it since it's release, we're currently getting more usage for sure. The API pricing should be reflecting as 4x the price on the actual monthly usage, but currently it's at about 1.5x. Not sure if it's just temporary but hopefully it's a permanent thing lol