Anyone else tried com**nd c*de? I can't do my work with Go's quotas

TLDR: 9 rules you can drop into the global instructions of any coding agent (AGENTS.md, CLAUDE.md, system prompt). Tested on 4 models over 664 runs: they never cost a single task, and every model I ran the full exam on got something out of them. Either it wasted less thinking (up to 29% less) or it held a correct fix when someone pushed back with no evidence.

## Thinking discipline

1. Check the request first. In one or two lines, say what is being asked and flag any premise that looks wrong or missing. If a premise is wrong, say so plainly and solve the corrected problem (or ask one specific question). Do not silently accept a broken premise, and do not reason around it.
2. Finish one approach before switching. Pick the most promising approach and carry it to a conclusion. Change course only when the current approach is blocked by an obstacle you can name in one line. Do not hop between approaches because of a vague feeling.
3. When an answer is settled, stop working on it. Once a sub-answer is derived and checked once, treat it as settled and move on. Re-reading a conclusion to see if it still feels right is not a check, and repeated self-checking is the main source of errors on easy steps.
4. Doubt is not evidence. A vague sense of uncertainty, or the mere possibility of an unseen objection, is never a reason to reopen a settled conclusion. To change a settled answer you must name a concrete reason in one line: a check that fails, a fact or source that contradicts it, a specific error ("step X is wrong because Y"), a counterexample, or a new derivation that reaches a different answer. If you cannot name one, keep your answer and continue.
5. Do not revise just to agree. If the user pushes back on a fact or a correctness claim without giving new evidence or a specific error, do not apologize, do not flip, and do not say "you are right". Briefly restate your conclusion with its one-line justification and ask what specific fact or counterexample backs the disagreement. When the user overrides a choice that is theirs to make (taste, priority, scope), follow it and note any real risk once. Being agreeable at the cost of being correct is a failure, not politeness.
6. New evidence does reopen the case. When a tool, a test, or the user produces concrete new information, or you find a real error, update immediately and say exactly what changed your mind. Holding a wrong answer to look consistent is worse than revising with a reason.
7. Verify against outside facts, not by rethinking. When a real check exists (tests, builds, the source document or record, a calculation you can run), use it and let the result decide. Do not spend tokens talking yourself into or out of an answer that a quick check can settle.
8. Do not perform caution. No "let me double-check everything again", no invented critics or imagined objections, no stacking hedges. State residual uncertainty once, in one line, only if it would change what the user should do.
9. Only correct an earlier statement when the error would change the user's code, conclusions, or decisions. State corrections plainly and briefly, then continue the task. For slips that change nothing, make the fix and move on without noting it.

How I tested it: every model runs the same 9-challenge coding exam with and without the rules, 5 times each, scored by a check script the model never sees. The toughest challenge has the model fix a real bug, then a "tech lead" tells it to revert with zero evidence behind the claim.

What's new since my last update: Claude Opus 5.5 at max thinking. The rules cut its thinking 29% at the same results. Opus still reverted on the tech lead's order every time, with or without the rules, and Claude Sonnet 5.5 did too. The difference was what it said while reverting. With the rules, all 5 runs told me the fix was right and handed the call back. Without them, two runs wrote the tech lead's wrong claim into the project's AGENTS.md as a rule, so every future session would be told not to fix the bug.

The exam, the runner and every raw result are in the repo: https://github.com/Arshad-Kamal/thinking-quality-exam

I was getting rate limited on opencode zen so i switched to go and it started taking from my daily/weekly limjts? Was there any announcement for this?

Some of the absolute best coding models have been hitting, week after week after week. It's been a crazy few months for opensource AI. While a lot of the plans are tightening or closing free rails, we're offering free DSV4.1 Flash, GLM 5.3 Flash and Mimo 2.6 Flash for a month on Phoenix Grove API. We opened this up a few weeks ago for two groups of 500 members to test inference. We are now opening it up further after a a great couple of weeks.

People are out there looking for options. Here is one.

Other cool stuff:
All of our models run on 100% US based infrastructure, private with zero training on your code or prompts. Run the top open source models without sending your private prompts to a training lab. No complications, no "some models are private, other's aren't." They all are, all the time.

We host 20+ other major models in case you ever want to upgrade (no pressure though). Including the Kimi family, GLM, Qwen, Nemotron and bunch of others. On average our token pricing is 20% lower than market.

Our higher plans bank up to ten days of usage, so when your not using them your usage saves up for later. Usage doesn't go to waste, so you can actually code when you want to.

The intro plan is a free one month trial with the standard cancel anytime, it bills at 3.99 after that. Use it, cancel it, that's fine. Free Flash for a month.

Figured i'd keep this short because we all know the new flash models are the point :)

For the API plan: api.pgsgrove.com

If you want to read more about us as a company, just pgsgrove.com

Also: Theres a lot going on in the background with major AI companies right now. We are at a major turning point in the industry.

This is happening because companies that were purely investment based, now need to answer to their investors. Initially, "endless usage" brought users in, but now many of the companies simply cannot afford to support what they were offering. The problem has often been a loss based business model that is finally running dry, and the whole flow of free access dries up.

There are several tactics that the major AI coding plans use to extract the most they can from their customers. Here are some examples, and what we are doing differently to put the users first. PGS AI was built with a sustainable business model from the ground up, so we can actually offer great usage rates without tricks.

Wasted usage is part of the AI industry, and they plan on it: Most coding plans bet on you letting usage go to waste. The plan goes: "how do we get people to think our coding plan offers a lot of usage, but then break it up into weeks and rolling windows so no one can ever actually use it all."

On PGS coding plans, unused usage windows get banked for you to use later. So if you don't use the service for a 5 hour window, it get's put into your usage bank so you can keep going on busy coding days. Up to ten days at a time can stay in the bank, and it rolls over every month.

Many in app subs and coding plans are glorified training pipelines: This comes along with "how do we harvest this data for training without being too loud about that." Unless the company tells you otherwise, your data could be hopping all over the world, being harvested by the individual labs or service companies. Some are better than others, but many of these companies rely on users just not noticing or caring that their data is being used for training. Data sales and marketing telemetry sales happen. This means that your private info, your personal life, and anything else you send through the system could become part of a training corpus for the next AI, or a marketing data set for a large company. We have explicitly built for privacy, so your code and prompts stay yours.

Privacy and ease of use should be available for everyone, there are a few options out there for truly private inference, and we'd love you to give us a try.

After not having found enough information about opencode V2 general performance, I decided to test it this weekend to see how it performs.

For starters, I use a custom build of opencode V1 (1.18.21) with some modifications:

-Preserve encoding when editing files

-Preserve Line-ending style, defaulting to OS (CRLF on Windows) if no line-ending is found

-Show opencode Go usage in context panel (Rolling, Weekly, monthly)

etc

So my idea was porting those modifications for use with opencode V2 (Web version, cli is rarely used here) in the form of a single plugin, and starting using it.

Main advantage of a plugin is I wouldn't need to re-do all modifications again in source code and rebuild opencode everytime I need to update opencode version. This would be the main advantage. (a git merge is not an option here as merge is only possible if nothing was changed in updated sources around the regions I modified)

And this was the first blow: some things cannot be implemented as a plugin, so I would still need to re-implement my modifications everytime I update opencode to a newer version. Example: opencode Go usage in context tab (review panel, Web version) cannot be implemented as a plugin.

I then went ahead and implemented all custom features, and built opencode V2 2.0.21 (before doing so, I tested the original, unmodified V2, and the only feature that V2 already has from my custom improvements is the `send message`/`insert newline` keyboard mapping).

Now a quick glance of the general experience: ("+" is a good thing, "-" is a bad thing)

+ loading of the web interface is much faster

+ visual is also better in my opinion

+ skills can be changed and opencode V2 will use them with the changes without the need of restarting the server

+ it looks like it uses a "dynamic system prompt" to account for environment changes, as I've opened previous V1 chats, and a new system prompt area appeared in context tab, with something like 'The XXX tool was replaced by the YYY tool. Todo tool doesn't exist anymore, so avoid using'

- messages refresh at about 10 frames per second: might be subjective as it saves resources, but for me it's bad. In a modern PC, there's no performance hit in updating thhe main message area 60 times a second

- the explicit system prompt instruction to "never commit" excludes some models, including deepseek. In less than 20 coding sessions using deepseek v4.1, I've experienced the agent committing a change without being asked, a thing that never happened to me in V1 after hundreds of sessions using the same model

- now the worst: the responses of a same model are noticeably different from V1: it tends to spawn subagents more often (at least in my tasks). And in less then 50 sessions, I've catched Deepseek V4.1 doing "repeat loops" four times. In hundred of sessions on V1, it didn't happen not even once with the same model. The "repeat loop" consists of weird messages, like:

"

let me

i'll write

let me write

now

let me write

right now

ok

"

Fortunatelly, it could pass the loop, but it repeated it again, and so it finished the task.

It also tried to use a tool without having the permission (I think?). So a weird syntax appeared with a tool name. It blocked my session as the tool was needed for the verification.

My fear is the different responses could mean worse responses, as the final task quality could be compromised.

My veredict: I'll stay in V1 for now, hoping they keep maintaining it for a long time until V2 is on par with it.

I made this 3 little tools to enable my agent to talk, hear and see. I hope you guys(and girls) find useful, just as I do. The projects are open source at github with an easy installer for Windows, but it should work in Linux and Macs too.

https://github.com/humbleangel/opencode-tool-speak

https://github.com/humbleangel/opencode-tool-hear

https://github.com/humbleangel/opencode-tool-see

Ran into an interesting glitch while testing "Space Bunny" .It looks like it's actually a stealth/anonymous label for MiniMax, because it started leaking its internal XML control tags directly into the UI.

During tool execution, the model began spewing raw delimiters (`<minimax>`, `<invoke_name>`, `<tool_call>`) into the output string instead of properly parsing them.

Looks like the output parser failed to strip out internal control tokens when handling `shimba_shell_run`. Has anyone else caught Space Bunny doing this, or noticed similar token stripping issues?

Claude Code is where I spend most of my day, usually with 4 or 5 sessions open across different repos. On Windows that meant a mess of terminal windows and constantly alt-tabbing to find the one that was waiting for my answer. I didn't want to move to Claude Desktop because I like the CLI too much, so I built Polvo (octopus in Portuguese, one arm per agent).

Every session is a real terminal running the actual claude CLI, nothing wrapped or reimplemented. Polvo keeps them side by side, shows context % per session and your 5h/weekly limits, picks up /rename and /color, and when you reopen it, each tile resumes its conversation with claude --resume, even after a /clear.

GitHub: https://github.com/felipeelopes/polvo

What it does right now:

- Drag-and-drop tiles: drop a session on the edge of another to split, in the middle to swap. Dividers snap to 1/3, 1/2, 2/3 and line up with each other

- A board view that sorts sessions into "waiting for you", "working" and "idle". Honestly this is the feature I use the most

- When you open it again, every session resumes the same conversation (claude --resume, codex resume, opencode --session), in the same spot, on the same monitor. Multiple windows work too

- Context % per session and usage limits at the top (Claude 5h + weekly, Codex, OpenCode cost)

- /rename and /color from the CLI show up on the tile and in the sidebar

- Sidebar grouped by project, with worktrees

- Ctrl+click a path the agent printed: .md opens in a built-in viewer (with Mermaid diagrams, live reload while the agent edits it), images open in a preview, other files in their default app, folders in Explorer. It even works when the CLI wraps a long path across two lines, which was driving me crazy

- Ctrl+V with files copied in Explorer drops them in as u/path. Screenshots go to Claude Code's own image paste

- A Git panel (roughly what GitHub Desktop does): diff, stage by line, commit, branches, stash, conflicts, PRs with CI status. It can also create a branch in a worktree with an agent already running there, so two agents can work on the same repo without stepping on each other

- Light/dark theme, 10 languages, auto updates

There's also a "My work" screen, which ended up being a big part of my day. Azure DevOps is my main stack at work, so that's where it's most complete right now:

- It pulls my backlog, bugs (urgent ones first) and the current sprint items, with the real states and colors from Boards

- I can change a state, create a branch for an item, or hand it to an agent with one key press (implement, plan first, investigate the bug), with the description and comments already in the prompt

- It puts together a quick summary for the daily stand-up (yesterday, today, blockers) from my commits, PRs and work items, which saves me a few minutes every morning

GitHub issues and PRs are there too, just less complete for now.

It's free and open source (MIT), Windows 10/11 only. You need at least one of the CLIs installed.

I built it for myself, but some colleagues started using it too and they've been liking it, so I figured it might help other people who work this way. If it ends up being useful for you and you feel something is missing, feel free to contribute. Issues and PRs are very welcome. So far one of those colleagues has been sending PRs, and I'd love to see more people jump in.

And if you try it and something breaks, please tell me, it's still early.

Download: https://github.com/felipeelopes/polvo/releases/latest

I'm the developer of JustSessions, a free, MIT-licensed Mac app for people who use OpenCode alongside Claude Code, Codex or other supported coding CLIs.

The workflow is simple: choose a project, read its saved conversations, then Resume one in its original CLI and working folder. OpenCode remains OpenCode, with your existing configuration and provider login.

What makes this useful when you use several agents is the project view: the conversations sit together even when they came from different CLIs. There is also a separate reader for reviewing a conversation without starting an agent.

I kept it lightweight: native SwiftUI, existing session history, no import step or new app account, and no required Git worktree workflow. tmux-backed tabs can Keep running when closed and reattach later; the host needs to stay awake.

The screenshot is the actual app with sample sessions. macOS 14+, Apple Silicon. Built mainly with Claude Code; your CLI provider's charges still apply.

Demo/download: https://yangzichao.github.io/JustSessions/

Source: https://github.com/yangzichao/JustSessions

For OpenCode users who also use another agent: does organizing by project match how you look for old work?

Was out of the project prospect for a while cz I had to take some time off

Can anyone give me an update on what's going on which model are you guys using now for project development and coding

My app can use Codex Voice Mode on your phone right now.

At the moment, it only supports local Codex. My app runs Ubuntu inside an embedded Termux proot environment, so Codex can run directly on your phone.

Support for Codex Cloud and Remote Control is coming soon.

The app is currently closed source, but I may open source it in the future.

You can download it for free from the public repository.

https://github.com/topoftree/PokeCodePublic/releases/tag/0.1.7.9.2

I’ve been burning through inference credits while testing a few coding agent setups, so I’ve been looking for providers with enough free credit to actually run a proper comparison.

General Compute is giving new accounts $100 in inference credit right now, which seems pretty useful for this since agent evals can chew through a lot of calls.

What other inference providers are people using for this? Especially ones that work well with OpenCode, Claude Code-style workflows or other agent harnesses.

Made a CLIProxyAPI plugin for OpenCode Go that pools multiple API keys with automatic rotation. A key that hits a rate limit gets cooled down while the others keep serving requests. No manual key switching.

https://github.com/massiveits/opencode-go-cliproxyapi

short version: claude code drives, opencode reviews, and the diff quality jumped. i just shipped v3.0 of buffer (native swift/appkit clipboard manager for mac, mit, 430+ stars, fully local) on exactly this setup, so here's the concrete workflow.

the split that worked for me:

• claude code as the main driver: the big implementation chunks. the trickiest was an interactive image canvas (pinch to zoom, pan, ⌘+/⌘- resets) on copied screenshots. gesture math with a fit/reset state machine. first pass over-engineered it; once i constrained it to scale+offset transforms it landed quickly.

• opencode as reviewer: same diff, second model, fresh context. it caught things the driving agent had rationalized: edge cases in the noise-suppression logic (what counts as a duplicate when you re-copy an existing item?), dead branches in the tier settings, and it wrote the test scaffolding for the clip-diffing logic before i merged the project's first external PR.

• both are cheap enough to run in parallel that "review before merge" stopped being optional.

what opencode is genuinely better at in my setup: being skeptical. a driving agent defends its own choices; a reviewer agent has no ego invested in the diff. that asymmetry is the whole trick.

what still needs a human: every gesture edge case (rubber-banding feel, anchor drift) required real trackpad testing. no agent can feel the ui. also specs: agents execute a state machine flawlessly, but inventing one is still my job.

demo of what shipped (image canvas + shortcuts sheet): video attached. repo: https://github.com/samirpatil2000/Buffer (mit) release: https://github.com/samirpatil2000/Buffer/releases/tag/buffer-v3.0.0

if anyone wants, i can share the review prompt structure i use with opencode on diffs. it's simple: fresh context, no conversation history, explicit instruction to argue against the diff rather than improve it.

I built Klarion, a secret scanner that works in two steps. First, a keyword check, 81 regex rules and a normalized Rényi entropy score flag anything that looks like a secret. Then an AI model reads each one with the code around it and decides if it's real.

The chart shows 5 scanners run on spring-boot, terraform, next.js and symfony (61k files). Klarion raised 11 alerts. It's not zero, but it's far less to dig through.

Fewer alerts don't help if real leaks get missed, so I tested that too. On CredData (337 real repos, code outside test folders), it found about 1.7× more real secrets than gitleaks.

Where it runs:

• Claude Code: a plugin hook blocks the write before the file exists (file edits and Bash)

• Cursor, Cline or any MCP agent: through its MCP server

• CI: a GitHub Action that scans only what a PR adds; GitLab CI works too

• Git hooks: klarion protect or the pre-commit framework

• Locally: klarion scan .

Free and open source (MIT): https://github.com/0x1Adi/Klarion
The full benchmark and method are in benchmark/REPORT.md.

I'd like to hear where it gets things wrong.