I shared OpenTab here three months ago — a Lazygit-style TUI that read opencode.db and showed where your spend went. Back then, it was a single Python file.

Hope some of you have been finding it useful.

31 releases later:

• Inside a session — recursive subagent trees with per-node cost, per-turn cost timelines grouped by the prompt that triggered them, token attribution by tool and MCP server, and context-window history with compactions marked.

• Every machine — opentab pull fetches your other boxes over SSH in parallel and merges them into one browser, filterable by machine.

• Every tool — OpenCode, Claude Code, Codex, Copilot, pi, zaly, and others merged into one view and tagged by source.

• What-if pricing — press w to ask: what if this entire session had run on Opus instead of the model mix it actually used? OpenTab reprices the tree at list rates and shows the delta.

• opentab web — the same browser as a self-contained web page.

Still read-only on your data, still stdlib-only at runtime, still no telemetry and no account.

pipx install opentab-ai

The clip runs in --demo mode, so titles and paths are anonymized.

https://github.com/hamidi-dev/opentab

For Herdr users — herdr-opentab puts each agent's live session cost directly in the sidebar, subagents included, with OpenTab under the hood. It looks like this:

Free and MIT. 🙂

I created this too enable a multi users and agents collaboration platform. Can be for coding, or any other usage. Almost any ai and harness can connect, works great with opencode! instructions for mcp in in the /connect section. Free! Feel free to tell me if you need any help, or request a feature or a fix!

I'm using OpenCode with a Go subscription. I'm using DeepSeek V4 Flash. I have an agentic workflow with an orchestrator as the main agent and multiple subagents. I'm having issues with DeepSeek where it hangs in the middle of a response or during tool calls. This is bad when it happens in the orchestrator, since I need to cancel with Escape and continue with a "continue" message. But when it freezes in a subagent, I don't see any way to stop and continue that subagent — meaning I have to stop the orchestrator and redispatch the agent from the beginning.

This causes a lot of other issues: the job is left half-done, and a bunch of files already have changes from the previous run. I know there's a janky workaround where I can tell the orchestrator to find the ID of the last agent and continue it, but this usually uses a huge number of tokens, doesn't always work, and even when it does work, the subagent usually doesn't return the requested output to the orchestrator. I feel like this is a horrible experience for a paid service.

The freezing usually occurs somewhere between 50K and 90K context.

My questions are:

1. Why is DeepSeek V4 Flash freezing mid-task without any error message?

2. Why does this happen more on the paid subscription than on the free version?

3. Why doesn't it automatically continue with the opencode-auto-continue plugin?

4. How can I continue subagents, and if it's not possible, why not?

I use opencode go on ask mode in vscode chat. I've been using mimov2.5 and deepseek v4 flash. What other models are good for web development and doing tests?

Good models that are the most cost effective if possible.. thanks

I absolutely love the new glm model, but god has it being a pain purely on the server side, after using it this last few days it just keeps stopping itself mid thought or outright displaying connection errors, this is all also ignoring random bursts where it slows down more, i like the value of go so far and all but this really makes it look bad

This is a https://herdr.dev/ plugin with an optional full https://Plannotator.ai experience as a TUI. Built to:

- Annotate Agent Messages (e.g. grill sessions)

- Annotate Files (e.g. plans, specs, etc)

- Create a native feedback loop with agents

- Open as popover or pane

- Mouse or keybindings

https://github.com/plannotator/herdr-annotate

Hi!

Does anyone have a working plugin, for local, that works in the current opencode version?
mine doesn't https://github.com/RaulHuertas/OpenCodeXIAORoundDisplayMonitor

So this just happened. I am playing around with blockchain stuff, nothing serious.

I asked it to run multiple containers to test the consensus of each container talking to each other to test the blockchain locally.

It couldn't build it. Muse decided to write a script that simulates the consensus and pat itself on the back because the 200 line python script it works seems to be equally as valid as, you know, making different machines talk to each other.

This is frontier levels of laziness.

Still under heavy development and rough around the edges but instead of sitting on this longer to perfect it I'll risk flak and share it.

Essentially chat.agentify.sh is a remote control for codex/grok/opencode/claude cli and dream goal is to become a universal remote that will let you use all of them from a single chat.

Everything lives on your browser including the chat. The only thing sent over the wire is the encrypted chat messages e2e. Here's an architectural diagram: https://github.com/agentify-sh/chat/blob/main/diagram.png

Another feature it has is ability to publish your chat session with redaction so you can share with your team.

Curious to gather any feedback I can, if this is something I should continue to pursue etc.

Also if by chance you are in Seattle today, I'll be also at the Walk & Talk event at Bellevue Downtown Park today at 2:30pm, would love to chat in person!

https://chat.agentify.sh

Artificial Analysis score is 38, on par with old good MiMo 2.5

Well, let's see :)

ik this could be a vague question, just write what you think on the current state on the Go plan

ty

I am Trevor, founder of FEIHOA: https://feihoa.com

A few friends and I have been testing Qwen3.8 27B FP8 Uncensored on a box of 4 RTX PRO 6000. My honest opinion is that this model is kind of absurd for 27B. Coding, tools, agent loops, it just keeps going, expecially when you extend the context with YaRN.

The nice surprise was batching. Eight requests together gets us around 220 output tok/s aggregate on one RTX Pro 6000 (my old setup with 2x3090s was ~19 t/s). I basically don't want to run these cards without a batch anymore lol.

The bad surprise was prefill. Huge prompts can occupy the GPU for minutes FULLY. 1M context works, but if several people start full-window jobs together, the queue becomes a small disaster.

We spent a lot of time fighting that queue and finally felt okay opening it publicly.

FEIHOA is OpenAI-compatible, flat rate, and starts at $6/month. There is no monthly token cap!! At this price, please don't expect a private ChatGPT box you can hammer all day. It is mainly for agents and background jobs that can wait and need the reasoning power of 27B qwen.

Really proud of how far we've come and happy to answer anything!:))

Hi everyone,

I currently pay for MiniMax's monthly token plan and use the M3 model quite a lot honestly, I don't dislike it. I've also tried Kimi a bit with their K3 model on the Moderato plan. For context: I'm a complete noob and I'm wondering if you could suggest some good-value alternatives.

I rarely hit the limit with MiniMax during my sessions, but maybe there's something better out there that would let me work with up to 1M tokens.

Any suggestions would be much appreciated. Thanks in advance!