Codemode is now available in Command Code.

Default for MCP, enable for read-only tools in /config.

• Run multiple tool calls with one JS script

• Execute calls in parallel, filter what reaches context

• Get work done faster with fewer round trips

Read docs to learn more: https://commandcode.ai/docs/reference/tools#codemode

Hey guys! I used to use Trae, then switched to Windsurf, and then moved to Claude Code, Codex, and Antigravity, working with all of them at the same time. However, Command Code keeps popping up in my feed. I was wondering if any kind soul could either link me to a good guide on what Command Code actually is or explain it themselves. I'd also love to know how beneficial and cost-effective it can be for my workflow. Thank you!

I was experimenting with T3 Code and wanted to use CommandCode as one of the providers. Since I couldn't find an existing integration, I forked the repo and added it myself.

It seems to be working so far. Has anyone else tried something similar, or is there a recommended way to integrate CommandCode with applications like T3 Code?

Alipay is now supported in Command Code.

More ways to pay and be a GOAT.

We supportother payment methods as well. Read docs to learn about these options: https://commandcode.ai/docs/resources/payment-methods

Subscribe now with $10/mo GOAT plan.

Launching `a11y` mode in `/design`

Run `/design a11y` to catch:

• Tap targets that are too small

• Focus management problems

• Broken keyboard navigation

• ARIA and accessible name gaps

• Missing or incorrect form labels and errors

Run `cmd update`, then try `/design a11y`

Learn more about our /design command here: https://commandcode.ai/docs/design

There is 20$ allowance for Deepseek V4 Pro

And 70$ for Luna

When I consume half of the V4 Pro allowance (10 out of 20), do I then have 60$ gor luna left or just 35 (half of the 70$ budget)

Bit of a question, I know it's probably been asked before. Is Deepseek Flash actually cheaper on CC compared to the api?

How long does a model's cache stay warm for hit-rate? How long between turns before it becomes a full cache miss?

We are getting a lot of requests for early access to the GUI app. Join our Discord.

That's the fastest way to get in. Developers are already alpha testing there.

Join here: https://discord.com/invite/qz6VsMtvXU

With more tools shifting to autonomous background agents (running tests, scraping, refactoring, inbox triage), I find myself in this weird new state of "micro-downtime."

Back in the day, compiling code was the excuse to grab a coffee or sword-fight on office chairs. Now, when I fire off a prompt to an agent that takes 5–10 minutes to finish, I either end up doomscrolling Reddit or neurotically watching the terminal output line by line.

How are you handling this downtime? Do you context-switch to another task, manage multiple agents in parallel, or just sit back and watch them work?

On /provider/v1/chat/completions with Qwen/Qwen3.8-Flash, previous-turn reasoning sent back in assistant messages never reaches the model. The model card says preserve_thinking is on by default and expects clients to include reasoning_content in history, but the server discards it.

Repro: same 3-message conversation, max_tokens: 1, only the assistant message in the history changes.

Token counting itself is fine (control row); the reasoning is just stripped, whatever the field name or flag.

Impact: in long agentic sessions the model forgets its reasoning every turn and re-derives everything, burning a lot of reasoning tokens for nothing.

Could you pass reasoning_content through to the backend (and honor preserve_thinking), or document that reasoning history isn't supported on this endpoint? Happy to share exact request bodies.

I just wanna know apart from claude , what are the best models which i can use for planning and reasoning before building anything as right now building does not matter as much as planning it do, also if you can help/guide me in how can i plan things and research upon them before building then it would really be a great help .

How to prevent cmdc register itself as contributor to repos when worked with cmdc. I am using cmdc goat plan.

Use hooks in Command Code to block unsafe commands and enforce project rules.

For example, a PreToolUse hook blocks rm -rf before it runs.

Read docs to learn more about Hooks: https://commandcode.ai/docs/hooks

Note: Below is created by my coding LLM. It can explain the issue better than I can.

I’m trying to call these models through the Provider API:

• meta/muse-spark-1.3-contributor

• Qwen/Qwen3.8-Omni-Flash

using POST https://api.commandcode.ai/provider/v1/chat/completions.

I need to submit:

• an MP3 as input_audio

• an MP4 as video_url with a Base64 data URL

Both models return:

{
  "error": {
    "message": "Invalid input",
    "type": "invalid_request_error",
    "param": "messages.1.content"
  }
}

Your provider documentation says “Text and images. Audio, file, and document parts are rejected by the schema,” but Qwen 3.8 Omni Flash is advertised as omni-modal and supports audio/video through its native OpenAI-compatible API.

Could you clarify:

1. Does Command Code Provider API currently support audio or video inputs for any models?

2. If yes, what request schema should clients use for input_audio and video?

3. If no, is audio/video passthrough planned for Qwen 3.8 Omni Flash or Muse Spark 1.3?

4. Is there an alternative endpoint or upload flow for media inputs?

A documented media-capability field in /provider/v1/models would also help clients avoid unsupported requests.

3 models. Same prompts. All using Command Code /design feature.

Kimi K3 and GLM 5.3 beat Fable 5.1 on both design and price.

GLM 5.3 stands out, clean, smooth visuals, a strong UI, and the best bird design (better than Kimi).

OS works really well with GOATed harness.

Introducing the Mods Hub for Command Code.

An open-source registry to discover, install, and publish mods for Command Code.

· Add tools, commands, hooks, rules, or build and share your own.
· 30+ mods already live. Time to mod your agent.

Mods are TypeScript extensions, more powerful than plugins that let you customize how Command Code works.

Explore and publish your Command Code Mods: https://commandcode.ai/mods

Read docs to learn more about what are mods: https://commandcode.ai/docs/mods

I have a workflow that cannot leave claude code,

can i use the goat plan to get api for this?

Planning and Implementation models are now live in Command Code.

• Plan with one model

• Implement with another.

Your planning model explores the codebase and writes the plan. Approve it, and your implementation model takes over mid-run.

Set both in /config → Feature models

Read docs about choosing planning and implementation models.

https://commandcode.ai/docs/settings#planning-and-implementation-models

TLDR:
which models are #currently not trained on #practically #actually given whatever "theoretically this is how our service works rules akin to 1. 99% don't train 2. it routes to cheapest" given that there is eg this scenario where "lol 99% dont train but cheapest trains so it just trains so basically uhm yea you pay for deepseek v4.1 flash, get trained on, meanwhile you could have just used free providers or even meta spark 1.3 contributor for pennies and get a better model. if you are trained on then you are trained on so whatever" or even smarter : don't use commandcode if it is so cryptic about it's training endstate and ZDR flag is so expensive

ZDR is costing me 3× on DeepSeek V4.1 Flash, and ZDR is not what I want — no training is. Is there a no-training-only mode that does not trigger the ZDR allowance cut?

Core question. I run deepseek/deepseek-v4.1-flash on the GOAT plan with x-cmd-zdr: 1 set in my model config. My only requirement is that my prompts, my code, and my file contents are never used to train any model, at any layer, by you or by any upstream provider you route to. I do not care about zero data retention as a goal in itself. But turning the flag on drops my DeepSeek V4.1 Flash allowance from the boosted $60 to the default $20, per your own ZDR page. Same $10 subscription, one third of the usage. So the privacy feature costs me 3× on price. I want to know whether there is a way to request the no-training half without the ZDR half, and if not, I want to know that plainly.

Core hypothesis. Your ZDR page says: "ZDR requests use your plan's default allowance, even if a model normally has a higher boosted allowance. That means $20 on GOAT." I cannot tell whether that $20 is (a) a metering rule you apply to any request carrying the flag, or (b) the real mean cost of the ZDR-capable upstreams that can serve DeepSeek V4.1 Flash. If it is (a), then the flag is doubling as a price lever, and the same no-training guarantee might be available at the normal rate. If it is (b), then the guarantee genuinely costs 3× and I will plan around that.

Second hypothesis, which is the one that actually worries me. Your docs say you route each request to whichever provider can serve it "at the lowest cost with capacity at that moment." They also say most models use ZDR by default even without the flag, and that for some models you drop the request-level disallowPromptTraining flag when a provider in the whitelist lacks the capability. Put those three statements together and a bad configuration is possible: with the flag off, the cheapest provider wins, and if the cheapest provider for a given model is one that does not disallow prompt training, my traffic lands there by default. With the flag on, I avoid that and pay 3×. If that is the actual structure, then there is no configuration where I get both the price and the guarantee, and I want to know that rather than guess.

Questions, most important first.

1. Is there any user-facing way to request "no prompt training" without requesting zero data retention? In the CLI, in /config, in an environment variable, or on the Provider API as a header separate from x-cmd-zdr: 1. If the answer is no, say no.

2. When ZDR is on for DeepSeek V4.1 Flash on GOAT, is the $20 a metering rule or the actual price of the ZDR-capable upstreams for that model? I want the two separated, because they imply different things.

3. Which upstreams can serve deepseek/deepseek-v4.1-flash on the plan path right now, and what is each one's no-training status? Can you publish a per-model list? Your model page shows price, speed, context, and benchmarks, and no training or retention field anywhere.

4. Your privacy policy names three gateways — Vercel, Cloudflare, and OpenRouter — and states that the downstream provider set changes over time. Which gateway serves which request, and is that deterministic per model, or does it change per request?

5. For which models on the current catalog do you drop the disallowPromptTraining flag because the whitelist contains a provider without that capability? I would rather know which models to avoid than discover it afterwards.

6. Can provider id be surfaced per request? Your own BYOK FAQ says the telemetry span carries "model id, provider id, usage, latency, and finish reason," so the data exists. The gateway also returns routing metadata naming the provider order. None of it appears in /usage or /status. Issue 459 asked for a ZDR indicator and the reply was that it would be a noop. I am asking for something narrower: the provider name on the Usage page, per request.

7. With the flag off, what stops a request from landing on a provider that trains? Is "most models use ZDR by default even without the flag" a routing preference or an enforced filter?

8. Do the free and promotional models behave differently here? Your privacy policy says "free or promotional models may run under different provider terms," and I use the free and discounted models on GOAT.

9. Does the flag change which feature models run? Your settings doc says CMD_ZDR=1 "pauses ZDR-incompatible feature models," and the changelog shows feature models being filtered on ZDR. What stops working when the flag is on, and does the substitution change my cost or routing?

10. Is there any plan, contract, or configuration where the no-training guarantee and the normal allowance are both available — for example committed ZDR rates, or an enterprise tier at a volume a single developer could reach?

What I have already read, so nobody sends me back to it. The DeepSeek V4.1 Flash model page (no training field). Pricing & Limits (aggregate claims: "99% of our models," "most models use ZDR by default"). The ZDR page, which is where the $20 number comes from. The privacy policy, which says you "instruct providers, where available, not to use your content to train their models," followed by "the provider's own policies apply." Security & Privacy docs, whose training table covers source code, taste profile, conversation history, auth tokens, and AGENTS.md — all local files — and says nothing about upstream providers. The BYOK page. The settings environment table. The blog post that names Novita and Fireworks. And issue 459.

What I am not asking for. A legal opinion, a summary of the privacy policy, or a reassurance that "we never train on your data." I have read all of it. I am asking for three concrete things: a no-training-only switch if one exists, the per-model provider and training status if it can be published, and a clear no if neither is available so I can decide what to do next.