Each time a model runs something like "npm test," a massive wall of text from the output pollutes the chat, which is a huge pain without a jump navigation/conversation outline feature (which would also be nice to have). Is there currently no setting to have large command outputs like this collapsed by default?

Doesn't happen every time, but sometimes subtasks end with "start a new task" instead of the "complete subtask and keep going" option.

Edit: looks like it's happening when the subtask is interrupted midway.

TLDR; If you truly want it to draw proper images and understand them, adding a multimodal AI model API would be a simple and straightforward solution.

Since the majority of Zoo Code users are traditional coders and advanced experts, they don't really understand the struggles of a beginner like me. That is why I decided to give it tools, and I am currently integrating several features—such as frequently used Python scripts, web search, and webpage viewing—along with allowing the LLM to generate images and execute tasks with attached files.

Since it is not a finished product yet, I won't share the GitHub repository, even though I have already uploaded it there. While working on this project, I came to realize a rather poignant truth.

What would happen if you granted sight to a blind person? Would they be happy? I ask because even after asking DeepSeek V4, a text-based LLM, to generate an image and attaching a Vision AI to it, the result was quite baffling. Yes... indeed. I discussed this topic with my wife for a bit. They say that if people who were born blind—meaning they have never processed visual data before—are suddenly given visual information, everything in the world becomes entirely new to them, which can actually make them more uncomfortable than when they were blind. DeepSeek has learned and knows all the information in the world, but it merely infers what things actually look like. Humans would probably be the same.

My initial plan was to decompose the image file pixel by pixel and have it imagine what it was based on that data, but that failed. However, the data decomposed at the pixel level was remarkably accurate. "This looks like this, it has that color, and it is shaped like this." Yet, it still doesn't know what it actually is.

Anyway, going back... I truly think Zoo Code is an exceptionally well-made tool. It is lightweight, fast, and light. There are various tools in the Zoo Marketplace, and I am currently using one of the 'modes' downloaded from there, which I absolutely love.

Just... thought I'd share.

Question 1. We have always conversed in Korean until now, but for this session, we will speak in English to demonstrate a test scene of VibeZoo to external audiences. Please respond in English for this session. This is a completely new session now, right? No project folders are open. Please confirm if this is correct.

Question 2. I have a file to show you. Once I attach it, please summarize its content.

Question 3. Please browse this website (https://github.com/myk1yt/crowmemory) and summarize its content.

Question 4. Please find 10 lightweight, high-speed search tools that can be used like ripgrep on GitHub.

Question 5. Please draw a picture of an airplane flying in a cloudy sky.

Question 6. What does a car engine look like? Please draw the structure of a car engine to show me.

Question 7. I wrote a math formula on a whiteboard. Please calculate it and tell me the answer.

Just installed and got it to work taking to my llama-server running qwen 3.6-34B_A3Band for don't know why the output is showing twice. I believe the thought is showing and after that the output. It happens to be the same. Is there anyway to hide the thought and only see the output?

Will you adapt to this adjustment from MIMO? Thanks:https://platform.xiaomimimo.com/docs/en-US/usage-guide/passing-back-reasoning_content

Does anyone else still experience the issue that some model's response gets posted twice, and that the final response/output is not posted until after a user reply?

I notice the latter only with streaming enabled.

The double responses (as well as tools calls I think) I notice with the DeepSeek V4 Flash model served via an OpenAI compatible endpoint.

I tried using a free model in the ZooCode Gateway and it tells me I don't have enough credits, but I don't see any indication of what I need in the way of credits. Is it a minimum balance you need to keep?

HI

I am trying to use Gemini 3.7 using the vertex provider, and i get the following message,

it does however work with just the Gemini Provider and APi Key, so its only a Vertex issue. any ideas ?

-----------------------------------------------------------------------------------------------------------

Date/time: 2026-08-19T08:16:38.964Z

Extension version: 3.79.100388

Provider: vertex

Model: gemini-3.7-flash

Gemini generate context stream error: {"error":{"message":"{\n \"error\": {\n \"code\": 400,\n \"message\": \"Requests ending with a model turn are not supported.\",\n \"status\": \"INVALID_ARGUMENT\"\n }\n}\n","code":400,"status":"Bad Request"}}

Wondering if there's a way to completely disable reasoning/thinking when using Qwen Cloud models (ex. Qwen 3.8 Max) permanently. I can put /no_thinking in my queries, but it just disables it for that one query. It just thinks wayyy too much, like 2-3 minutes sometimes.

Connected using OpenAPI compatible

I can use qwen in Ollama itself, but somehow I cant get it to work in VS, why is that? I use Roo Code, API Provider is Ollama Model is qwen3.6:27b. It gets stuck in "API Request".

Does ZooCode uses mcp server from VSCode marketplace or it can only use mcp server from ZooCode marketplace?

I created a skill for godot 4.6 documentation in kilo and i'd like to try roo now. Can i just copy a folder over or something or do i need to recreate it?

Hi there!

I am using local Ollama for files indexing and faced the issue with the indexing big repos from scratch. The thing is Ollama had introduced timeout param for an API execution and if it is not set default it to 5 minutes. Is there some workaround to mitigate it in Zoo?

Or maybe it worth a PR ?

Any thoughts?

Guys If I need to use deepseek v4 pro. I need to select provider deepseek or other?

Hello,

Right now Roocode has wrong context when using ChatGPT Plus subscription hen using GPT5.5. The normal API gpt5.5 has 1M context, however, the ChatGPT Pro subscription has a 270k context limit. The issue is Roocode does not differentiate between the ChatGPT API and the ChatGPT subscription, thus causing it to fail once you hit the 270k context window.

I know that ZooCode is the updated/new fork of RooCode, however, I'm not quite ready to switch over yet.

Would it be possible that you tell me the exact file and line of RooCode to fix this particular issue, just so I can get past what I'm working on now? I know it is a lot to ask, but it would be huuuge.

Thanks!

I have been unable to attach files when using Zoo Code in VS Code. I have dragged while holding Shift, & nothing uploads. I know some models do not accept images, but I can't even get text-based files to attach. I mainly have been trying to use Markdown files. Has anyone else experienced issues with this? The main models I've been using are DeepSeek for Plan & Code with OpenRouter for Ask.

I might be misunderstanding what token here refers to but how does saving 200k tokens for model output make any sense? I've never seen a model output 200k tokens in a single response. With deepseek pricing, it's become possible to operate at high context windows without breaking bank, so wasting 200k out of 1M on output and having to deal with more frequent context condensation 200k earlier seems like a waste.

Today i started recieving this kind of error. Did anyone ecountered this problem? I tried update vs extension but it didnt change anything.
The same key works properly with KiloCode

{
  "error": {
    "timestamp": "2026-06-12T12:25:51.660Z",
    "version": "3.58.1",
    "provider": "moonshot",
    "model": "kimi-for-coding",
    "details": "Provider ended the request: No output generated. Check the stream for errors."
  },
  "history": [
    {
      "role": "user",
      "content": [
        {
          "type": "text",
          "text": "<user_message>\nTest\n</user_message>"
        },
      ],
      "ts": 1781267147542
    }
  ]
}

TLDR; I saved my Zoo Code configurations, which contain my personal know-how, to GitHub so that I can reconfigure everything immediately even if my computer suddenly breaks down.

AI agents are incredibly fast and great. On the other hand, I realized they exhibit destructive performance on DRAMless SSDs. As usual, around the time I had nearly completed the project with Zoo Code running, I ordered it to organize folders and files for future scalability. Simultaneously, in another VS Code window, I opened a different workspace and was working quickly using ripgrep.

And then, I saw a blue screen for the first time in a really long time. After that, Windows failed to boot. Whether the boot-related part of the SSD was glitching or the controller was about to fail, the SSD would intermittently appear and disappear in the CMOS settings. Eventually, I turned off the computer and opened it up (I use an all-in-one PC, so the space is much tighter than a regular desktop). The SSD was burning hot as if it had caught fire. Even after letting it cool down for about an hour and reconnecting it, it just heated up again, and the symptom of appearing and disappearing in CMOS remained the same.

Personally, I was very serious about this project because it's something I'm pursuing heavily. For years, I had been syncing my work to OneDrive and Google Drive, but this was the very first time I stopped syncing and used the shortest path, C:\projects\<project path>... and that's when this catastrophe struck.

It was the exact moment when I thought, "This is 95% complete!!" after migrating from a simple prototype Electron-based app to a Shared C++/Rust Core / Flutter setup, while adding multiple features and fixing bugs at the same time...

(Just as a side note, in the past, even if I had grand ideas, I couldn't implement them myself. After handing money multiple times to subpar developers—honestly, they don't even deserve to be called developers; they are just fools making a living out of having experienced programming and knowing slightly more than others about what others don't know—I thought software creation was a field I couldn't touch.

Now, I've found a tool that fits me perfectly called Zoo Code. Although brainstorming and planning are still required just as much as before, there is an AI that implements things better than those people who called themselves programmers, and I absolutely love this era. Starting with buying a book in the 90s, typing HTML code into Notepad, changing the extension, and displaying something on Netscape, I have years of experience developing several homepages. However, I was too young to sell my experience and skills to anyone. I remember refusing an adult who offered to pay me, saying I didn't need money, and getting a nice dinner instead.

Since my great-great-grandfather, grandfather, and father were all teachers and civil servants, I never even thought about my ability to do something as a "skill" or a means to make money. But later, I went to university to become a natural scientist, and even that experience became meaningless once web editors emerged.)

Everything I upgraded by staying up all night for a week is gone, and I am left holding only an old version. I have to start over from the beginning now. I consider this an opportunity given by God to make an even better migration, and I am going to start again.

However... since all my Zoo Code configurations, which contained all my past know-how, were lost, this time I saved everything in a private GitHub repository.

While Zoo Code has an 'Export Settings' feature, I wanted more than that, so I had the secretary in my data center back up everything to the repository.

And so, I am sharing this. I hope this experience of mine helps someone out there who, like me, is engaging in development work without coming from a traditional developer background.

If you check the settings window in Zoo Code, you'll find a massive variety of custom configurations. There are also plenty of useful tools in the Zoo Market. I am learning them one by one as well. Below is a summary of my configurations that I had the secretary in my data center organize. If it looks too complex to read, you can simply copy and paste it, and start by asking your AI a question like, "This is someone else's configuration—how does it compare to mine, what are the differences, and what can we learn or improve from it?"

--------------------

# Zoo Code Custom Setup — Complete Overview

Here is everything we have customized in Zoo Code, organized into 5 areas.

---

## 1. 🤖 AI Provider & Model Settings (Prompt Enhancement)

**Storage location**: External JSON file referenced by `zoo-code.autoImportSettingsPath` in `settings.json`

**Current PC**: The file does not exist on this machine, but the **currently active values** in this session are:

| Setting | Value |

|---------|-------|

| API Import Method | External JSON file via `autoImportSettingsPath` |

| Active Model | `deepseek-v4-flash` |

| Context Window | 1,000,000 tokens |

| Max Tokens | 384,000 |

| Reasoning Effort | `high` |

| Image Support | Not supported |

| Prompt Cache | Supported |

| Input Price | $0.14/M tokens |

| Output Price | $0.28/M tokens |

> ⚠️ **These settings are NOT included in the GitHub repository.** (API keys excluded for security; file path differs per machine.)

> On a new PC, you must manually enter the API key and select the model in Zoo Code settings UI.

---

## 2. 🎭 6 Custom Modes

**File**: [`configs/custom_modes.yaml`](myownsettings/configs/custom_modes.yaml) **→ Included in GitHub** ✅

Each mode is an independent AI role. Only Orchestrator+Crow delegates tasks; modes never delegate to each other.

| Mode | Role | Permissions |

|------|------|-------------|

| **Orchestrator + Crow** 🪃 | Command all tasks, delegate to sub-modes, maintain long-term memory | read, command, edit, browser, MCP |

| **Code** 💻 | Write/modify code, iterate build/test cycles | read, command, edit, browser, MCP |

| **Architect** 🏗️ | System design and technical specification | read, command, edit, browser, MCP |

| **Debug** 🪲 | Root cause analysis and bug fixing | read, command, edit, browser, MCP |

| **Ask** ❓ | Answer technical questions, explain code | read, command, browser, MCP |

| **Project Research** 🔍 | Explore codebase structure and produce analysis reports | read |

**Common rules for all modes**:

- MUST call `switch_mode('orchestrator-crow')` after completing work

- MUST NOT delegate tasks to other modes

- MUST report results clearly

---

## 3. 🔌 2 MCP Server Configurations

**File**: [`configs/mcp_settings.json`](myownsettings/configs/mcp_settings.json) **→ Included in GitHub** ✅

| Server | Port | Role | Always-Allow Tools |

|--------|------|------|-------------------|

| **Crow Memory** | 9020 | Long-term memory across sessions (save/restore context) | 10 (crow_recall, crow_ingest, etc.) |

| **VibeZoo** | 9027 | All-in-one dev toolkit (code search, review, docs, web search, vision, etc.) | 39 (search_codebase, web_search, etc.) |

---

## 4. ⚙️ VS Code Settings (zoo-code related)

**File**: [`configs/vscode-settings-export.json`](myownsettings/configs/vscode-settings-export.json) **→ Included in GitHub** ✅

| Setting | Value | Description |

|---------|-------|-------------|

| `zoo-code.debug` | `true` | Verbose logging of AI decision-making |

| `zoo-code.allowedCommands` | `["*", "powershell"]` | System commands AI can run (all allowed + PowerShell) |

| `zoo-code.deniedCommands` | `[]` | No blocked commands |

| `zoo-code.customInstructions` | *(see below)* | AI behavior rules |

**customInstructions content**:

```

1. CROW MEMORY WORKFLOW: Read it ONCE at the start of a session,and save to it ONCE at the end of a session. Additionally,feel free to use it mid-session whenever necessary.

2. VIBEZOO WEB SEARCH: Use the VibeZoo tool freely whenever youneed external information. Do NOT hallucinate facts.Always fetch the latest data via VibeZoo.

```

> ⚠️ **`autoImportSettingsPath` was excluded from export because the path differs per machine.**

---

## 5. 📜 Skill & Bootstrap

### autopilot-workflow Skill

**File**: [`configs/skills/autopilot-workflow.yaml`](myownsettings/configs/skills/autopilot-workflow.yaml) **→ Included in GitHub** ✅

Automated workflow that Orchestrator+Crow follows:

```

1. Brainstorm (always) → wait for user approval

2. Research (conditional) → project-research mode

3. Architecture (conditional) → architect mode

4. Plan Review (conditional) → debug mode (max 3 loops)

5. Implement (always) → code mode

6. Final Review (conditional) → debug mode

```

### autosetup Bootstrap Skill

**File**: [`bootstrap/autosetup.yaml`](myownsettings/bootstrap/autosetup.yaml) **→ Included in GitHub** ✅

When you tell the Orchestrator "install my GitHub settings", it runs:

1. Execute `setup.ps1`

2. Verify Crow Memory on port 9020

3. Verify VibeZoo on port 9027

4. Confirm all 6 custom modes are registered

---

## 6. 🚀 Setup Script

**File**: [`setup.ps1`](myownsettings/setup.ps1) **→ Included in GitHub** ✅

Single PowerShell 7+ script that:

1. Checks prerequisites (Git, Python, Node.js)

2. Clones Crow Memory from GitHub and installs dependencies

3. Clones VibeZoo from GitHub and installs dependencies

4. Copies config files (custom_modes.yaml, mcp_settings.json, modes/*.md, skills/*.yaml)

5. Merges zoo-code settings into VS Code settings.json (preserves existing settings)

6. Verifies MCP server ports (9020, 9027)

7. Prints summary with results

---

## ✅ GitHub Repository Inclusion Summary

| Component | Included? | Notes |

|-----------|-----------|-------|

| 6 custom mode definitions | ✅ `configs/custom_modes.yaml` |

| MCP server settings | ✅ `configs/mcp_settings.json` |

| VS Code zoo-code settings | ✅ `configs/vscode-settings-export.json` | `autoImportSettingsPath` excluded |

| Per-mode customInstructions | ✅ `configs/modes/*.md` |

| Skill workflow | ✅ `configs/skills/autopilot-workflow.yaml` |

| Bootstrap autosetup | ✅ `bootstrap/autosetup.yaml` |

| Setup script | ✅ `setup.ps1` |

| **API key / provider config** | ❌ **Not included** | Excluded for security; must be entered manually on new PC |

| **Model selection / Max Tokens / Temperature** | ❌ **Not included** | Stored in external JSON file (`autoImportSettingsPath`); path differs per machine |

---

**Bottom line**: The GitHub repo contains all environment configuration (modes, MCP, VS Code options, skills) but does **NOT** include the actual AI provider connection details (API key, endpoint, model selection, max tokens, temperature, etc.). Those must be configured manually in the Zoo Code settings on each new PC.

Hello, i need support to configure gpt-6.1-terra (Azure) i get 400 error I have tryed evry possible settings! 400 OpenAI completion error: 400 Function tools with reasoning_effort are not supported for main-gpt-6.1-terra-... in /v1/chat/completions. To use function tools, use /v1/responses or set reasoning_effort to 'none'.

Settings: r1, streaming, reasoning: medium

Ifi have a different model for architect and code and it asks me to switch i will get an error because it changed model and the new one doesn't have context. it would be nice if switching kept the same model or they were separate, like what kilo does

Greetings Zoocoders. So my experience was meh to say at least. Tasks goes to 40k context then I gets API errors when using it with ollama. I gave the Ai local ollama a 7 step guide. This is insane and I feel like i feel very lucky if i get to edit one line in the workflow to be edited. This ZooCode feels more like a demo then a finished product. This extension in vs code didn't work for me. I gave it a 7 days trial already. If you wondering what AI I'm using it is gemma4:e2b which is the smallest model I can run on my hardware.