/install cowork-cog
Cowork Cog — CellCog on Your Machine
Co-work turns any machine into CellCog's workspace. CellCog Desktop acts as a bridge: CellCog's cloud agents coordinate with the desktop app to run commands, read files, and write code directly on the user's machine.
All commands are auto-approved for SDK/agent users — fully autonomous, no manual approval needed.
Prerequisites
This skill requires the cellcog skill for SDK setup and API calls.
clawhub install cellcog
How to Use
For your first CellCog task in a session, read the cellcog skill for the full SDK reference — file handling, chat modes, timeouts, and more.
OpenClaw (fire-and-forget):
result = client.create_chat(
prompt="[your task prompt]",
notify_session_key="agent:main:main",
task_label="my-task",
chat_mode="agent core",
enable_cowork=True,
cowork_working_directory="/path/to/project",
)
All agents except OpenClaw (blocks until done):
from cellcog import CellCogClient
client = CellCogClient(agent_provider="openclaw|cursor|claude-code|codex|...")
result = client.create_chat(
prompt="[your task prompt]",
task_label="my-task",
chat_mode="agent core",
enable_cowork=True,
cowork_working_directory="/path/to/project",
)
print(result["message"])
Why Co-work?
Your Machine as a Data Source
Your data lives on the user's machine — project files, databases, logs, configs. Instead of uploading everything, enable co-work with a working directory and CellCog agents explore, read, and reason about the data directly. No file size limits, no upload hassle.
CellCog as Your Coding Powerhouse
CellCog agents are among the most capable coding agents available — deep reasoning paired with real execution. Enable co-work and delegate complex coding tasks: build websites, APIs, fix bugs, refactor codebases, set up infrastructure.
CellCog itself is built using this exact co-work capability.
Think of it as a Claude Code or Cursor alternative, backed by CellCog's multi-agent depth and any-to-any engine.
Quick Start
from cellcog import CellCogClient
client = CellCogClient(agent_provider="openclaw")
# 1. Check if desktop app is connected
status = client.get_desktop_status()
# 2. If not connected, get install instructions
if not status["connected"]:
info = client.get_desktop_download_urls()
# info contains per-platform URLs + install commands
# Run the install commands for the user's OS, then:
# cellcog-desktop --set-api-key \x3CCELLCOG_API_KEY>
# cellcog-desktop --start
# 3. Create a co-work chat
# OpenClaw agents (fire-and-forget):
result = client.create_chat(
prompt="Refactor the auth module to use JWT tokens",
notify_session_key="agent:main:main", # OpenClaw only
chat_mode="agent core",
enable_cowork=True,
cowork_working_directory="/Users/me/project",
task_label="refactor-auth",
)
# All other agents (blocks until done):
result = client.create_chat(
prompt="Refactor the auth module to use JWT tokens",
chat_mode="agent core",
enable_cowork=True,
cowork_working_directory="/Users/me/project",
task_label="refactor-auth",
)
Desktop App Setup
Call client.get_desktop_download_urls() — returns download URLs and platform-specific install commands for macOS, Windows, and Linux.
After installation:
cellcog-desktop --set-api-key \x3CCELLCOG_API_KEY>
cellcog-desktop --start
The agent can do all of this programmatically — no human interaction needed beyond providing the API key.
Alternatively, ask your human to download CellCog Desktop from cellcog.ai/cowork, open it, and enter their API key.
Desktop CLI Reference
All commands output JSON for easy agent parsing:
| Command | What it does |
|---|---|
cellcog-desktop --set-api-key \x3Ckey> |
Authenticate with API key |
cellcog-desktop --status |
Check connection + app state |
cellcog-desktop --start / --stop |
App lifecycle |
cellcog-desktop --logs |
Debug logs |
Chat Mode for Co-work
Use "agent core" mode for coding tasks — lightweight context focused on code, terminal, and file operations. Multimedia tools load on demand when needed.
result = client.create_chat(
prompt="Your coding task",
chat_mode="agent core",
enable_cowork=True,
cowork_working_directory="/Users/me/project",
task_label="my-task",
)
"agent" mode also works with co-work but loads all multimedia tools upfront. Use "agent core" for faster, more focused coding sessions.
See https://cellcog.ai for complete SDK API reference — delivery modes, send_message(), timeouts, and more.
Error Recovery
If the desktop app disconnects, CellCog auto-fails pending commands with a clear message.
To recover:
cellcog-desktop --stop && cellcog-desktop --start
Then send continue to the chat:
client.send_message(chat_id="abc123", message="continue")
Security
Even with auto-approve, these protections are always active:
- Blocked paths:
~/.ssh,~/.aws, credential files are inaccessible - Output redaction: Sensitive data is automatically redacted from command output
- Per-chat scoping: Each chat session is scoped to its working directory
What You Can Build
Co-work enables the full spectrum of development tasks:
- Web development — Build React apps, APIs, landing pages
- Bug fixing — Debug stack traces, fix test failures
- Refactoring — Modernize codebases, improve architecture
- DevOps — Set up CI/CD, Docker configs, infrastructure
- Data pipelines — ETL scripts, database migrations
- Documentation — Generate docs from code, README files
For the best coding experience, also install code-cog:
clawhub install code-cog
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install cowork-cog - 安装完成后,直接呼叫该 Skill 的名称或使用
/cowork-cog触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
Cowork Cog 是什么?
AI pair programming powered by CellCog Desktop. Code, debug, refactor, and build directly on the user's machine. Terminal access, file operations, full devel... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 242 次。
如何安装 Cowork Cog?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install cowork-cog」即可一键安装,无需额外配置。
Cowork Cog 是免费的吗?
是的,Cowork Cog 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Cowork Cog 支持哪些平台?
Cowork Cog 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(darwin, linux, windows)。
谁开发了 Cowork Cog?
由 CellCog(@nitishgargiitd)开发并维护,当前版本 v1.0.10。