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nitishgargiitd

Cowork Cog

by CellCog · GitHub ↗ · v1.0.10 · MIT-0
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Install in OpenClaw
/install cowork-cog
Description
AI pair programming powered by CellCog Desktop. Code, debug, refactor, and build directly on the user's machine. Terminal access, file operations, full devel...
README (SKILL.md)

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
Usage Guidance
This skill wants to install and run a native CellCog desktop agent and then let remote CellCog agents execute commands and read/write files in a working directory using only CELLCOG_API_KEY. Before installing: 1) Verify the CellCog desktop installer URLs are official and point to signed releases (cellcog.ai or a known GitHub releases page). 2) Review the cellcog SDK source and the desktop app build/release process (or ask the vendor for reproducible builds). 3) Limit the cowork_working_directory to a minimally privileged project folder (do not point it at your home dir). 4) Prefer testing in an isolated environment (VM/container) before running on a primary machine. 5) Consider creating a scoped API key with least privilege and rotate/revoke it after testing. 6) Do not rely solely on the SKILL.md claims (blocked paths, redaction) — confirm those protections in code or documentation. If you cannot validate the installer provenance and the SDK behavior, proceed cautiously or decline installation.
Capability Analysis
Type: OpenClaw Skill Name: cowork-cog Version: 1.0.10 The cowork-cog skill (SKILL.md) enables autonomous remote code execution and file system access by facilitating the installation and execution of a desktop binary (cellcog-desktop) from cellcog.ai. It explicitly instructs the agent that commands are 'auto-approved' and 'fully autonomous,' bypassing manual approval for terminal and file operations. While the documentation claims to block sensitive paths like ~/.ssh, the combination of automated binary installation and unrestricted shell access represents a significant security risk and a massive attack surface for the user's machine.
Capability Tags
cryptorequires-sensitive-credentials
Capability Assessment
Purpose & Capability
Name/description match the requirements: a local desktop bridge is needed to let remote agents read/write files and run commands. Requiring python3 and CELLCOG_API_KEY is consistent with a Python SDK that authenticates to CellCog.
Instruction Scope
Runtime instructions direct agents to install and start a native desktop app, set an API key, and then allow agents to run commands and read/write files in a provided working directory. The SKILL.md also declares 'all commands are auto-approved' and that the agent can perform installs programmatically — this grants wide discretion to execute installers and shell commands on the host without interactive user approval.
Install Mechanism
The skill is instruction-only and contains no install spec, yet it instructs the agent to download and run platform installers (URLs returned by the SDK). Because the skill relies on running external installers at runtime (via commands returned by get_desktop_download_urls), the install surface depends entirely on those URLs and on the cellcog SDK behavior — there is no built-in validation or pinned release in the skill itself.
Credentials
Only CELLCOG_API_KEY is required, which is proportionate for authenticating the desktop client. However the SKILL.md instructs setting that key into a local desktop process, which effectively grants that process (and any agents it coordinates) access to the scoped working directory. The SKILL.md also asserts protections (blocked paths, output redaction) but those are policy claims in prose and not enforced in this instruction-only skill — treat them as unverifiable guarantees unless you audit the desktop app/SDK.
Persistence & Privilege
always:false (good), but the combination of autonomous agent invocation, 'auto-approved' command execution, and programmatic installation/start of a native desktop agent increases privilege: the agent can install and run software and execute commands on your host without further human approval. That elevated runtime privilege increases risk even though the skill isn't force-enabled globally.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install cowork-cog
  3. After installation, invoke the skill by name or use /cowork-cog
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.10
- Added Windows to the list of supported operating systems in metadata. - Declared new requirements in metadata: Python 3 (bin) and CELLCOG_API_KEY (environment variable). - No changes to functional usage or documentation content beyond metadata updates.
v1.0.9
- Shortened and clarified the skill description for easier understanding. - Simplified usage instructions, highlighting the distinction between OpenClaw and other agents. - Improved wording and formatting for consistency and readability across all sections. - No code or functionality changes; documentation only.
v1.0.8
- Expanded the usage instructions to clarify agent provider options for different environments (OpenClaw, Cursor, Claude Code, Codex, etc.). - Updated the skill description for improved clarity on features: now emphasizes AI pair programming, remote coding, and full development workflows. - Minor edits in documentation for precision, including additional example code and clearer guidance for multi-agent support. - No changes to code or dependencies; documentation (SKILL.md) update only.
v1.0.7
cowork-cog 1.0.7 - SKILL.md has been streamlined and reworded for clarity and conciseness. - "cellcog mothership skill" language updated to simply "cellcog skill." - Added a "How to Use" section with concise agent usage code examples. - Referenced https://cellcog.ai for SDK documentation instead of in-document duplication. - Reduced and clarified introductory and usage sections for easier onboarding. - No changes to code or functionality—documentation update only.
v1.0.6
- Updated usage instructions in SKILL.md to initialize the client with agent_provider="openclaw" (was agent_name). - No functional code or logic changes; documentation only.
v1.0.5
- Added agent_name="openclaw" parameter to the CellCogClient instantiation example in the Quick Start section. - No other user-facing changes. Documentation updated to clarify agent usage in code samples.
v1.0.4
- Major documentation update: SKILL.md rewritten for clarity and depth. - Expanded "Quick Start" and setup instructions, including specific CLI/SDK code examples. - Added "Why Co-work?" and "What You Can Build" sections to highlight benefits and use cases. - Included comprehensive desktop app installation steps, error recovery, and security notes. - Improved chat mode explanations for more effective agent workflow setup. - General content refresh for easier onboarding and developer understanding.
v1.0.3
- Updated documentation to clarify Cowork Cog as the first agent-focused co-work platform, emphasizing direct machine access for agents. - Improved explanation of CellCog Desktop’s capabilities: terminal, file system, development environment, and auto-approval for agent workflows. - Simplified setup instructions and highlighted key parameters for enabling coworking. - Enhanced security model section with bullet points for easy reference. - Added clear references to related skills (code-cog, project-cog) for expanded functionality.
v1.0.2
- Added clarity on co-work chat initiation, now distinguishing OpenClaw agent usage with notify_session_key vs other agents. - Updated "Quick Start" example to reflect agent-specific parameters and usage guidance. - No functional or API changes; documentation only.
v1.0.1
- Clarified language in setup and quick start sections for easier onboarding. - Updated code examples for conciseness and added blocking behavior in `create_chat`. - Added references to the cellcog mothership skill for full SDK API documentation. - Improved instructions for co-work chat mode and task labeling. - Minor wording and formatting enhancements for better readability.
v1.0.0
cowork-cog 1.0.0 - Initial release. - Allows CellCog agents to code, debug, refactor, and build directly on your local machine via CellCog Desktop. - Fully autonomous: all commands are auto-approved for agents, no manual approval required. - Supports co-working workflows for file access, terminal usage, and full development tasks. - Built-in security: blocks access to sensitive files, redacts credentials, and scopes sessions to project directories. - Compatible with macOS and Linux. Requires the cellcog skill and CellCog Desktop app.
Metadata
Slug cowork-cog
Version 1.0.10
License MIT-0
All-time Installs 1
Active Installs 1
Total Versions 11
Frequently Asked Questions

What is Cowork Cog?

AI pair programming powered by CellCog Desktop. Code, debug, refactor, and build directly on the user's machine. Terminal access, file operations, full devel... It is an AI Agent Skill for Claude Code / OpenClaw, with 242 downloads so far.

How do I install Cowork Cog?

Run "/install cowork-cog" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Cowork Cog free?

Yes, Cowork Cog is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Cowork Cog support?

Cowork Cog is cross-platform and runs anywhere OpenClaw / Claude Code is available (darwin, linux, windows).

Who created Cowork Cog?

It is built and maintained by CellCog (@nitishgargiitd); the current version is v1.0.10.

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