Install
openclaw skills install @cellcog/pair-programming-cellcogAI pair programming powered by CellCog Desktop. Code, debug, refactor, and build directly on the user's machine. Terminal access, file operations, full development workflows — auto-approved for agents.
openclaw skills install @cellcog/pair-programming-cellcogCo-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.
This skill requires the cellcog skill for SDK setup and API calls.
# Claude Code, Cursor, Codex + 70 more agents
npx skills add cellcog/skills --skill cellcog
# OpenClaw
openclaw skills install @cellcog/cellcog
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",
chat_tier="max",
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",
chat_tier="max",
enable_cowork=True,
cowork_working_directory="/path/to/project",
)
print(result["message"])
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 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.
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 <CELLCOG_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",
chat_tier="max",
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",
chat_tier="max",
enable_cowork=True,
cowork_working_directory="/Users/me/project",
task_label="refactor-auth",
)
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 <CELLCOG_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.
All commands output JSON for easy agent parsing:
| Command | What it does |
|---|---|
cellcog-desktop --set-api-key <key> | Authenticate with API key |
cellcog-desktop --status | Check connection + app state |
cellcog-desktop --start / --stop | App lifecycle |
cellcog-desktop --logs | Debug logs |
Use chat_mode="agent", chat_tier="max" for all coding work — code needs the deepest reasoning tier. The SDK applies "max" automatically whenever enable_cowork=True, so co-work sessions get it even without an explicit tier.
"agent core" is a legacy name that still works forever (the server maps it to Agent max), but new code should pass chat_mode="agent", chat_tier="max".
Agent Team (chat_mode="team") is reserved for deep research — use it only when the task IS research that happens to involve code.
Browse rides Co-work: create_chat(enable_browse=True, browser_profile_id=...) lets the agent drive the user's real Chrome alongside the terminal (profiles discoverable via client.get_browser_status(); enabling Browse auto-enables Co-work server-side).
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")
Even with auto-approve, these protections are always active:
~/.ssh, ~/.aws, credential files are inaccessibleCo-work enables the full spectrum of development tasks:
For the best coding experience, also install coding-agent-cellcog:
# Claude Code, Cursor, Codex + 70 more agents
npx skills add cellcog/skills --skill coding-agent-cellcog
# OpenClaw
openclaw skills install @cellcog/coding-agent-cellcog