TeamClaw for Openclaw

A high-performance multi-agent orchestration subsystem featuring the OASIS collaboration engine, automated computer use, and social platform integrations.

avalon-467
v1.0.0
Mar 3, 2026
0
470
0

Install & Download

1. ClawHub CLI

The fastest way to install a skill directly from the registry.

npx clawhub@latest install teamclawtest

2. Manual Installation

Copy the skill folder to one of these locations

Global
~/.openclaw/skills/
Workspace
<project>/skills/

Priority: Workspace > Local > Bundled

3. Prompt Installation

Copy this prompt to OpenClaw to install it automatically.

Help me install teamclawtest using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).

Prefer to download?

Get the raw skill files in a ZIP archive.

What is TeamClaw?

TeamClaw is an advanced agent subsystem designed for complex multi-agent orchestration (OASIS) and visual workflow management. It operates as a versatile extension within the Openclaw Skills ecosystem, providing a built-in lightweight agent capable of automated computer use tasks and real-time visual monitoring via a dedicated Web UI.

By supporting multi-vendor LLM backends like DeepSeek, OpenAI, Gemini, and Claude, TeamClaw allows developers to run independent agent processes without blocking the main agent. It also facilitates remote access through Cloudflare Tunnels, enabling mobile-friendly multi-agent programming and real-time social platform bot integrations for Telegram and QQ.

TeamClaw Use Cases

  • Orchestrating parallel multi-expert discussions for technical route selection and decision-making.
  • Automating complex computer use tasks via a dedicated agent subsystem.
  • Building and managing social platform bots for Telegram or QQ with AI backends.
  • Setting up scheduled AI tasks using the built-in APScheduler center.
  • Remote visual workflow programming via public HTTPS access using Cloudflare Tunnels.

How TeamClaw Works

  1. The user initiates the TeamClaw environment using the provided shell scripts in the Openclaw Skills structure.
  2. LLM providers and API keys are configured to power the conversational and orchestration engines.
  3. The OASIS platform categorizes agents into four types (Direct LLM, Oasis Session, Regular Agent, or External API) based on YAML configuration.
  4. Workflows are executed in either Discussion Mode for consensus or Execution Mode for direct deliverables.
  5. Real-time updates are pushed via SSE (Server-Sent Events) to the Web UI or via Bark push notifications to mobile devices.

TeamClaw Setup

Prerequisites

Ensure you are in the project root directory before running commands.

Installation & Initialization

# Install dependencies
bash selfskill/scripts/run.sh setup

# Initialize configuration
bash selfskill/scripts/run.sh configure --init

# Configure LLM credentials
bash selfskill/scripts/run.sh configure --batch \
  LLM_API_KEY=sk-your-key \
  LLM_BASE_URL=https://api.deepseek.com \
  LLM_MODEL=deepseek-chat

# Create a system user
bash selfskill/scripts/run.sh add-user system MySecurePass123

Service Control

# Start all services (Agent, OASIS, Frontend)
bash selfskill/scripts/run.sh start

TeamClaw Data Schema & Taxonomy

TeamClaw organizes its data through a structured file system and SQLite databases for persistence.

Data Type Storage Location
Agent Memory data/agent_memory.db (SQLite)
Workflows data/user_files/{user}/oasis/yaml/{file}.yaml
Custom Experts data/oasis_user_experts/{user}.json
Discussion Records data/oasis_topics/{user}/{topic_id}.json
Logs logs/launcher.log

TeamClaw Advanced Features

  • OASIS Detach Mode: Run long-running multi-round discussions in the background without blocking sessions.
  • External API Integration: Connect Openclaw Skills agents directly to the OASIS server as external experts.
  • Automated Tunneling: Integrated Cloudflare Tunnel support for secure, auto-configured public HTTPS domains.
  • Multi-Engine Support: Seamlessly mix and match different LLM providers within a single parallel orchestration plan.
  • Stateful Sessions: Persistent memory layers for agents across multiple rounds of discussion.

SKILL.md


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