A sophisticated multi-agent orchestration framework for Openclaw Skills that defines clear execution roles and isolation boundaries between specialized AI agents.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install multi-agent-hybrid-architecture
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install multi-agent-hybrid-architecture 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 Multi-Agent Hybrid Layered Isolation Architecture 1.0?
The Multi-Agent Hybrid Layered Isolation Architecture 1.0 is a comprehensive execution standard designed for Openclaw Skills to facilitate seamless collaboration between specialized agents. This architecture introduces a structured hierarchy where the Momo agent acts as a strategic coordinator and writer, while the Xiaomei agent handles creative media execution. By enforcing strict logical and physical isolation, the framework ensures that complex tasks are decomposed accurately and handled by the agent with the most appropriate skill set.
This framework is essential for developers looking to build scalable AI systems where task delegation, quality control, and knowledge management are handled automatically. It provides a blueprint for multi-agent interaction that minimizes errors and maximizes output quality by preventing role confusion and skill overlap.
Multi-Agent Hybrid Layered Isolation Architecture 1.0 Use Cases
- Orchestrating complex content creation projects that require both strategic planning and high-quality visual assets.
- Automated task delegation for social media management, from strategy formulation to final publishing.
- Managing emergency workflows where urgent tasks must bypass coordination layers for immediate execution.
- Implementing multi-layered quality assurance where one agent audits the technical output of another.
How Multi-Agent Hybrid Layered Isolation Architecture 1.0 Works
- The system detects user intent and classifies task complexity based on specific keywords such as planning, scheme, or image generation.
- For complex tasks, the Writer agent (Momo) decomposes the project into logical sub-tasks and identifies required specialized skills.
- The Writer agent delegates specific creative or execution tasks to the Media agent (Xiaomei) using standardized communication protocols.
- The Media agent executes specialized skills like image generation or new media formatting and submits the results for review.
- The Writer agent performs a multi-dimensional quality audit to ensure the output meets the project resolution and tone standards.
- Completed tasks are integrated and delivered to the user, with session data archived into the long-term memory system of these Openclaw Skills.
Multi-Agent Hybrid Layered Isolation Architecture 1.0 Setup
To deploy this architecture, ensure your agent environment is configured to support layered isolation for Openclaw Skills. You must verify that the constraint files are present in your workspace.
# Validate the configuration of isolation constraints in SOUL.md
if [ -f "SOUL.md" ]; then
grep -q "禁止.*baoyu" SOUL.md && echo "Momo isolation constraints active"
fi
Multi-Agent Hybrid Layered Isolation Architecture 1.0 Data Schema & Taxonomy
The architecture organizes its operational data into a structured taxonomy to ensure cross-agent consistency for Openclaw Skills.
| Data Component | File Location | Information Managed |
|---|---|---|
| Session Memory | memory/YYYY-MM-DD.md |
Daily logs, task success rates, and execution time metrics. |
| Knowledge Base | MEMORY.md |
Distilled reusable experiences and strategic workflow optimizations. |
| Prompt Assets | Creative Metadata | Successful prompt templates and specific image parameter configurations. |
Multi-Agent Hybrid Layered Isolation Architecture 1.0 Advanced Features
- Strategic task bypass protocols for emergency requests to ensure sub-30 second response times.
- Automated quality audit checklists covering image resolution, tone consistency, and safety compliance.
- Integrated memory synchronization that moves session-specific learnings into a permanent knowledge base.
- Hard-coded safety boundaries that prevent agents from executing unauthorized technical skills.
SKILL.md
Loading
Related Openclaw Skills
Feishu Multi-Agent Onboarding Skill
A specialized tool for rapidly configuring and validating multiple AI agents within Feishu via the OpenClaw framework.
Valence Memory
A persistent knowledge substrate for Openclaw Skills that replaces flat-file memory with structured, confidence-scored beliefs and semantic search.
YBoard Operator
An automated assistant for managing and editing video storyboards and presentation plans on yboard.online.
SearXNG Web Search
Provides AI agents with private, aggregated web search capabilities via a local SearXNG instance.
Table Mountain Status
A powerful automation tool to fetch real-time Table Mountain Cableway status, weather data, and waiting times directly into your workflow.
Tageblatt Headlines
Automatically fetch, archive, and notify top news headlines from tageblatt.de using a lightweight Python workflow.
Featured*
