DeepMind is a world-leading AI research laboratory under Google that focuses on solving intelligence to advance scientific discovery.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install deepmind
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install deepmind using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
DeepMind represents the pinnacle of artificial intelligence research, moving beyond simple pattern recognition to solve complex scientific challenges. Originally founded in 2010 and acquired by Google in 2014, it has consistently pushed the boundaries of what is possible with reinforcement learning and deep learning. The skill integrates the legacy and technical breakthroughs of DeepMind into the AI agent ecosystem.
By utilizing this skill within the Openclaw Skills framework, developers and researchers can access the logic and methodologies behind revolutionary models like AlphaFold. It serves as a bridge between high-level AI research and practical application in fields like structural biology, material science, and advanced game theory.
To integrate this research-driven capability into your environment, use the following commands within the Openclaw Skills CLI:
# Install the DeepMind research connector
openclaw install skill-deepmind
# Configure access to the AlphaFold database API
openclaw configure deepmind --api-key YOUR_DATABASE_ACCESS_KEY
# Verify the installation and scientific modules
openclaw verify deepmind
The skill organizes its high-fidelity research data and model outputs using a structured taxonomy:
| Data Component | Description | Format |
|---|---|---|
| Timeline Data | Historical milestones from 2010 to 2024 | JSON / Markdown |
| Protein Structures | AlphaFold predictions for over 200 million proteins | PDB / .cif |
| Model Metadata | Technical specs for AlphaGo, AlphaZero, and AlphaFold 3 | YAML |
| Research Papers | Curated links and summaries of ICML/NeurIPS winning papers | Markdown |
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