A professional assessment tool that evaluates Web3 AI Agent projects using a rigorous 11-dimension framework for long-term investment analysis.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install web3-agent-screener
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 web3-agent-screener 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 Web3 AI Agent Screener?
The Web3 AI Agent Screener is a specialized analytical tool designed for the Openclaw Skills ecosystem. It provides deep-dive evaluations of blockchain-based AI projects, moving beyond market hype to assess technical and economic fundamentals. By analyzing everything from liquidity to token value capture, it helps developers and investors identify sustainable projects with a three-year value investment perspective.
This skill automates the due diligence process by synthesizing real-time market data, protocol metrics, and competitive landscapes into a standardized report. It is particularly effective at filtering out projects that lack real-world utility or technical moats, ensuring that only high-quality opportunities are prioritized.
Web3 AI Agent Screener Use Cases
- Performing due diligence on emerging Web3 AI Agent protocols.
- Filtering high-growth investment opportunities based on TVL and revenue trends.
- Identifying structural risks in tokenomics and liquidity for long-term holding.
- Benchmarking competitive advantages between different AI-driven decentralized platforms.
How Web3 AI Agent Screener Works
- The user provides a project name or description to the agent.
- The skill initiates a batch web search using specialized keyword strings to gather data on market cap, TVL, revenue, and exchange listings.
- Data is processed through an 11-dimension framework, covering liquidity, moat, tokenomics, and investor quality.
- A comprehensive judgment is made based on the macro context and specific project metrics.
- If the project meets the minimum score threshold (6.5/10), a full investment-grade report is generated; otherwise, a rejection summary is provided.
Web3 AI Agent Screener Setup
To deploy this skill within your environment, ensure you have the Openclaw Skills CLI configured. Use the following command to integrate the screener:
openclaw install web3-agent-screener
Ensure your agent has permissions for web search tools to allow the screener to fetch real-time market data.
Web3 AI Agent Screener Data Schema & Taxonomy
The skill organizes its evaluation into a structured report following this taxonomy:
| Section | Data Points |
|---|---|
| Basic Info | Ticker, Market Cap, Exchanges, Official Links |
| 11-Dimension Table | Scoring (1-10) and evidence for Liquidity, TVL, Moat, Users, etc. |
| Investment Rating | 3-year+ rating and core investment logic summary |
| Risk Profile | Categorized alerts for technical, regulatory, and liquidity risks |
Web3 AI Agent Screener Advanced Features
- Threshold-based filtering: Automatically discards projects scoring below 6.5/10 to save analysis time.
- Multi-exchange liquidity verification: Specifically checks for listings on Tier-1 exchanges like Binance, Coinbase, and OKX.
- Specialized search strategies: Uses compound keyword patterns to extract deep-web data regarding protocol revenue and institutional backers.
- Narrative vs. Reality check: Specifically cross-references stated narratives with verifiable on-chain user activity.
SKILL.md
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