A specialized AI agent skill for performing comprehensive Uniswap-based due diligence, liquidity analysis, and risk assessment for any crypto token.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install research-token
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 research-token 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 Research Token?
The Research Token skill is a sophisticated tool designed for the Openclaw Skills ecosystem that empowers AI agents to conduct deep-dive technical research on decentralized finance assets. It focuses specifically on the Uniswap protocol, providing developers and traders with a clear picture of a token's liquidity depth, volume trends, and distribution across multiple chains. By synthesizing complex on-chain data, it transforms raw pool information into actionable trading intelligence.
This skill is essential for anyone building automated trading bots, research assistants, or portfolio management tools within the Openclaw Skills framework. It goes beyond simple price checks by analyzing market impact, pool fragmentation, and concentration risks, ensuring that agents can provide high-fidelity financial insights based on observable protocol metrics.
Research Token Use Cases
- Assessing the liquidity depth of a token like UNI or PEPE before executing large trades.
- Conducting automated due diligence to identify high-risk pool concentrations for new token listings.
- Analyzing volume trends across multiple chains including Ethereum, Arbitrum, and Polygon.
- Determining the maximum trade size possible with minimal price impact for a specific asset.
How Research Token Works
- The agent receives a user request containing a token name, symbol, or contract address.
- Parameters such as specific chains or a specific analytical focus (liquidity, volume, or risk) are extracted from the prompt.
- The skill delegates the core processing to a specialized token-analyst sub-agent within the Openclaw Skills architecture.
- The sub-agent performs a comprehensive scan of Uniswap pools to aggregate TVL and volume data.
- A structured report is generated, highlighting liquidity fragmentation, turnover, and severity-graded risk factors.
Research Token Setup
To deploy this skill within your environment, ensure you have the Openclaw Skills runtime configured and the token-analyst sub-agent enabled. You can initiate a research task via the CLI:
# Trigger a token research task for a specific asset
openclaw-agent run research-token --token "UNI" --chain "ethereum"
Ensure your model configuration includes Task(subagent_type:token-analyst) in the allowed tools section of your manifest.
Research Token Data Schema & Taxonomy
The skill produces a structured report containing detailed metadata about the token's market health. The data is organized into the following categories:
| Section | Data Points |
|---|---|
| Identity | Token address, supported chains, and active pool count |
| Liquidity | Total TVL, best performing pool, and 1% price impact depth |
| Volume | 24h/7d/30d volume trends, turnover ratios, and stability metrics |
| Risk | Pool concentration percentages and severity levels (Low/Med/High) |
| Actionability | Maximum suggested trade size for < 1% impact |
Research Token Advanced Features
- Multi-chain cross-referencing to provide a global view of liquidity across all supported L2s and sidechains.
- Focus-specific analysis modes that allow users to isolate risk factors or volume trends exclusively.
- Seamless delegation to the token-analyst sub-agent for institutional-grade data accuracy.
- Integration ready for broader Openclaw Skills workflows involving portfolio rebalancing or automated trading strategies.
SKILL.md
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