A comprehensive analytical tool for comparing Liquidity Provider strategies across multiple fee tiers, versions, and blockchains.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install lp-strategy
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 lp-strategy 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 LP Strategy Comparison?
The LP Strategy Comparison skill is a specialized tool designed for DeFi power users and liquidity providers who need a granular view of their investment options. Unlike basic recommendation engines, this skill leverages Openclaw Skills to perform a deep-dive analysis into all viable strategies for a specific token pair, including V2 full-range, V3 concentrated liquidity, and V4 options. It synthesizes complex data like Fee APY, Impermanent Loss (IL), and gas costs into a side-by-side comparison.
By integrating data from pool researchers and risk assessors, the skill ensures that users understand the trade-offs between high-yield/high-risk narrow ranges and low-maintenance/passive strategies. It is particularly effective for evaluating cross-chain opportunities where gas costs significantly impact net returns, providing a technical foundation for informed decision-making in the volatile DeFi landscape.
LP Strategy Comparison Use Cases
- Compare LP strategies for volatile or stable token pairs like ETH/USDC.
- Identify the most capital-efficient fee tier (0.05% vs 0.30%) for specific market conditions.
- Evaluate the impact of different range widths (narrow, medium, wide) on potential Impermanent Loss.
- Analyze cross-chain liquidity opportunities to find the best net APY after gas considerations.
- Conduct a full breakdown of LP options before committing capital to a decentralized exchange.
How LP Strategy Comparison Works
- The skill extracts necessary parameters such as token pairs, capital amount, and preferred chains from the user prompt.
- It triggers a pool-researcher subagent to gather live data on TVL, volume, and existing fee tiers across all protocol versions.
- An lp-strategist subagent evaluates every combination of range widths and rebalancing frequencies.
- The system calculates Net APY by subtracting expected Impermanent Loss and gas costs from the gross Fee APY.
- A comprehensive comparison table is generated through Openclaw Skills, ranking strategies by risk-adjusted returns and providing actionable pros and cons for each.
LP Strategy Comparison Setup
To use this skill within the Openclaw Skills framework, ensure your agent has access to the lp-strategist and pool-researcher subagents. Configure your agent configuration to include the required model (e.g., Opus) and ensure your environment has access to live market data providers. No manual installation of external libraries is required if the core agent environment is properly configured with the necessary subagent permissions.
LP Strategy Comparison Data Schema & Taxonomy
The skill organizes its output into a structured analytical report. The data model includes:
| Attribute | Description |
|---|---|
| Strategy | The protocol version and range configuration (e.g., V3 0.05% Narrow). |
| Fee APY | Projected annual percentage yield from trading fees alone. |
| IL | Predicted Impermanent Loss based on historical volatility. |
| Net APY | The final expected return after IL and gas fees. |
| Risk Rating | A qualitative assessment (Low, Medium, High) based on range width and volatility. |
| Rebalance Freq | How often the position is expected to need manual adjustment. |
LP Strategy Comparison Advanced Features
- Multi-protocol support covering Uniswap V2, V3, and upcoming V4 hooks.
- Automated gas cost factoring to determine break-even periods for rebalancing on Ethereum Mainnet vs L2s.
- Cross-chain comparison mode for identifying yield opportunities on networks like Base or Arbitrum.
- Integration with risk-assessor subagents for sophisticated volatility and draw-down modeling.
- Strategy ranking that prioritizes capital efficiency based on the user's specific capital amount.
SKILL.md
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