← Back to Skills Marketplace
wpank

Uniswap Lp Strategy

by wpank · GitHub ↗ · v0.1.0
cross-platform ✓ Security Clean
754
Downloads
0
Stars
3
Active Installs
1
Versions
Install in OpenClaw
/install lp-strategy
Description
Comprehensive LP strategy comparison for a token pair — evaluates all versions, fee tiers, range widths, and rebalance approaches side-by-side with APY, IL, gas costs, and risk ratings. Use when the user wants to compare LP options or see a detailed analysis of all strategies.
README (SKILL.md)

LP Strategy Comparison

Overview

Produces a comprehensive, multi-strategy comparison for LP positions on a token pair. Unlike optimize-lp which gives a single recommendation, this skill presents all viable strategies side-by-side with detailed pros/cons, enabling the user to make an informed decision.

This is the "deep dive" version — use when the user wants to understand all their options, not just the top pick.

When to Use

Activate when the user asks:

  • "Compare LP strategies for ETH/USDC"
  • "What are my options for LPing into X/Y?"
  • "Detailed LP analysis for WETH/USDC"
  • "Show me all fee tiers for this pair"
  • "V2 vs V3 vs V4 comparison for X/Y"
  • "Give me a full breakdown of LP options"
  • "I want to understand the tradeoffs before LPing"

Parameters

Parameter Required Default How to Extract
token0 Yes First token
token1 Yes Second token
capital No Amount available for LP
chain No All chains Specific chain or "all" for cross-chain comparison
strategies No All Specific strategies to compare (usually "all")

Workflow

  1. Extract parameters from the user's request.

  2. Delegate to pool-researcher: First, get a full pool comparison across all fee tiers and versions via Task(subagent_type:pool-researcher). This provides the data foundation (TVL, volume, APY per pool).

  3. Delegate to lp-strategist: Invoke Task(subagent_type:lp-strategist) in comprehensive comparison mode. The agent evaluates every viable combination:

    • V2 full-range (passive)
    • V3 narrow range per fee tier
    • V3 medium range per fee tier
    • V3 wide range per fee tier
    • V4 options (if available)
    • Cross-chain opportunities (if chain="all")
  4. Present comparison table with all strategies ranked and annotated with pros/cons.

Output Format

LP Strategy Comparison: WETH/USDC

  Pair Type: Stable-Volatile (moderate volatility)
  Best Overall: V3 0.05%, Medium Range (see row 2 below)

  ┌────┬──────────────────┬────────┬──────────┬───────┬──────────┬──────────┬────────┐
  │ #  │ Strategy         │ Chain  │ Fee APY  │ IL    │ Net APY  │ Rebal.   │ Risk   │
  ├────┼──────────────────┼────────┼──────────┼───────┼──────────┼──────────┼────────┤
  │ 1  │ V3 0.05% Narrow  │ ETH    │ 35%      │ -12%  │ 23%      │ Weekly   │ HIGH   │
  │ 2  │ V3 0.05% Medium  │ ETH    │ 21%      │ -6%   │ 15%      │ Bi-weekly│ MEDIUM │
  │ 3  │ V3 0.05% Wide    │ ETH    │ 12%      │ -2%   │ 10%      │ Monthly  │ LOW    │
  │ 4  │ V3 0.30% Medium  │ ETH    │ 8%       │ -6%   │ 2%       │ Bi-weekly│ MEDIUM │
  │ 5  │ V3 0.05% Medium  │ Base   │ 18%      │ -5%   │ 13%      │ Bi-weekly│ MEDIUM │
  │ 6  │ V2 0.30% Full    │ ETH    │ 4%       │ -1%   │ 3%       │ Never    │ LOW    │
  └────┴──────────────────┴────────┴──────────┴───────┴──────────┴──────────┴────────┘

  Strategy Details:

  #1 V3 0.05% Narrow (±5%) — HIGH RISK, HIGH REWARD
    Pros: Highest fee capture, maximum capital efficiency
    Cons: Frequent rebalancing ($15/rebalance on mainnet), high IL risk
    Best for: Active managers with >$10K positions
    Gas warning: Break-even ~3 days per rebalance

  #2 V3 0.05% Medium (±15%) — RECOMMENDED
    Pros: Strong APY with manageable rebalancing, 80%+ time-in-range
    Cons: Moderate IL during large moves
    Best for: Most LPs with $1K+ positions
    Gas warning: Break-even ~1 day per rebalance

  #3 V3 0.05% Wide (±50%) — LOW MAINTENANCE
    Pros: Rarely needs rebalancing, low IL, almost passive
    Cons: Lower capital efficiency, lower APY
    Best for: Passive LPs, small positions where gas matters

  #6 V2 0.30% Full Range — SET AND FORGET
    Pros: Zero maintenance, no range management, battle-tested
    Cons: Lowest returns, less capital efficient
    Best for: First-time LPs, long-term holders who don't want to manage

  Ready to proceed? Choose a strategy and say "Add liquidity with strategy #2"

Important Notes

  • This skill produces analysis, not execution. To act on a strategy, use manage-liquidity.
  • Net APY = Fee APY - Expected IL. Always show both components.
  • Gas costs for rebalancing are factored into the comparison for each chain.
  • Cross-chain comparison (when chain="all") highlights L2 gas advantages.
  • The lp-strategist internally uses pool-researcher for data and risk-assessor for risk evaluation.

Error Handling

Error User-Facing Message Suggested Action
Token not found "Could not find token X." Provide contract address
No pools exist "No pools found for X/Y." Try different tokens or chain
Insufficient data "Not enough data for a reliable comparison." Pool may be too new
Agent unavailable "LP strategist is not available." Check agent configuration
Usage Guidance
This skill is instruction-only and appears coherent for providing LP strategy comparisons; it asks for nothing sensitive itself. Before installing or using it, confirm that the subagents it delegates to (pool-researcher, lp-strategist, and any risk-assessor those subagents use) are trustworthy and examine whether they require API keys or wallet access. If you run the README's npx install commands, you'll be downloading code from a GitHub path — review that repo before executing installs. Finally, remember the skill only analyzes strategies; executing a chosen strategy requires a separate 'manage-liquidity' skill which may need wallet credentials and on-chain transactions, so treat that step with appropriate caution.
Capability Analysis
Type: OpenClaw Skill Name: lp-strategy Version: 0.1.0 The skill bundle is benign. The `SKILL.md` clearly defines an analytical workflow for comparing LP strategies, delegating to `lp-strategist` and `pool-researcher` subagents, which aligns with its stated purpose. Crucially, the `SKILL.md` explicitly states 'This skill produces analysis, not execution,' and there are no instructions for the agent to perform any malicious actions, exfiltrate data, establish persistence, or engage in prompt injection to deviate from its intended function. All files are consistent with a legitimate financial analysis tool.
Capability Assessment
Purpose & Capability
Name/description (LP strategy comparison) matches the SKILL.md: it extracts tokens, asks pool-researcher for pool data, and asks lp-strategist to evaluate strategy variants. No unrelated services, binaries, or env vars are requested.
Instruction Scope
Runtime instructions are limited to parameter extraction and delegating to two subagents (pool-researcher and lp-strategist) and formatting the comparison. The skill explicitly states it produces analysis only and does not execute transactions. It does not instruct reading local files, scanning env vars, or sending data to external endpoints.
Install Mechanism
No install spec and no code files beyond README/SKILL.md (instruction-only). The README suggests optional npx install steps, which would download external code if the user runs them — but the skill itself as published has no installer configured.
Credentials
The skill declares no required environment variables, credentials, or config paths. That is proportional for an analysis-only skill. Note: results depend on the availability and design of the referenced subagents (they may request credentials when invoked).
Persistence & Privilege
always is false and model invocation is allowed (platform default). The skill does not request persistent installation or modify other skills' configuration in the provided instructions.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install lp-strategy
  3. After installation, invoke the skill by name or use /lp-strategy
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v0.1.0
- Initial release of lp-strategy skill for comprehensive LP strategy comparison. - Compares all LP strategies for a token pair across pool versions, fee tiers, ranges, and chains. - Outputs a side-by-side table with APY, impermanent loss, gas costs, and risk ratings for each strategy. - Offers detailed strategy breakdowns with pros/cons and usage recommendations. - Automatically leverages pool-researcher and lp-strategist agents for underlying data and analysis. - Includes robust error handling for missing tokens, pools, data, or unavailable agents.
Metadata
Slug lp-strategy
Version 0.1.0
License
All-time Installs 3
Active Installs 3
Total Versions 1
Frequently Asked Questions

What is Uniswap Lp Strategy?

Comprehensive LP strategy comparison for a token pair — evaluates all versions, fee tiers, range widths, and rebalance approaches side-by-side with APY, IL, gas costs, and risk ratings. Use when the user wants to compare LP options or see a detailed analysis of all strategies. It is an AI Agent Skill for Claude Code / OpenClaw, with 754 downloads so far.

How do I install Uniswap Lp Strategy?

Run "/install lp-strategy" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Uniswap Lp Strategy free?

Yes, Uniswap Lp Strategy is completely free (open-source). You can download, install and use it at no cost.

Which platforms does Uniswap Lp Strategy support?

Uniswap Lp Strategy is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Uniswap Lp Strategy?

It is built and maintained by wpank (@wpank); the current version is v0.1.0.

💬 Comments