Liquidity Pool Assessment

SkillDev tools

Evaluate liquidity pools across DeFi protocols by analyzing depth, fee structures, volume trends, and risk-reward profiles to determine optimal liquidity provision strategies.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Liquidity Pool Assessment skill

What this skill tells your AI

The instructions your AI receives, as published by nirholas/three.ws in data/skills/defi/liquidity-pool-assessment/SKILL.md and read by ahel’s review.

When to use this skill

Use when the user asks about:

  • Evaluating whether to provide liquidity to a specific pool
  • Comparing liquidity pools across protocols or chains
  • Understanding LP fee earnings potential
  • Analyzing pool depth and slippage characteristics
  • Concentrated liquidity range selection (Uniswap V3 style)

Assessment Methodology

1. Pool Identification

Collect baseline information:

  • Protocol and chain (e.g., Uniswap V3 on Ethereum, Curve on Arbitrum)
  • Pool type: constant product (x*y=k), stableswap, concentrated liquidity, or weighted
  • Token pair composition and fee tier
  • Contract address and verification status

2. Liquidity Depth Analysis

Evaluate the pool's liquidity characteristics:

  • Total TVL and trend over 7d/30d
  • Liquidity distribution — for concentrated liquidity pools, analyze where liquidity is clustered relative to current price
  • Top LP concentration — what percentage of liquidity is from the top 5 LPs? High concentration means exit risk if large LPs withdraw
  • Historical liquidity stability — has TVL been steady or volatile?

3. Volume and Fee Analysis

Assess revenue potential:

  • 24h, 7d, 30d trading volume and trend direction
  • Fee tier and effective fee rate
  • Fee APR derived from actual volume (not projected)
  • Volume-to-TVL ratio — higher ratio means better capital efficiency for LPs
  • Volume source — organic trading vs arbitrage vs MEV

4. Price Impact and Slippage

Model trade execution quality:

  • Slippage for standard trade sizes ($1K, $10K, $100K, $1M)
  • Compare to competing pools for the same pair
  • Identify if the pool is the primary routing destination on aggregators

5. Risk Evaluation

RiskAssessment
Impermanent lossEstimate based on pair correlation and volatility
Smart contract riskAudit status, bug bounty program, incident history
Concentration riskSingle large LP withdrawal impact
Protocol riskGovernance changes, fee switch proposals
Inventory riskFor concentrated positions — price moving out of range

6. Concentrated Liquidity Strategy (if applicable)

When the pool uses concentrated liquidity:

  • Recommend a price range based on historical volatility
  • Calculate capital efficiency multiplier vs full-range
  • Estimate rebalancing frequency and associated gas costs
  • Suggest whether active management or passive full-range is better given the user's time commitment

7. Output Format

Present findings as:

  • Pool: Protocol / Pair / Fee Tier
  • TVL: Current value and 30d trend
  • Fee APR: Based on actual volume
  • Volume/TVL ratio: Assessment of capital efficiency
  • Liquidity quality: Deep / Adequate / Thin
  • Risk level: Low / Medium / High
  • Recommendation: Provide / Avoid / Provide with conditions
  • Optimal strategy: Full range vs concentrated range with specific bounds
  • Position size guidance: Suggested allocation relative to portfolio

Signals

GitHub stars
114
Forks
29
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
liquidity-pool-assessment
Source
github.com/nirholas/three.ws