From trading-skills
Evaluates DeFi yield opportunities by decomposing fee APR, token emissions, and real vs nominal yield. Accounts for impermanent loss, gas costs, and emission depreciation.
How this skill is triggered — by the user, by Claude, or both
Slash command
/trading-skills:yield-analysisThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
DeFi yields are often misleading. A pool advertising 200% APY may deliver negative real returns once you account for impermanent loss, gas costs, and emission token depreciation. This skill provides the framework to decompose, evaluate, and compare yield opportunities accurately.
DeFi yields are often misleading. A pool advertising 200% APY may deliver negative real returns once you account for impermanent loss, gas costs, and emission token depreciation. This skill provides the framework to decompose, evaluate, and compare yield opportunities accurately.
Most DeFi yield dashboards show nominal yield — the headline number. Real yield requires decomposing that number into its components and subtracting all costs. Without this decomposition:
Every DeFi yield breaks down into one or more of these sources:
Swap fees earned by liquidity providers. This is the most sustainable yield source because it comes from real economic activity.
fee_apr = (daily_volume * fee_rate / tvl) * 365
your_daily_fees = daily_volume * fee_rate * (your_liquidity / total_liquidity)
For CLMM pools (concentrated liquidity), fee income is amplified by how tightly you concentrate your range. See the lp-math skill for CLMM mechanics.
Protocol reward tokens distributed to LPs. Often the largest component of advertised yields, but frequently unsustainable.
emission_apr = (daily_emission_tokens * token_price * 365) / tvl
The critical question: will the emission token hold its value? If everyone farms and dumps, the token depreciates and actual USD yield is much lower.
Interest earned from lending protocol deposits (Marginfi, Kamino, Solend). Driven by borrowing demand — more sustainable than emissions but fluctuates with utilization.
Validator staking yield (~7% APR on Solana) or liquid staking token (LST) yield. The baseline risk-free rate for the Solana ecosystem.
| Metric | What It Includes | What It Ignores |
|---|---|---|
| Nominal APY | Fee APR + emission APR (compounded) | IL, gas, depreciation, risk |
| Real Yield | Everything, net of all costs | Nothing — this is the true return |
real_yield = fee_apr
+ emission_apr × (1 - emission_depreciation)
- il_cost
- gas_cost
- rebalancing_cost
Where:
fee_apr: annualized fee income as fraction of position valueemission_apr: annualized emission income at current token priceemission_depreciation: expected decline in emission token price (0.0 to 1.0)il_cost: expected impermanent loss as annualized rate (see impermanent-loss skill)gas_cost: transaction fees for deposits, withdrawals, claims, compoundsrebalancing_cost: for CLMM positions, cost of rebalancing out-of-range positionsNominal APY displayed: 45%
Decomposition:
Fee APR: 18%
Emission APR: 30% (RAY token rewards)
Emission depreciation: 40% (RAY down 40% over 30d)
Effective emission: 18% (30% × 0.6)
IL cost (estimated): 12% (SOL volatile against USDC)
Gas + rebalance: 1%
Real yield = 18% + 18% - 12% - 1% = 23%
The 45% nominal yield is really 23% after accounting for all factors.
fee_apr = fee_rate * daily_volume / tvl * 365
For a pool with 0.25% fee rate, $2M daily volume, and $10M TVL:
fee_apr = 0.0025 * 2_000_000 / 10_000_000 * 365 = 18.25%
CLMM fee income depends on your position range relative to trading activity:
# Simplified — see lp-math skill for full CLMM math
fee_apr = fee_rate * daily_volume_in_range / position_liquidity * 365
Tighter ranges earn higher fees per dollar deployed but go out of range more frequently, requiring rebalancing.
your_share = your_liquidity / total_pool_liquidity
your_daily_fees = total_daily_fees * your_share
# Protocol P/E ratio
pe_ratio = fully_diluted_valuation / annual_protocol_revenue
# Revenue-to-emission ratio (> 1.0 is sustainable)
sustainability = annual_revenue / annual_emission_value
# Token velocity (high = lots of sell pressure)
velocity = daily_emission_selling / daily_token_volume
Interpretation:
When comparing yield opportunities, normalize across these dimensions:
Compare like for like. For SOL:
| Strategy | Expected APR | Risk Level | IL Exposure |
|---|---|---|---|
| Native staking | ~7% | Low | None |
| Liquid staking (mSOL) | ~7.5% | Low | Minimal |
| SOL-USDC LP (Orca) | ~15-25% | Medium | High |
| SOL lending (Marginfi) | ~3-8% | Low-Med | None |
| Leveraged yield | ~20-50% | High | Varies |
risk_score = (
il_risk * 0.3 +
smart_contract_risk * 0.25 +
emission_sustainability_risk * 0.2 +
liquidity_risk * 0.15 +
protocol_risk * 0.1
)
risk_adjusted_yield = net_apr / risk_score
Include all costs:
impermanent-loss skill)| Protocol | Pool Types | Fee Tiers | Notes |
|---|---|---|---|
| Raydium | CPMM, CLMM | 0.01-1% | Largest Solana DEX by volume |
| Orca | CLMM (Whirlpool) | 0.01-2% | Concentrated liquidity focused |
| Meteora | DLMM, Dynamic | Variable | Dynamic fee adjustment |
| Protocol | Assets | Typical APR | Notes |
|---|---|---|---|
| Marginfi | SOL, USDC, etc. | 2-10% | Points program active |
| Kamino | SOL, USDC, etc. | 2-12% | Auto-compound vaults |
| Solend | SOL, USDC, etc. | 1-8% | Established protocol |
| Method | APR | Lock Period | Notes |
|---|---|---|---|
| Native SOL staking | ~7% | 1 epoch (~2d) | Validator selection matters |
| mSOL (Marinade) | ~7.2% | Instant | Liquid, usable in DeFi |
| jitoSOL (Jito) | ~7.5% | Instant | Includes MEV rewards |
| bSOL (BlazeStake) | ~7% | Instant | Decentralized validator set |
import httpx
# All yield pools
pools = httpx.get("https://yields.llama.fi/pools").json()
# Filter for Solana
solana_pools = [p for p in pools["data"] if p["chain"] == "Solana"]
# Sort by TVL
solana_pools.sort(key=lambda p: p.get("tvlUsd", 0), reverse=True)
Response fields: pool, chain, project, symbol, tvlUsd, apy, apyBase, apyReward, il7d, exposure.
https://api-v3.raydium.io/pools/info/listhttps://api.mainnet.orca.so/v1/whirlpool/listlp-math: AMM formulas for fee calculation and position mathimpermanent-loss: IL estimation for real yield calculationdefillama-api: Fetching yield and TVL data across protocolsrisk-management: Portfolio-level yield allocation decisionsposition-sizing: How much capital to allocate to yield strategiesreferences/yield_math.md — Fee APR, APR/APY conversion, net yield formulas, break-even analysisreferences/sustainability_analysis.md — Emission sustainability metrics, death spiral patterns, real yield identificationscripts/yield_calculator.py — Offline yield calculator with fee APR, IL estimation, net yield, break-even, and sensitivity analysisscripts/yield_comparison.py — Fetches DeFiLlama yield data and compares Solana yield opportunities with risk-adjusted rankingnpx claudepluginhub agiprolabs/claude-trading-skills --plugin trading-skillsAggregates DeFiLlama data to compare yields across protocols/chains, calculate APYs, assess risks via TVL/audits, and recommend optimizations for farming strategies.
Analyzes DEX liquidity pools on Uniswap, Curve, Balancer for TVL, volume, fees, impermanent loss, and LP profitability using Python scripts with IL calculations and pool comparisons.
Calculates and models impermanent loss for AMM liquidity provision, including constant-product and concentrated liquidity formulas with breakeven analysis.