Skills Guide

Optimizing Staking Rewards

VerifiedCaution

Compare and optimize staking rewards across validators, protocols, and blockchains with risk assessment. Analyze PoS opportunities, calculate net yields, and maximize returns.

Sby Skills Guide Bot
Data & AIIntermediate
9903/4/2026
Claude Code
#staking#defi#yield-optimization#risk-assessment#python

Recommended for

Claude CodeBackend developerData scientistData & analysis

Automated summary

Analyzes and compares proof-of-stake and liquid staking opportunities across multiple blockchains, calculating net yields and assessing protocol risk.

Strengths

  • Compares gross and net APY, fees, TVL, and unbonding periods across protocols.
  • Adjusts yields for position size and gas costs, with projections over 1, 3, 6, and 12 months.
  • Suggests portfolio optimization moves and supports head-to-head protocol comparisons.
  • Provides per-protocol risk details such as audits, production age, validator diversity, and slashing incidents.

Limitations

  • Relies on DeFiLlama APIs and network access; rates and TVL may be delayed or incomplete.
  • Risk scores and recommendations are indicative and not a substitute for financial due diligence.
  • Does not execute staking transactions; the user must act on the protocols separately.
When to use it

Use it to quickly compare staking or liquid staking options and estimate net returns before making a decision.

When not to use it

Do not use it as the sole basis for an investment decision, or when you need automated execution of staking transactions.

Security analysis

Caution
Quality score82/100

The skill is limited to local file operations and a restricted crypto staking command, and it runs a bundled Python script that fetches public yield data from DeFiLlama. There is no evidence of destructive, exfiltration, obfuscation, or safety-disabling behavior. Because it executes a bundled script and uses network APIs, it warrants caution rather than a safe rating.

Findings
  • •Documented commands invoke 'python {baseDir}/scripts/staking_optimizer.py', which does not match the declared bash restriction 'Bash(crypto:staking-*)'; either the tool will fail to run as documented or broader bash permission is implied.
  • •The skill depends on an external Python script and outbound calls to DeFiLlama/CoinGecko APIs; the script's actual source is not included here, so its behavior is not auditable from the SKILL.md alone (supply-chain dependency, not an observed issue).
  • •Output files are written to user-specified paths (JSON/CSV); harmless but worth noting as write access.
  • •Executes a bundled Python script (scripts/staking_optimizer.py) via Bash; the script contents were not provided for inspection.
  • •Requires outbound network access to DeFiLlama and optionally CoinGecko, so sensitive API keys or wallet data should not be passed to it.
  • •Provides staking allocation recommendations; despite the disclaimer, users may treat the output as financial advice.
How this analysis is made

Examples

Compare ETH staking options
Compare current ETH staking options across native and liquid staking protocols, and show net APY, risk score, TVL, and unbonding period.
Optimize an existing staking portfolio
My staking portfolio is 10 ETH on Lido, 100 ATOM natively, and 50 DOT natively. Optimize it for higher net yield and show projected improvement and switching costs.
Gas-adjusted yield for 25 ETH
Calculate gas-adjusted staking rewards for 25 ETH, including projected returns over 1, 3, 6, and 12 months.

name: optimizing-staking-rewards description: | Compare and optimize staking rewards across validators, protocols, and blockchains with risk assessment. Use when analyzing staking opportunities, comparing validators, calculating staking rewards, or optimizing PoS yields. Trigger with phrases like "optimize staking", "compare staking", "best staking APY", "liquid staking", "validator comparison", "staking rewards", or "ETH staking options".

allowed-tools: Read, Write, Edit, Grep, Glob, Bash(crypto:staking-*) version: 2.0.0 author: Jeremy Longshore jeremy@intentsolutions.io license: MIT

Optimizing Staking Rewards

Overview

This skill analyzes staking opportunities across multiple proof-of-stake blockchains and liquid staking protocols. It compares APY/APR, calculates net yields after fees, assesses protocol risks, and provides optimization recommendations for maximizing staking returns.

Key capabilities:

  • Compare native and liquid staking options across chains
  • Calculate true APY after protocol fees and gas costs
  • Assess risk factors for each staking protocol
  • Optimize portfolio allocation across staking opportunities
  • Project returns over custom time horizons

Prerequisites

Before using this skill, ensure you have:

  • Python 3.8+ installed
  • requests library for API calls (pip install requests)
  • Network access to DeFiLlama APIs
  • Basic understanding of staking concepts (APY, validators, unbonding)

Optional:

  • CoinGecko API key for higher rate limits on price data

Instructions

Step 1: Compare Staking Opportunities

To compare staking options for a specific asset:

python {baseDir}/scripts/staking_optimizer.py --asset ETH

This fetches current rates from DeFiLlama and displays:

  • Protocol name and type (native vs liquid)
  • Gross APY (advertised rate)
  • Net APY (after protocol fees)
  • Risk score (1-10, where 10 is safest)
  • TVL and lock-up period

Step 2: Analyze with Position Size

For gas-adjusted yields based on your stake amount:

python {baseDir}/scripts/staking_optimizer.py --asset ETH --amount 10

Adding --amount calculates:

  • Effective APY accounting for gas costs
  • Projected returns (1M, 3M, 6M, 1Y)
  • Gas cost as percentage of position

Step 3: Optimize Existing Portfolio

Input current positions for optimization recommendations:

python {baseDir}/scripts/staking_optimizer.py --optimize \
  --positions "10 ETH @ lido 4.0%, 100 ATOM @ native 18%, 50 DOT @ native 14%"

The optimizer will:

  • Calculate current total yield
  • Suggest higher-yield alternatives
  • Show projected improvement
  • Warn about switching costs

Step 4: Compare Specific Protocols

For head-to-head protocol comparison:

python {baseDir}/scripts/staking_optimizer.py --compare --protocols lido,rocket-pool,frax-ether

Compare metrics:

  • APY side-by-side
  • Fee structures
  • Risk profiles
  • Liquidity depth

Step 5: Detailed Risk Assessment

For in-depth protocol analysis:

python {baseDir}/scripts/staking_optimizer.py --asset ETH --detailed

Shows for each protocol:

  • Audit status and age
  • Time in production
  • Validator diversity
  • Historical performance
  • Slashing incidents

Step 6: Export Results

Save analysis for further use:

# JSON output
python {baseDir}/scripts/staking_optimizer.py --asset ETH --format json --output staking.json

# CSV for spreadsheets
python {baseDir}/scripts/staking_optimizer.py --asset ETH --format csv --output staking.csv

Output

Quick Comparison Table

==============================================================================
  STAKING REWARDS OPTIMIZER                              2025-01-15 15:30 UTC
==============================================================================

  STAKING OPTIONS FOR ETH
------------------------------------------------------------------------------
  Protocol        Type      Gross APY  Net APY  Risk   TVL         Unbond
------------------------------------------------------------------------------
  Frax (sfrxETH)  liquid      5.10%     4.59%   7/10   $450M       instant
  Lido (stETH)    liquid      4.00%     3.60%   9/10   $15B        instant
  Rocket Pool     liquid      4.20%     3.61%   8/10   $3B         instant
  Coinbase cbETH  liquid      3.80%     3.42%   9/10   $2B         instant
  ETH Native      native      4.00%     4.00%   10/10  $50B        variable
------------------------------------------------------------------------------
  Ranked by risk-adjusted return (Net APY × Risk Score / 10)
==============================================================================

Optimization Report

==============================================================================
  PORTFOLIO OPTIMIZATION
==============================================================================

  CURRENT PORTFOLIO
------------------------------------------------------------------------------
  Position              APY      Annual Return
  10 ETH @ Lido         3.60%    $720
  100 ATOM @ Native     18.00%   $3,600
  50 DOT @ Native       14.00%   $1,400
------------------------------------------------------------------------------
  Total Portfolio: $25,000      Blended APY: 22.88%    Annual: $5,720

  OPTIMIZED ALLOCATION
------------------------------------------------------------------------------
  Recommendation        APY      Annual Return   Change
  10 ETH → Frax         4.59%    $918           +$198
  100 ATOM → Keep       18.00%   $3,600         $0
  50 DOT → Keep         14.00%   $1,400         $0
------------------------------------------------------------------------------
  Optimized Annual: $5,918      Improvement: +$198 (+3.5%)

  IMPLEMENTATION
  1. Unstake 10 ETH from Lido (instant - liquid)
  2. Swap stETH → ETH on Curve (0.01% slippage est.)
  3. Stake ETH for sfrxETH on Frax Finance
  4. Est. gas cost: ~$15 (current gas: 25 gwei)
==============================================================================

Risk Assessment Detail

  RISK ASSESSMENT: Lido (stETH)
------------------------------------------------------------------------------
  Overall Score: 9/10 (Low Risk)

  Breakdown:
  - Audit Status:        ✓ Multiple audits, latest 6 months ago (+2.0)
  - Time in Production:  ✓ 3+ years live (+2.0)
  - TVL Size:            ✓ $15B+ locked (+2.0)
  - Protocol Reputation: ✓ Industry standard, DAO governance (+1.5)
  - Validator Diversity: ✓ 30+ validators (+1.5)

  Considerations:
  - Largest LSD by market share (potential centralization concerns)
  - stETH occasionally trades at slight discount to ETH
  - 10% fee on staking rewards

  Historical:
  - No slashing events to date
  - stETH peg maintained through market stress
  - Consistent validator performance
------------------------------------------------------------------------------

Error Handling

See {baseDir}/references/errors.md for comprehensive error handling.

Common issues:

  • API timeout: Cached data used, shown with warning
  • Invalid asset: Lists supported assets
  • Rate limited: Automatic retry with backoff
  • No data found: Falls back to known protocol list

Examples

Example 1: Quick Comparison

python {baseDir}/scripts/staking_optimizer.py --asset ETH
# Shows all ETH staking options ranked by risk-adjusted return

Example 2: Large Position Analysis

python {baseDir}/scripts/staking_optimizer.py --asset ETH --amount 100 --detailed
# Shows gas-adjusted yields for 100 ETH with full risk analysis

Example 3: Multi-Asset Research

python {baseDir}/scripts/staking_optimizer.py --assets ETH,SOL,ATOM --format csv
# Compares staking across multiple assets, exports to CSV

Example 4: Portfolio Optimization

python {baseDir}/scripts/staking_optimizer.py --optimize \
  --positions "50 ETH @ lido 3.6%, 500 SOL @ marinade 7.5%"
# Analyzes current positions and suggests improvements

Example 5: Protocol Deep Dive

python {baseDir}/scripts/staking_optimizer.py --protocol rocket-pool --detailed
# Full analysis of Rocket Pool including validator metrics

Resources

  • DeFiLlama Yields: https://defillama.com/yields - Primary data source
  • StakingRewards: https://www.stakingrewards.com - Native staking reference
  • Lido: https://lido.fi - Largest liquid staking protocol
  • Rocket Pool: https://rocketpool.net - Decentralized ETH staking
  • Frax Finance: https://frax.finance - sfrxETH liquid staking
  • Marinade: https://marinade.finance - Solana liquid staking

Important Notes

  • APYs are variable and change based on network participation
  • Historical yields do not guarantee future returns
  • This tool provides information, not financial advice
  • Always DYOR (Do Your Own Research) before staking
  • Consider your risk tolerance and liquidity needs
Related skills

Prompt Engineering

Data & AI

Prompt engineering best practices and templates to maximize AI outputs.

Claude CodeCursorCodexintermediateSafe
289
78
1,167
Admin

Data Visualization

Data & AI

Generates data visualizations and charts tailored to your data.

Claude CodeCursorWindsurfintermediateSafe
198
56
967
Admin

RAG Architecture Setup

Data & AI

Setup guide for RAG (Retrieval-Augmented Generation) architectures.

Claude CodeCursorWindsurf+1intermediateSafe
167
51
922
Admin