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Optimizing Staking Rewards

Free

Maximize your staking yields with risk assessments.

by jeremylongshore2.6k stars on jeremylongshore/claude-code-plugins-plus-skills
Updated Aug 10, 2026
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Free · Opens the source repo

What Optimizing Staking Rewards does

The Optimizing Staking Rewards skill provides a comprehensive toolset for analyzing and optimizing staking opportunities across various proof-of-stake (PoS) blockchains and liquid staking protocols. By comparing annual percentage yields (APY) and annual percentage rates (APR), calculating net yields after fees, and assessing protocol risks, this skill helps users make informed decisions about their staking strategies. It is particularly useful for those who actively participate in staking or are looking to enter the cryptocurrency space with a focus on yield optimization.

This skill operates through a series of Python scripts that fetch and analyze data from DeFiLlama APIs, enabling users to compare staking options for specific assets, analyze potential returns based on position sizes, and optimize existing portfolios. Users can easily trigger analyses with straightforward command-line instructions, allowing for quick comparisons and assessments of different validators and protocols. Additionally, the skill provides options to export results in JSON or CSV formats, facilitating further analysis or record-keeping.

The target audience for this skill includes cryptocurrency investors, DeFi enthusiasts, and anyone interested in maximizing their staking rewards while minimizing risks. By leveraging the built-in risk assessment features, users can better understand the trade-offs associated with different staking options, ensuring they choose the most suitable protocols based on their risk tolerance and investment goals.

In summary, the Optimizing Staking Rewards skill is a powerful ally for anyone looking to navigate the complexities of staking in the cryptocurrency landscape, providing essential tools for comparison, analysis, and optimization of staking rewards.

When to use it

Use this skill when you need to analyze and compare staking opportunities across multiple validators and protocols.

When not to use it

This skill may not be suitable for users who are not familiar with command-line interfaces or those looking for a graphical user interface for staking analysis.

What you can build with it

Quick ETH Staking Comparison

Run a simple command to quickly compare different staking options for Ethereum and identify the best yields.

Full Risk Analysis for Large Positions

Analyze the potential returns and risks for a large staking position, ensuring you understand the implications of your investment.

Multi-Asset Comparison Exported to CSV

Compare staking options across multiple assets and export the results for further analysis or reporting.

How to install Optimizing Staking Rewards

View source

1. Install with the skills CLI

npx skills add jeremylongshore/claude-code-plugins-plus-skills/optimizing-staking-rewards --agent claude-code

2. Or install it manually

Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.

Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs

Inside SKILL.md

Written by jeremylongshore

Optimizing Staking Rewards

Overview

Analyze staking opportunities across PoS blockchains and liquid staking protocols. Compares APY/APR, calculates net yields after fees, assesses protocol risks, and recommends optimal allocations.

Prerequisites

  1. Python 3.8+ installed
  2. Dependencies: pip install requests
  3. Network access to DeFiLlama APIs
  4. Optional: CoinGecko API key for higher rate limits

Instructions

  1. Compare staking options for a specific asset:

    python ${CLAUDE_SKILL_DIR}/scripts/staking_optimizer.py --asset ETH

    Shows protocol name, type (native vs liquid), gross/net APY, risk score, TVL, and lock-up period.

  2. Analyze with position size for gas-adjusted yields:

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

    Calculates effective APY accounting for gas costs and projects returns at 1M, 3M, 6M, and 1Y.

  3. Optimize existing portfolio with current positions:

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

    Suggests higher-yield alternatives with projected improvement and switching costs.

  4. Compare protocols or run risk assessment:

    python ${CLAUDE_SKILL_DIR}/scripts/staking_optimizer.py --compare --protocols lido,rocket-pool,frax-ether
python ${CLAUDE_SKILL_DIR}/scripts/staking_optimizer.py --asset ETH --detailed

  5. Export results in JSON or CSV:

    python ${CLAUDE_SKILL_DIR}/scripts/staking_optimizer.py --asset ETH --format json --output staking.json

Output

Comparison table ranked by risk-adjusted return (Net APY multiplied by Risk Score / 10), showing native and liquid staking options:

  STAKING OPTIONS FOR ETH                              2025-01-15 15:30 UTC  # 2025 timestamp
  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

Error Handling

ErrorCauseSolution
API timeoutDeFiLlama unreachableCached data used with warning
Invalid assetUnknown staking assetLists supported assets
Rate limitedToo many API callsAutomatic retry with backoff
No data foundProtocol not indexedFalls back to known protocol list

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

Examples

Common staking analysis workflows from single-asset comparison to full portfolio optimization:

# Quick ETH staking comparison
python ${CLAUDE_SKILL_DIR}/scripts/staking_optimizer.py --asset ETH

# Large position with full risk analysis
python ${CLAUDE_SKILL_DIR}/scripts/staking_optimizer.py --asset ETH --amount 100 --detailed

# Multi-asset comparison exported to CSV
python ${CLAUDE_SKILL_DIR}/scripts/staking_optimizer.py --assets ETH,SOL,ATOM --format csv

# Portfolio optimization with current positions
python ${CLAUDE_SKILL_DIR}/scripts/staking_optimizer.py --optimize \
  --positions "50 ETH @ lido 3.6%, 500 SOL @ marinade 7.5%"  # 500 - minimum stake amount in tokens

Resources

Frequently asked questions about Optimizing Staking Rewards

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