Optimizing Staking Rewards

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'Compare and optimize staking rewards across validators, protocols, and

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Details

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Optimizing Staking RewardsStart free

What this skill tells your AI

The instructions your AI receives, as published by jeremylongshore/tons-of-skills-marketplace in skills/.curated/optimizing-staking-rewards/SKILL.md and read by Ahel’s review.

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

Signals

GitHub stars
3k
Forks
415
Last commit
Oct 2026

Ahel review

  • K1binfo
    installs-packages
  • K1binfo
    installs-packages (in references/errors.md)

Automated review, not a security audit. Ruleset v1+k2.

Advanced
Item type
skill
Key
optimizing-staking-rewards
Source
github.com/jeremylongshore/tons-of-skills-marketplace