agentsclimarketplace

Optimizing staking rewards

Skill jeremylongshore/claude-code-plugins-plus-skills/plugins/crypto/staking-rewards-optimizer/skills/optimizing-staking-rewards

'Compare and optimize staking rewards across validators, protocols, and blockchains with risk assessment.From its SKILL.md

Install
npx -y skills add jeremylongshore/claude-code-plugins-plus-skills --skill optimizing-staking-rewards

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

What its file declares

Copied from the file, not written here

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

4.5 KB, ~1.1k tokens by cl100k_base, as published. Nobody here has run it

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

What ships with it: 11 files

106.6 KB alongside SKILL.md, 5 of them executable

config/

references/

scripts/

Keep looking

Skills are one crate of 326,144. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.