How do I install the Optimizing Staking Rewards skill?

Run npx skillmds@latest add jeremylongshore/optimizing-staking-rewards in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Optimizing Staking Rewards safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: makes network calls. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Optimizing Staking Rewards?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Optimizing Staking Rewards free to use?

Yes. Installing skills from SkillMD is free. This skill is licensed under MIT.

Who published Optimizing Staking Rewards?

jeremylongshore (@jeremylongshore) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Optimizing Staking Rewards by jeremylongshore

Name: Optimizing Staking Rewards
Rating: 4.666666666666667 (3 reviews)
Author: jeremylongshore

Optimizing Staking Rewards

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".

File contents

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

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

Instructions

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.
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.

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.

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

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

Error	Cause	Solution
API timeout	DeFiLlama unreachable	Cached data used with warning
Invalid asset	Unknown staking asset	Lists supported assets
Rate limited	Too many API calls	Automatic retry with backoff
No data found	Protocol not indexed	Falls 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

${CLAUDE_SKILL_DIR}/references/implementation.md - Optimization reports, risk assessment details, disclaimers
${CLAUDE_SKILL_DIR}/references/errors.md - Comprehensive error handling
DeFiLlama Yields: https://defillama.com/yields
StakingRewards: https://www.stakingrewards.com
Lido: https://lido.fi | Rocket Pool: https://rocketpool.net

---name: optimizing-staking-rewardsdescription: 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".license: MIT---# Optimizing Staking Rewards## OverviewAnalyze staking opportunities across PoS blockchains and liquid staking protocols. Compares APY/APR, calculates net yields after fees, assesses protocol risks, and recommends optimal allocations.## Prerequisites1. **Python 3.8+** installed2. **Dependencies**: `pip install requests`3. Network access to DeFiLlama APIs4. Optional: CoinGecko API key for higher rate limits## Instructions1. **Compare staking options** for a specific asset: ```bash 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: ```bash 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: ```bash 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**: ```bash 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: ```bash python ${CLAUDE_SKILL_DIR}/scripts/staking_optimizer.py --asset ETH --format json --output staking.json ```## OutputComparison 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 $50B variable```## Error Handling| Error | Cause | Solution ||-------|-------|----------|| API timeout | DeFiLlama unreachable | Cached data used with warning || Invalid asset | Unknown staking asset | Lists supported assets || Rate limited | Too many API calls | Automatic retry with backoff || No data found | Protocol not indexed | Falls back to known protocol list |See `${CLAUDE_SKILL_DIR}/references/errors.md` for comprehensive error handling.## ExamplesCommon staking analysis workflows from single-asset comparison to full portfolio optimization:```bash# Quick ETH staking comparisonpython ${CLAUDE_SKILL_DIR}/scripts/staking_optimizer.py --asset ETH# Large position with full risk analysispython ${CLAUDE_SKILL_DIR}/scripts/staking_optimizer.py --asset ETH --amount 100 --detailed# Multi-asset comparison exported to CSVpython ${CLAUDE_SKILL_DIR}/scripts/staking_optimizer.py --assets ETH,SOL,ATOM --format csv# Portfolio optimization with current positionspython ${CLAUDE_SKILL_DIR}/scripts/staking_optimizer.py --optimize \ --positions "50 ETH @ lido 3.6%, 500 SOL @ marinade 7.5%" # 500 - minimum stake amount in tokens```## Resources- `${CLAUDE_SKILL_DIR}/references/implementation.md` - Optimization reports, risk assessment details, disclaimers- `${CLAUDE_SKILL_DIR}/references/errors.md` - Comprehensive error handling- DeFiLlama Yields: https://defillama.com/yields- StakingRewards: https://www.stakingrewards.com- Lido: https://lido.fi | Rocket Pool: https://rocketpool.net

Frequently asked questions

Optimizing Staking Rewards

File contents

Optimizing Staking Rewards

Overview

Prerequisites

Instructions

Output

Error Handling

Examples

Resources

Related skills

Frequently asked questions

How do I install the Optimizing Staking Rewards skill?

What does the Optimizing Staking Rewards skill do?

Is Optimizing Staking Rewards safe to use?

Which AI agents work with Optimizing Staking Rewards?

Is Optimizing Staking Rewards free to use?

Who published Optimizing Staking Rewards?