Synthèse automatique

Analyse et compare les opportunités de staking proof-of-stake et de staking liquide sur plusieurs blockchains, avec calcul du rendement net et évaluation des risques.

Points forts

Compare les APY brutes et nettes, les frais, la TVL et les périodes de déblocage pour plusieurs protocoles.
Ajuste le rendement selon la taille de position et les coûts de gas, avec projections sur 1, 3, 6 et 12 mois.
Propose des recommandations d'optimisation pour un portefeuille existant et des comparaisons directes entre protocoles.
Fournit une évaluation des risques par protocole (audits, ancienneté, diversité des validateurs, incidents).

Limites

Dépend des API DeFiLlama et de la disponibilité réseau ; les taux et TVL peuvent être retardés ou incomplets.
Le score de risque et les recommandations sont indicatifs et ne remplacent pas une due diligence financière.
Ne réalise aucune transaction de staking ; l'utilisateur doit agir lui-même sur les protocoles.

Quand l'utiliser

À utiliser pour comparer rapidement des options de staking ou de staking liquide et estimer un rendement net avant de prendre une décision.

Quand l'éviter

À éviter comme unique source pour une décision d'investissement, ou si vous cherchez à exécuter automatiquement des opérations de staking.

Analyse de sécurité

Prudence

Score qualité82/100

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.

Points d'attention

•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.

Comment cette analyse est faite

Exemples

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

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Optimisation des Rendements de Staking

Recommandé pour

Synthèse automatique

Points forts

Limites

Analyse de sécurité

Exemples

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

Prerequisites

Instructions

Step 1: Compare Staking Opportunities

Step 2: Analyze with Position Size

Step 3: Optimize Existing Portfolio

Step 4: Compare Specific Protocols

Step 5: Detailed Risk Assessment

Step 6: Export Results

Output

Quick Comparison Table

Optimization Report

Risk Assessment Detail

Error Handling

Examples

Example 1: Quick Comparison

Example 2: Large Position Analysis

Example 3: Multi-Asset Research

Example 4: Portfolio Optimization

Example 5: Protocol Deep Dive

Resources

Important Notes

Ingénierie de Prompts

Visualisation de Données

Architecture RAG