zerion-vaultsfyi-strategist

name	zerion-vaultsfyi-strategist
description	Institutional-grade yield strategy analysis using vaults.fyi historical data, benchmark rate environments, share price trends, and curator track records, paired with Zerion wallet context.
license	MIT

vaults.fyi Strategist

Purpose: Run deep strategy analysis using vaults.fyi's historical data and benchmark infrastructure alongside Zerion wallet context to answer questions no other DeFi data source can.

When to use

• "If I'd been in vault A instead of vault B, how much more would I have earned?"
• "Are rates high right now or should I wait?"
• "Which curator has the best track record?"
• "Compare Gauntlet vs Steakhouse vs RE7 over the last 30 days"
• "Why is this vault's APY so high?"
• "Break down where this vault's yield is coming from"
• Any request for backtesting, rate environment assessment, or curator evaluation

Key Commands

• zerion portfolio <address> — current portfolio for context
• zerion positions <address> — existing DeFi positions
• zerion pnl <address> — realized P&L for comparison with vault returns
• vaults.fyi MCP: vault_details — full vault metadata, score, curator, protocol, fees
• vaults.fyi MCP: vault_apy_history — historical APY over configurable windows
• vaults.fyi MCP: vault_tvl_history — historical TVL trends
• vaults.fyi MCP: vault_history — share price history for precise return calculation
• vaults.fyi MCP: vault_returns — realized returns for a specific wallet
• vaults.fyi MCP: benchmark_apy — current network benchmark rate
• vaults.fyi MCP: benchmark_apy_history — historical benchmark for rate environment analysis
• vaults.fyi MCP: curators — list and normalize curator names
• vaults.fyi MCP: vaults_search — search by curator, asset, network, protocol

Requirements

• Zerion CLI: npm install -g zerion-cli
• Zerion API key: export ZERION_API_KEY="zk_..."
• vaults.fyi hosted MCP v2 connected

Workflow

Backtest: "What if I'd been in vault X instead?"

Compare historical performance of two or more vaults to quantify the difference a decision would have made.

1. Gather historical data

For each vault being compared:

• Call vault_apy_history for the comparison window (30, 60, or 90 days). Set fromTimestamp to the start of the window (e.g. current unix timestamp minus 2592000 for 30 days) — without it, the API returns data from vault creation.
• Call vault_history for share price data over the same period. Use the same fromTimestamp.
• Call vault_tvl_history to understand capital flow context. Use the same fromTimestamp.
• Call vault_details for current score, fees, and flags.

2. Calculate comparative returns

Using share price history (the most accurate method):

• Period return: (end_share_price - start_share_price) / start_share_price
• Annualized return: compound the period return to a yearly figure
• For a specific amount: hypothetical_value = deposit_amount * (end_share_price / start_share_price)

Account for fees: share price already reflects performance fees on most vaults, but note management fees or withdrawal fees that would apply on exit.

3. Add wallet context

If the user provides an address, show their actual returns in the current vault:

zerion pnl <address>

Call vaults.fyi vault_returns with the wallet address and vault to get realized return data. Compare actual returns against what the alternative vault would have delivered.

4. Present the backtest

Metric	Current Vault	Alternative Vault
Period return
Annualized return
Hypothetical value on $10,000
APY stability (high/low range)
TVL trend
Score
Fees

State the dollar difference clearly: "Over the last 30 days, vault B would have earned $X more on a $10,000 position."

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Rate Environment: "Are rates high or low right now?"

Use benchmark infrastructure to characterize the current yield market and identify anomalies.

1. Build the benchmark picture

For target networks (default: mainnet, Base, Arbitrum, Optimism):

• Call benchmark_apy with code: "usd" and code: "eth" for current rates.
• Call benchmark_apy_history for 30-day and 90-day windows.

2. Classify the environment

For each network and benchmark:

• Elevated: current rate > 1.5x the 30-day average
• Compressed: current rate < 0.7x the 30-day average
• Normal: between those bounds
• Trending: compare 7-day average vs 30-day average for direction

3. Identify what's driving the environment

When rates are elevated:

• Call vaults_search sorted by apy30day descending to find the top-yielding vaults.
• Check whether high yields are concentrated in a single protocol, curator, or asset — that usually signals an incentive campaign or temporary liquidity event.
• Call vault_details on the top yielders to check for reward tokens or incentive flags.

4. Make a recommendation

• Elevated rates: "Rates are high. Lock in yield now, but be aware this may be incentive-driven and temporary."
• Compressed rates: "Rates are low. Consider shorter-duration positions or waiting for better entry points."
• Normal rates: "Rates are in line with recent history. Standard deployment criteria apply."

If the user has a wallet, compare their current positions against the environment:

zerion positions <address>

Flag positions that are earning below the compressed benchmark — those are underperforming even in a bad market.

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Curator Track Record: "Who should I trust with my capital?"

Evaluate curators by their historical performance, risk management, and vault quality.

1. Resolve and compare curators

Call curators to normalize names. Then for each curator:

• Call vaults_search with curators: [name], sortBy: "tvl", sortOrder: "desc" to get all their vaults.
• For each vault, call vault_apy_history for 30-day performance.
• Call vault_details for score, flags, and fees.

2. Build curator scorecards

For each curator, aggregate:

Metric	Curator A	Curator B	Curator C
Vaults managed
Total TVL
TVL-weighted avg APY (30d)
Average score
Score range (min–max)
Active incidents
Historical incidents
Networks active on
Assets managed
APY consistency (range over 30d)

3. Verdict

Rank curators on:

1. Risk management: incident frequency, score consistency, flag history
2. Yield delivery: TVL-weighted APY vs benchmark
3. Consistency: APY stability over 30 days
4. Diversification: breadth across markets, assets, and networks

If the user holds positions with any of these curators, show their exposure:

zerion positions <address>

Common Blockers

• Limited historical data for new vaults: Vaults launched recently won't have 90-day history. Note the available data window and compare only within it.
• Benchmark not available for all networks: Smaller or newer networks may lack benchmark history. Note the gap.
• Curator comparison across different assets: Comparing a stablecoin curator to an ETH curator on raw APY is misleading. Group by asset class and compare within groups.
• Complex deposit/redeem flows affect strategy viability: When recommending vaults or curators, factor in transactionalProperties. A vault with redeemStepsType: "complex" (e.g., quarterly settlement, multi-day cooldowns) is less suitable for active rebalancing strategies. A vault with depositStepsType: "complex" has higher operational cost to enter. Include flow type in curator and vault assessments.
• Zerion positions vs vaults.fyi positions: Zerion shows all DeFi positions (broad coverage, USD values). vaults.fyi adds vault-specific yield intelligence (APY methodology, scores, flags, curator data). When the user provides a wallet for context, use both — Zerion for the portfolio-wide picture, vaults.fyi for the yield analysis layer.

Related Skills

• zerion-vaultsfyi-yield-optimizer — act on strategist findings by identifying rebalance opportunities
• zerion-vaultsfyi-rebalance — execute the moves the strategist recommends
• zerion-vaultsfyi-market-intel — lighter-weight market overview
• zerion-analyze — Zerion's wallet analysis for portfolio context