Pubfi wallet portfolio analysis

Wallet Portfolio Analysis

Goal: Provide concise asset distribution analysis and risk assessment for EVM wallets.

Inputs

• wallet_address (required): EVM address (0x...)

Data Source

Primary: Zerion API via zerion-portfolio.py

# Get all assets
python3 zerion-portfolio.py <address>

# Get only DeFi positions
python3 zerion-portfolio.py <address> --only-defi

Environment: ZERION_API_KEY must be set. If not set, get your API key at: https://www.zerion.io/api

Execution Workflow

Step 1: Validate Input

1. Check address format: 0x + 40 hex characters
2. If invalid format: Exit with error message

Step 2: Fetch Portfolio Data

# Execute Zerion portfolio script
python3 skills/pubfi-wallet-portfolio-analysis/zerion-portfolio.py <address>

Handle Edge Cases:

• Empty wallet → Report "Empty wallet"
• API failure → Exit with error, cannot proceed
• Zero-value positions → Skip

Step 3: Categorize Assets

Group by type:
  Native: ETH, MATIC, BNB, etc.
  Stablecoins: USDC, USDT, DAI, USDS
  DeFi Positions: Has protocol attribute + position_type != 'wallet'
  Other Tokens: Everything else

Track total value per category for distribution percentages

Step 4: Identify DeFi Protocols

For each DeFi position:
  1. Extract protocol name from attributes.protocol
  2. Identify position type (Lending/Staking/LP/etc.)
  3. Record position value and percentage of portfolio
  4. Create list of unique protocols for risk assessment

Step 5: Risk Assessment (DeFi Protocols Only)

For each identified protocol:
  
  A. Fetch Protocol Data (parallel):
     - DefiLlama API: curl "https://api.llama.fi/protocol/{slug}"
     - Extract TVL, chains, audit info, category
  
  B. Check Recent Exploits:
     - Search rekt.news for protocol name
     - Filter last 90 days
     - Record any incidents
  
  C. Calculate Risk Score:
     Risk = Base + Events + Audit + TVL Trend
     
     Factors:
     - No audit: +5
     - Recent exploit (90 days): +5
     - TVL drop >50% (30 days): +3
     - TVL drop 20-50%: +2
     - New protocol (<6 months): +2
     - Single audit: +1
     - Multiple audits: -2
     - Battle-tested (>1 year): -1
  
  D. Assign Risk Level:
     - Score > 7: 🔴 High Risk
     - Score 4-7: 🟡 Medium Risk
     - Score < 4: 🟢 Low Risk
  
  E. Error Handling:
     - DefiLlama fails: Mark TVL as "N/A", continue
     - Rekt.news unavailable: Mark exploits as "Unknown"

Known Safe Protocols (auto 🟢):
  - Aave V2/V3, Uniswap V2/V3, Compound V2/V3
  - Lido, Curve, MakerDAO/Sky

Step 6: Generate Report

Output structured markdown report following the Output Format section below.

---

Output Format

1) Summary

Portfolio: 0x...
Total Value: $X,XXX USD
Chains: Ethereum, Arbitrum, Base

2) Asset Distribution

Asset Breakdown:
• Native: $XXX (XX%)
• Stablecoins: $XXX (XX%)
• DeFi Positions: $XXX (XX%)
• Other Tokens: $XXX (XX%)

3) Top Positions

Table format showing all positions sorted by value:

Protocol/Wallet | Position Type | Value | % Portfolio
----------------|---------------|-------|------------
Wallet Assets   | Wallet        | $XXX  | XX%
Protocol A      | Lending       | $XXX  | XX%
Protocol B      | LP            | $XXX  | XX%

4) Top Holdings (>2% of portfolio)

Table format:

Chain | Asset | Type | Amount | Value | % Portfolio
------|-------|------|--------|-------|------------

5) DeFi Exposure

For each protocol with 🟡 Medium or 🔴 High risk only (skip 🟢 Low risk):

Protocol Name (Chain)
• Position Value: $XXX (XX% of portfolio)
• Position Type: Lending/Staking/LP/etc.
• Risk: 🟡/🔴
• TVL: $XXX (DefiLlama)
• Audit: Yes/No (auditor names)
• Recent Issues: None / [describe]

If all protocols are low risk, output: "All DeFi positions are in low-risk protocols (🟢)"

6) Risk Summary

High Priority:

• List any 🔴 high-risk positions with recommended actions

Medium Priority:

• List any 🟡 medium-risk positions with considerations

Overall Assessment:

• One paragraph summary
• Risk score: Low/Medium/High

7) Data Sources

• Zerion API: Portfolio data (timestamp)
• DefiLlama: Protocol TVL and info
• Rekt.news: Security incidents
• [Other sources used]

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Quality Standards

Conciseness:

• Total report: 200-400 words (excluding tables)
• Focus on actionable insights only
• No filler or generic statements

Accuracy:

• All data must have timestamps
• All values must come from real API calls
• Risk assessments must cite specific evidence

Usefulness:

• Highlight positions >5% of portfolio
• Flag any high-risk exposure immediately
• Provide clear next actions if needed

---

Update Frequency

• Risk database: Update monthly with rekt.news
• Known protocols: Update as new major protocols launch
• Audit status: Verify quarterly

Last updated: 2026-02-05