Gate Info Addresstracker

gate-info-addresstracker

The on-chain detective Skill. The user inputs an on-chain address; the system first calls the address info Tool to get the profile, then based on user intent depth (simple query vs. fund tracing) decides whether to additionally call transaction history and fund flow tracing Tools.

Trigger Scenarios: User provides an on-chain address (0x... / bc1... / T... format) or explicitly expresses intent to track/query an address.

Routing Rules

Execution Workflow

Step 1: Intent Recognition & Parameter Extraction

Extract from user input:

• address: On-chain address (auto-detect format)
• chain (optional): Chain type (ETH/BSC/TRX/BTC, etc. — can be auto-inferred from address format)
• intent_depth: User intent depth
  • basic — just asking "who is this" / "how much do they hold"
  • deep — requesting "track funds" / "show transactions" / "where did the money go"

Automatic Address Format Detection:

Step 2: Phase 1 — Address Profile (Required)

Step 3: Decision Branch

get_address_info response
    │
    ├── User only wants a simple query (intent_depth = basic)
    │   └── → Output address profile report directly (skip to Step 5)
    │
    └── User requests deep tracking (intent_depth = deep)
        └── → Proceed to Step 4 parallel calls

Conditions for automatic upgrade to deep mode:

• Address has known labels (e.g., exchange, hacker, whale) → likely worth investigating
• Address balance > $1M
• Address has risk flags

Step 4: Phase 2 — Deep Tracking (Conditionally Triggered)

Both Tools called in parallel. min_value_usd thresholds are adaptively adjusted based on address size.

Adaptive Threshold Logic:

Step 5: LLM Aggregation

Report Template

Basic Mode

## Address Analysis Report

> Address: `{address}`
> Chain: {chain}
> Query time: {timestamp}

### 1. Address Profile

| Metric | Value |
|--------|-------|
| Address Label | {label} (e.g., Exchange Hot Wallet / Whale / Unknown / Hacker-linked) |
| Risk Score | {risk_score}/100 ({Low Risk/Medium Risk/High Risk}) |
| First Transaction | {first_tx_time} |
| Total Transactions | {tx_count} |
| Current Balance | ${total_balance_usd} |

### 2. Asset Holdings

| Token | Amount | Value (USD) | Share |
|-------|--------|-------------|-------|
| {token_1} | {amount} | ${value} | {pct}% |
| {token_2} | ... | ... | ... |
| ... | ... | ... | ... |

**Holding Characteristics**: {LLM analyzes the holding structure, e.g., "Highly concentrated in ETH", "Diversified across multiple DeFi tokens", "Possible market maker"}

### 3. DeFi Positions (if available)

| Protocol | Type | Amount | Status |
|----------|------|--------|--------|
| {protocol} | {Lending/LP/Staking} | ${value} | {Healthy/Near Liquidation} |
| ... | ... | ... | ... |

### 4. PnL Summary (if available)

| Metric | Value |
|--------|-------|
| Realized PnL | ${realized_pnl} |
| Unrealized PnL | ${unrealized_pnl} |
| Win Rate | {win_rate}% |

Deep Tracking Mode (appended to Basic Mode)

### 5. Large Transaction History

> Filter: Amount > ${min_value_usd} | Most recent {count} transactions

| Time | Type | Amount | Counterparty | Counterparty Label |
|------|------|--------|--------------|-------------------|
| {time} | {In/Out/Contract Interaction} | ${value} | `{counterparty}` | {label/unknown} |
| ... | ... | ... | ... | ... |

**Transaction Pattern Analysis**:
{LLM analyzes transaction records and identifies patterns:}
- Frequent interactions with an exchange → likely depositing/withdrawing
- Large one-way outflows → possibly liquidating
- Interacting with many new addresses → possibly dispersing funds
- Regular fixed-amount transfers → possibly payroll/OTC

### 6. Fund Flow Tracing

> Trace depth: {depth} levels | Minimum amount: ${min_value_usd}

{address} (origin) ├── ${amount} → {addr_1} ({label_1}) │ ├── ${amount} → {addr_1a} ({label}) │ └── ${amount} → {addr_1b} ({label}) ├── ${amount} → {addr_2} ({label_2}) │ └── ${amount} → {addr_2a} ({label}) └── ${amount} → {addr_3} ({label_3})

**Fund Flow Analysis**:
{LLM analysis based on tracing results:}
- Ultimate destination of funds (exchange? mixer? DeFi protocol?)
- Any suspicious patterns (split transfers, circular transfers, obfuscation paths)
- Associated known entities

### ⚠️ Risk Warnings

{If the address has risk flags, prominently display:}
- ⚠️ This address is flagged as: {risk_label}
- ⚠️ Associated addresses involved in: {risk_detail}

Decision Logic

Error Handling

Cross-Skill Routing

Safety Rules

1. Privacy protection: Do not link on-chain addresses to specific natural persons (unless publicly labeled as institutional addresses)
2. Clear risk warnings: High-risk addresses must have prominent, unmistakable risk labels with reasons
3. No definitive characterization: Do not use terms like "criminal address" or "dirty money" — use objective language like "flagged as high risk" or "associated with suspicious activity"
4. Data source transparency: Label data sources (BlockInfo / Nansen / Arkham) must be attributed
5. Flag missing data: Fund tracing rolls out in phases; when unavailable, explicitly state it
6. Do not encourage stalking: If a user attempts to track many personal addresses for harassment purposes, prompt responsible use