insider-wallets-finder – OpenClaw Skill

---

name: insider-wallets-finder description: Find and analyze smart money addresses - discover early buyers, track successful traders, identify whale accumulation patterns, and research on-chain alpha. metadata: {"openclaw":{"requires":{"bins":["python3"]},"install":[{"id":"python","kind":"pip","package":"requests","bins":[],"label":"Install requests (pip)"}]}}

Insider Wallets Finder

Overview

Identify profitable addresses by analyzing:

• Early token buyers
• Consistent profitable traders
• Whale accumulation patterns
• DEX trading patterns
• NFT flippers

Find Early Buyers of Token

Ethereum (ERC-20)

# Get first 100 transfers of a token
TOKEN="0xTokenContractAddress"
curl -s "https://api.etherscan.io/api?module=account&action=tokentx&contractaddress=${TOKEN}&page=1&offset=100&sort=asc&apikey=YourKey" | \
python3 -c "
import sys, json
from collections import Counter
data = json.load(sys.stdin)
buyers = Counter()
for tx in data.get('result', []):
    buyers[tx['to']] += 1
print('=== Early Buyers ===')
for addr, count in buyers.most_common(20):
    print(f'{addr} | {count} buys')"

Solana (SPL Token)

# Find early holders using Birdeye API
curl -s "https://public-api.birdeye.so/public/token_holder?address=TOKEN_MINT&offset=0&limit=20" \
  -H "X-API-KEY: your-birdeye-key" | python3 -m json.tool

Analyze Deployer Activity

# Find what else deployer created
DEPLOYER="0xDeployerAddress"
curl -s "https://api.etherscan.io/api?module=account&action=txlist&address=${DEPLOYER}&sort=desc&apikey=YourKey" | \
python3 -c "
import sys, json
data = json.load(sys.stdin)
contracts = []
for tx in data.get('result', []):
    if tx['to'] == '' and tx['contractAddress']:
        contracts.append(tx['contractAddress'])
print('Deployed contracts:')
for c in contracts[:10]:
    print(c)"

Track Whale Accumulation

python3 << 'EOF'
import requests

TOKEN = "0xTokenAddress"
API_KEY = "YourEtherscanKey"

# Get top holders
url = f"https://api.etherscan.io/api?module=token&action=tokenholderlist&contractaddress={TOKEN}&page=1&offset=50&apikey={API_KEY}"
resp = requests.get(url).json()

print("=== Top Holders ===")
for holder in resp.get('result', [])[:20]:
    addr = holder['TokenHolderAddress']
    qty = float(holder['TokenHolderQuantity']) / 1e18
    print(f"{addr[:20]}... | {qty:,.2f}")
EOF

Find Profitable DEX Traders

Analyze Uniswap Trades

python3 << 'EOF'
import requests

# GraphQL query for top traders
query = """
{
  swaps(first: 100, orderBy: amountUSD, orderDirection: desc, where: {amountUSD_gt: "10000"}) {
    sender
    amountUSD
    token0 { symbol }
    token1 { symbol }
  }
}
"""

resp = requests.post(
    "https://api.thegraph.com/subgraphs/name/uniswap/uniswap-v3",
    json={"query": query}
).json()

from collections import Counter
traders = Counter()
for swap in resp.get('data', {}).get('swaps', []):
    traders[swap['sender']] += float(swap['amountUSD'])

print("=== High Volume Traders ===")
for addr, vol in traders.most_common(10):
    print(f"{addr[:20]}... | ${vol:,.0f}")
EOF

Solana DEX Analysis

Find Raydium/Jupiter Traders

# Using Birdeye API
curl -s "https://public-api.birdeye.so/public/txs/token?address=TOKEN_MINT&tx_type=swap&limit=50" \
  -H "X-API-KEY: your-key" | \
python3 -c "
import sys, json
from collections import Counter
data = json.load(sys.stdin)
traders = Counter()
for tx in data.get('data', {}).get('items', []):
    traders[tx.get('owner', '')] += 1
print('Active Traders:')
for addr, count in traders.most_common(10):
    print(f'{addr[:20]}... | {count} trades')"

NFT Flipper Analysis

python3 << 'EOF'
import requests

# OpenSea API - find profitable flippers
collection = "boredapeyachtclub"
url = f"https://api.opensea.io/api/v1/events?collection_slug={collection}&event_type=successful&limit=50"

resp = requests.get(url, headers={"Accept": "application/json"}).json()

from collections import defaultdict
profits = defaultdict(float)

for event in resp.get('asset_events', []):
    seller = event.get('seller', {}).get('address', '')
    price = float(event.get('total_price', 0)) / 1e18
    profits[seller] += price

print("=== Top Sellers ===")
for addr, total in sorted(profits.items(), key=lambda x: -x[1])[:10]:
    print(f"{addr[:20]}... | {total:.2f} ETH")
EOF

Cross-Reference Multiple Tokens

python3 << 'EOF'
import requests
from collections import Counter

API_KEY = "YourKey"
tokens = [
    "0xToken1",
    "0xToken2",
    "0xToken3"
]

all_early_buyers = Counter()

for token in tokens:
    url = f"https://api.etherscan.io/api?module=account&action=tokentx&contractaddress={token}&page=1&offset=50&sort=asc&apikey={API_KEY}"
    resp = requests.get(url).json()

    for tx in resp.get('result', []):
        all_early_buyers[tx['to']] += 1

print("=== Addresses in Multiple Early Buys ===")
for addr, count in all_early_buyers.most_common(20):
    if count >= 2:
        print(f"{addr} | {count} tokens")
EOF

Labeled Address Databases

Check Known Addresses

# Etherscan labels
curl -s "https://api.etherscan.io/api?module=account&action=balance&address=ADDRESS&tag=latest&apikey=YourKey"

Arkham Intelligence (API)

curl -s "https://api.arkhamintelligence.com/intelligence/address/ADDRESS" \
  -H "API-Key: your-arkham-key" | python3 -m json.tool

Pattern Detection

Find Addresses with Similar Behavior

python3 << 'EOF'
import requests
from datetime import datetime

TOKEN = "0xTokenAddress"
API_KEY = "YourKey"

# Get all transfers
url = f"https://api.etherscan.io/api?module=account&action=tokentx&contractaddress={TOKEN}&sort=asc&apikey={API_KEY}"
resp = requests.get(url).json()

# Group by timing
from collections import defaultdict
timing = defaultdict(list)

for tx in resp.get('result', []):
    block = int(tx['blockNumber'])
    timing[block // 100].append(tx['to'])  # Group by ~100 blocks

# Find coordinated buying
print("=== Potential Coordinated Buys ===")
for block_group, buyers in timing.items():
    if len(buyers) >= 3:
        unique = set(buyers)
        if len(unique) >= 3:
            print(f"Block ~{block_group * 100}: {len(unique)} unique buyers")
            for b in list(unique)[:5]:
                print(f"  {b}")
EOF

Research Tools

Tool	Purpose	Link
Nansen	Labeled addresses	nansen.ai
Arkham	Intel platform	arkhamintelligence.com
Bubblemaps	Holder visualization	bubblemaps.io
DeBank	Portfolio tracking	debank.com
Dune	Custom queries	dune.com
Birdeye	Solana analytics	birdeye.so

Dune Analytics Queries

Find smart money on Dune:

-- Top profitable traders
SELECT
  trader,
  SUM(profit_usd) as total_profit,
  COUNT(*) as trade_count
FROM dex.trades
WHERE block_time > now() - interval '7 days'
GROUP BY trader
HAVING SUM(profit_usd) > 10000
ORDER BY total_profit DESC
LIMIT 50

Notes

• All blockchain data is public
• Use for research and education
• Cross-reference multiple sources
• Patterns don't guarantee future performance
• Consider transaction fees in profit calculations
• Some "insiders" may be arbitrage bots
• Always verify findings manually