--- 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) ```bash # Get first 100 transfers of a token TOKEN="0xTokenContractAddress" curl -s "https:\/\/api.etherscan.io\/api?module=account&action=tokentx&contractaddress=${TOKEN}&page=1&offset=100&sort=asc&apikey=YourKey" | \ python3 -c " import sys, json from collections import Counter data = json.load(sys.stdin) buyers = Counter() for tx in data.get('result', []): buyers[tx['to']] += 1 print('=== Early Buyers ===') for addr, count in buyers.most_common(20): print(f'{addr} | {count} buys')" ``` ### Solana (SPL Token) ```bash # Find early holders using Birdeye API curl -s "https:\/\/public-api.birdeye.so\/public\/token_holder?address=TOKEN_MINT&offset=0&limit=20" \ -H "X-API-KEY: your-birdeye-key" | python3 -m json.tool ``` ## Analyze Deployer Activity ```bash # Find what else deployer created DEPLOYER="0xDeployerAddress" curl -s "https:\/\/api.etherscan.io\/api?module=account&action=txlist&address=${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 ```bash 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 ```bash 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 ```bash # 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 ```bash 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 ```bash 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 ```bash # Etherscan labels curl -s "https:\/\/api.etherscan.io\/api?module=account&action=balance&address=ADDRESS&tag=latest&apikey=YourKey" ``` ### Arkham Intelligence (API) ```bash 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 ```bash 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: ```sql -- 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