Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub ยท Developer Tools
WhaleWatch CLI
Agent-native whale wallet tracker for ETH and BTC chains. Track large crypto wallet movements, score whale activity, detect accumulation/distribution pattern...
skill openclawclawhub Free
Agent-native whale wallet tracker for ETH and BTC chains. Track large crypto wallet movements, score whale activity, detect accumulation/distribution pattern...
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- Tencent SkillHub
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- SKILL.md, scripts/whale_scan.py
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- Tencent SkillHub
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- 0.1.0
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Documentation
WhaleWatch CLI โ Agent Skill
Track crypto whale movements. Close the loop from on-chain signal โ agent reasoning โ prediction market bet.
Install
uv pip install whalecli
Quick Start
# Initialize config (creates ~/.config/whalecli/config.toml) whalecli config init # Set API key (free tier: 5 req/sec) whalecli config set api.etherscan_api_key YOUR_KEY # Add a whale wallet whalecli wallet add 0xd8dA6BF26964aF9D7eEd9e03E53415D37aA96045 --label "vitalik.eth" --chain ETH # Scan all wallets (last 24h) whalecli scan --format json # Stream real-time alerts (JSONL, one event per line) whalecli stream --chain ETH --interval 60
When to Use
Trigger phrases: "What are the whales doing?" "Check whale activity on ETH/BTC" "Are whales accumulating or distributing?" "Any large wallet movements?" "What's the on-chain signal?" "Run a whale scan" Automatic triggers (no user prompt needed): Every 60 minutes during market-active hours (via heartbeat) Before placing a Simmer/Polymarket bet (pre-bet whale sanity check) When fear/greed index crosses a threshold (corroboration)
whalecli scan โ One-shot whale analysis
whalecli scan --chain ETH --hours 4 --threshold 70 --format json Output (JSON): { "scan_id": "scan_20260222_103015_a1b2", "chain": "ETH", "window_hours": 4, "wallets": [ { "address": "0xd8dA...", "label": "vitalik.eth", "score": 82, "direction": "accumulating", "score_breakdown": { "net_flow": 35, "velocity": 20, "correlation": 15, "exchange_flow": 12 }, "net_flow_usd": 15000000, "tx_count": 12 } ], "summary": { "total_wallets": 5, "accumulating": 3, "distributing": 1, "neutral": 1, "avg_score": 65 }, "alerts_triggered": 2 }
whalecli stream โ Real-time JSONL streaming
whalecli stream --chain ETH --interval 60 --threshold 70 Events (one JSON per line): stream_start โ stream initialized whale_alert โ score exceeded threshold whale_activity โ activity detected below threshold heartbeat โ periodic health check stream_end โ clean shutdown
whalecli wallet โ Manage tracked wallets
whalecli wallet add 0x... --label "whale1" --chain ETH whalecli wallet list --format json whalecli wallet remove 0x... whalecli wallet import wallets.csv
whalecli alert โ Configure alert rules
whalecli alert set --score 75 --webhook https://example.com/hook whalecli alert set --threshold 1000000 --window 1h whalecli alert list --format json
whalecli report โ Historical analysis
whalecli report --wallet 0x... --days 30 --format json
whalecli config โ Configuration management
whalecli config init whalecli config set api.etherscan_api_key YOUR_KEY whalecli config show
Exit Codes
CodeMeaning0Success (alerts found or scan complete)1No alerts (scan ran but nothing above threshold)2API error (rate limit, invalid key)3Network error (timeout, connection refused)4Data error (invalid address, wallet not found)
Scoring Algorithm
4-dimension whale scoring (0โ100 points): Net Flow (0โ40): USD net flow with log10 scaling, wallet age weighting Velocity (0โ25): Current activity vs 30-day baseline (log2 ratio) Correlation (0โ20): Peer wallet direction agreement (min 2 peers) Exchange Flow (0โ15): CEX address registry lookup + direction match Interpretation: 80โ100: Strong whale signal (high confidence) 60โ79: Moderate activity (worth monitoring) 40โ59: Low activity (noise) 0โ39: Minimal (ignore)
Agent Integration Pattern
import subprocess, json def whale_scan(chain="ETH", hours=4, threshold=70): """Run whale scan and return parsed results.""" result = subprocess.run( ["whalecli", "scan", "--chain", chain, "--hours", str(hours), "--threshold", str(threshold), "--format", "json"], capture_output=True, text=True, timeout=30 ) if result.returncode == 2: raise RuntimeError(f"API error: {result.stderr}") if not result.stdout.strip(): return {"wallets": [], "alerts_triggered": 0} return json.loads(result.stdout) # Example: pre-bet whale check scan = whale_scan(chain="ETH", hours=4) if scan["summary"]["accumulating"] > scan["summary"]["distributing"]: print("Whales accumulating โ bullish signal")
FearHarvester Integration
The closed loop: Fear & Greed โ Whale Signal โ Simmer Bet # 1. Get F&G value fg_value = get_fear_greed_index() # e.g., 8 (Extreme Fear) # 2. Check whale confirmation scan = whale_scan(chain="ETH", hours=4) whales_accumulating = scan["summary"]["accumulating"] > scan["summary"]["distributing"] # 3. If fear + whales accumulating โ strong contrarian signal if fg_value <= 20 and whales_accumulating: # Place bet on recovery market place_simmer_bet(market="btc_recovery", side="yes", amount=15)
Supported Chains
ETH โ Etherscan API (free tier: 5 req/sec) BTC โ Mempool.space (primary) + Blockchain.info (fallback) HL โ Hyperliquid perpetual fills and positions
Links
PyPI: https://pypi.org/project/whalecli/ GitHub: https://github.com/clawinfra/whalecli Issues: https://github.com/clawinfra/whalecli/issues
Category context
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
1 Docs1 Scripts
- SKILL.md
- scripts/whale_scan.py