Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
What This Skill Does
Analyzes Ethereum addresses for phishing, honeypots, rug pulls, and exploit group activity using a local SQLite database. Checks return results in under 5ms because queries never hit external APIs. A background sync worker pulls transaction data from Etherscan on a separate schedule.
Checks complete in under 5ms with no rate limits because all user queries hit a local database rather than live blockchain APIs.
When to use it
- Verifying a wallet address before sending ETH
- Screening a DeFi contract before approving a transaction
- Checking an airdrop sender for phishing indicators
- Vetting a crypto payment recipient before transferring funds
- Identifying known exploit group addresses before interacting
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: Is 0x098b716b8aaf21512996dc57eb0615e2383e2f96 safe to send ETH to?
- 1Run python3 crypto_check_db.py with the provided address
- 2Query local SQLite database for address record, risk score, and scam indicators
- 3Decode suspicious transaction messages and check for flagged keywords
- 4Return risk level, detected indicators, and action recommendations
Risk Score 100/100 - CRITICAL RISK. Five scam indicators detected including 'lazarus', 'hack', 'exploit', and 'private key' keywords. Recommends against sending funds.
Requirements
Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.