Overview
- Skill Key
- 2663629531/meme-risk-radar-skill
- Author
- 2663629531
- Source Repo
- openclaw/skills
- Version
- -
- Source Path
- skills/2663629531/meme-risk-radar-skill
- Latest Commit SHA
- 5a204f6169cc34cec09fd2af7ffdc7348db14ed6
Bilingual meme token risk radar for Binance Web3 data. Scan newly launched or fast-rising meme tokens from Meme Rush, enrich with token audit and token info, produce a normalized risk report in Chinese or English, and support SkillPay billing hooks for paid scan and audit calls.
Stars
0
Installs
0
Status
ACTIVE
Visibility
PUBLIC
直接复制以下提示词,发送给你的 AI 助手即可完成安装。
请先检查是否已安装 SkillHub 商店,若未安装,请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店,然后安装 meme-risk-radar-skill 技能。 若已安装,则直接安装 meme-risk-radar-skill 技能。
# Skill: meme-risk-radar-skill ## Purpose Use this skill to turn Binance Web3 meme discovery data into a tradable risk workflow. It is designed for users who want fast meme coverage, but need structured filtering before deciding whether to research further. Default output supports both `zh` and `en`. ## Product Positioning - Built for traders, researchers, alpha groups, and content operators who need faster meme token triage. - Focus on `risk-first discovery`: find candidates first, then downgrade obvious traps before deeper research. - Suitable for ClawHub-style paid usage because value is tied to each actionable scan, not to raw static content. ## Trust Posture - Read-only by default. This skill does not place orders or request exchange trading keys. - Secrets are read only from environment variables and are never hard-coded. - Output is explainable: every score is backed by visible signals such as holder concentration, dev share, liquidity, audit hits, and tax flags. - User-facing language must remain neutral. Never promise profits or "safe coins." ## Commands Run from the skill root: ```bash python3 scripts/meme_risk_radar.py scan --chain solana --stage new --limit 10 --lang zh python3 scripts/meme_risk_radar.py scan --chain bsc --stage finalizing --limit 5 --lang en --min-liquidity 10000 python3 scripts/meme_risk_radar.py audit --chain bsc --contract 0x1234... --lang en python3 scripts/meme_risk_radar.py health ``` ## Output Contract Each scan returns: - `chain` - `stage` - `lang` - `generated_at_utc` - `tokens[]` Each token entry contains: - `symbol` - `name` - `contract_address` - `score` - `risk_level` - `summary` - `signals[]` - `metrics` - `audit` - `links` ## Billing Hook (SkillPay) - Bill only `scan` and `audit`. - Read API key from `SKILLPAY_APIKEY`. - Default price is read from `SKILLPAY_PRICE_USDT` (default `0.002`). - Do not hard-code secrets. ## Suggested Monetization - Entry offer: charge per `scan` and per `audit`, keep `health` free. -...
# Meme Risk Radar Skill A bilingual meme token risk radar for Binance Web3 data. Scan newly launched or fast-rising meme tokens from Meme Rush, enrich with token audit and token info, produce a normalized risk report in Chinese or English, and support SkillPay billing hooks for paid scan and audit calls. ## Version Current version: **1.0.0** ## Features - Multi-chain Support: Base, BSC, Ethereum, Solana - Risk Assessment: Scoring system with multiple risk signals - Audit Integration: Token security audit from Binance Web3 - Proxy Support: Built-in proxy configuration for restricted networks - Billing Hooks: Optional SkillPay integration - Bilingual: Chinese and English output - Fast Scanning: Real-time meme token discovery - Structured Output: JSON format for easy integration ## Installation ### Prerequisites - Python 3.9+ - requests>=2.31.0 ### Setup 1. Clone or copy to OpenClaw skills directory 2. Install dependencies: pip install -r requirements.txt 3. Configure environment variables: cp .env.example .env 4. Create global command (optional) ## Usage ### Health Check meme-risk health ### Scan Meme Tokens meme-risk scan --chain bsc --stage new --limit 10 --lang zh ### Audit Single Token meme-risk audit --chain bsc --contract 0x1234... --lang zh ## Configuration See .env.example for available configuration options. ## Risk Scoring - 0-25: Low Risk - 26-50: Medium Risk - 51-75: High Risk - 76-100: Critical Risk ## Disclaimer LOW risk never means safe. This skill is a risk-filtering tool, not an execution tool. The report is a point-in-time snapshot. Do your own research (DYOR) before investing. Most meme tokens eventually go to zero. ## Changelog See CHANGELOG.md for detailed version history. ## Support For issues and questions, please use OpenClaw support channels.
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