Search

PythonReactSEOPDF
OpenClaw

meme-risk-radar-skill

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.

26636295310 source installs☆ 0 Repository stars

Installation

Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.

SkillHub CLI

skillhub install 2663629531/meme-risk-radar-skill

Inspect the source and compatibility requirements, then follow its installation steps.

Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.

View source ↗Guides

Skill instructions

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:

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. -...

Source information

Source
github
Repository
openclaw/skills
Path
skills/2663629531/meme-risk-radar-skill
Version
—
Commit
5a204f6169cc34cec09fd2af7ffdc7348db14ed6
Classification source
rules
Status
active
Visibility
public

These signals come from indexed source analysis and may lag behind changes. Check the current source files.

README

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.

Extracted content

SKILL.md
# 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.
-...
README
# 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.

Related skills

OpenClaw

humanpages

human-pages-ai

Search and hire real humans for tasks — photography, delivery, research, and more

OpenClaw

openclaw-skills

zseven-w

Reusable skill templates for OpenClaw AI agents. Templates for API integration, data processing, web scraping, CLI tools, and file processing.

OpenClaw

firecrawl

capt-marbles

Web scraping and crawling with Firecrawl API. Fetch webpage content as markdown, take screenshots, extract structured data, search the web, and crawl documentation sites. Use when the user needs to scrape a URL...