A professional-grade scoring engine for Openclaw Skills that automates meme token evaluation through a 6-dimensional analysis framework and paper trading simulation.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install meme-signal-evaluator
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install meme-signal-evaluator using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Meme Signal Evaluator?
The Meme Signal Evaluator is a sophisticated systematic scoring engine designed to help developers and traders navigate the volatile meme token market using Openclaw Skills. It synthesizes real-time market data into actionable intelligence by evaluating tokens across six critical dimensions: Smart Money, Social Hype, Price Trend, Volume Inflow, KOL/Whale activity, and viral Hype.
By integrating this skill into your workflow, you can automate the entire lifecycle of token discovery—from initial filtering and multi-dimensional scoring to strategy-based signal generation. This tool for Openclaw Skills is essential for building data-driven trading pipelines that replace emotional decision-making with quantifiable metrics and simulated backtesting capabilities.
Meme Signal Evaluator Use Cases
- Token Scoring: Automatically evaluate any meme token with a 0-100 composite score based on live API data.
- Strategy Matching: Configure multiple trading strategies with custom thresholds and entry modes to suit different risk profiles.
- Paper Trading Simulation: Run risk-free buy/sell simulations with automated take-profit and stop-loss logic.
- Watchlist Management: Efficiently track token lifecycles from initial discovery to final exit or dismissal.
- Performance Tracking: Analyze win rates and P&L statistics to refine your trading strategies within the Openclaw Skills ecosystem.
How Meme Signal Evaluator Works
- Data Collection: The engine triggers collectors for smart money, social hype, and meme trends to gather raw market signals.
- Global Filtering: New tokens are automatically passed through filters for market cap, liquidity, and token age to ensure quality.
- Multi-Dimension Scoring: Each token is scored from 0-100 across six independent dimensions using weighted algorithms.
- Strategy Priority: The system matches the total score against user-defined strategies, prioritizing higher-threshold setups.
- Automated Simulation: When a buy signal is triggered, the paper trader records the entry and monitors real-time price changes for exit conditions.
- Exit Execution: The system automatically executes simulated sells based on Take Profit, Stop Loss, or maximum hold time constraints.
Meme Signal Evaluator Setup
To deploy this skill within your Openclaw Skills environment, follow these installation steps:
# Navigate to your skills directory
cd path/to/openclaw/skills
# Clone the evaluator repository
git clone https://github.com/ls569333469/meme-signal-evaluator.git
# Install required dependencies
cd meme-signal-evaluator
npm install
After installation, configure your config.yaml to define your strategy weights and API credentials for Token Dynamic and Social Hype data sources. Ensure your scheduler is active to allow the 5-minute evaluation pipeline to run automatically.
Meme Signal Evaluator Data Schema & Taxonomy
The Meme Signal Evaluator organizes data into structured schemas to provide clear insights into token performance and strategy efficacy:
| Data Object | Key Fields | Purpose |
|---|---|---|
| Scoring Dimensions | SM, Social, Trend, Inflow, KOL, Hype | Individual metric scores (0-100). |
| Strategy Config | name, entryMode, buyThreshold, weights | Defines how signals are generated. |
| Trade Record | entryPrice, exitPrice, pnlPercent, exitReason | Tracks simulated trading performance. |
| Watchlist | status (watching/bought), marketCap, age | Manages the token discovery lifecycle. |
| Global Filters | minLiquidity, maxMarketCap, minHolders | Pre-scans tokens before evaluation. |
Meme Signal Evaluator Advanced Features
- Dynamic Weighting: Fully configurable weights for all six dimensions to customize the engine for different market regimes within Openclaw Skills.
- Negative Signal Penalties: Automated protection that deducts points or forces dismissal for high-risk factors like honeypots or high tax.
- Multi-Timeframe Resonance: Advanced logic that identifies trend confirmation across 5m, 1h, and 4h price windows.
- Strategy Priority Matching: A priority-based system that ensures your highest-conviction strategies are triggered first when scores overlap.
- Automated Pipeline: A recurring scheduler that automates the collection, scanning, and monitoring process without manual intervention in Openclaw Skills.
SKILL.md
Loading
Related Openclaw Skills
Imou Device Manager
A comprehensive management skill for Imou cloud devices that enables status monitoring, device listing, and metadata configuration.
Navigation Menu Generator
A specialized tool for designing, auditing, and optimizing website navigation menus for superior SEO performance and user accessibility.
Consulting Report Search
A specialized AI agent skill for searching, analyzing, and answering questions from professional industry and consulting reports.
Photo to 3D
A professional-grade pipeline that converts 2D photos into high-quality 3D models using a multi-stage AI workflow.
Magyar Formatter
A specialized localization tool for converting dates, numbers, and currencies into valid Hungarian formats.
Magyar Szótár
A comprehensive Hungarian dictionary and linguistic analysis tool designed for seamless AI agent integration.
Featured*
