Binance Watchlist Scanner for Openclaw

A high-performance technical analysis tool that scans 20 Binance spot pairs and ranks them by real-time signal strength.

jamierossouw
v1.0.1
Feb 22, 2026
0
0
0

Install & Download

1. ClawHub CLI

The fastest way to install a skill directly from the registry.

npx clawhub@latest install binance-watchlist-scanner

2. Manual Installation

Copy the skill folder to one of these locations

Global
~/.openclaw/skills/
Workspace
<project>/skills/

Priority: Workspace > Local > Bundled

3. Prompt Installation

Copy this prompt to OpenClaw to install it automatically.

Help me install binance-watchlist-scanner 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 Binance Watchlist Scanner?

The Binance Watchlist Scanner is a specialized technical analysis utility designed to provide traders with an immediate overview of market momentum across major crypto assets. By utilizing public data, this skill eliminates the need for API key management, making it an accessible and secure choice for developers exploring Openclaw Skills. It evaluates 20 high-liquidity pairs, applying a multi-indicator scoring system to identify where the strongest buying or selling pressure exists.

This skill is particularly valuable for those who need to filter market noise and focus on high-probability setups. It processes complex data points from RSI, MACD, and Bollinger Bands into a human-readable ranked list, allowing users to spend less time charting and more time executing informed trades within their automated workflows.

Binance Watchlist Scanner Use Cases

  • Identifying the top 3 high-probability buy opportunities across the Binance spot market.
  • Rapidly screening a predefined watchlist for RSI divergence and EMA crossovers.
  • Automating technical sentiment checks during high-volatility trading sessions.
  • Ranking crypto assets by signal strength to prioritize capital allocation based on TA confluence.

How Binance Watchlist Scanner Works

  1. The skill triggers a comprehensive scan of 20 predefined Binance spot pairs using public data endpoints.
  2. It calculates six core technical indicators: RSI(14), MACD (12/26/9), EMA cross (9/21), Bollinger Bands (20), OBV divergence, and StochRSI(14).
  3. A weighted scoring algorithm processes these indicators to determine the overall signal strength for each asset.
  4. The assets are ranked from highest bullish potential to highest bearish risk.
  5. A summarized report is generated, displaying the pair, signal score, primary indicator status, and current price.

Binance Watchlist Scanner Setup

Integrating this tool into your environment is straightforward as it requires no private API credentials. To begin using this and other Openclaw Skills, follow these steps:

# Install the binance-watchlist skill
openclaw install binance-watchlist

# Run a manual scan to verify connectivity
openclaw run binance-watchlist --action scan

Ensure your agent has outbound internet access to reach the public Binance data nodes.

Binance Watchlist Scanner Data Schema & Taxonomy

The skill produces a structured output that categorizes market data into actionable trading intelligence. The data is organized as follows:

Field Description
Rank Score A numerical value (e.g., +4, -3) indicating signal strength
Symbol The Binance spot trading pair (e.g., SOL/USDT)
Primary Indicator The most significant technical trigger (e.g., MACD cross)
Price Data Real-time spot price at the time of the scan
Sentiment Descriptive tags like Overbought, Bull Cross, or BB Support

Binance Watchlist Scanner Advanced Features

  • Multi-indicator confluence scoring that combines momentum, trend, and volume metrics.
  • Zero-API dependency, allowing for immediate deployment without managing sensitive keys.
  • High-speed execution optimized to complete a 20-pair deep scan in under 30 seconds.
  • Seamless integration with other Openclaw Skills to trigger automated notifications or trade execution based on signal thresholds.

SKILL.md


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