A powerful interface for querying real-time TradingView market data and technical indicators for global stocks and ETFs.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install tvscreener
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 tvscreener 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 tvscreener?
The tvscreener skill provides a robust bridge between AI agents and TradingView's extensive market data. It allows users to programmatically retrieve stock data, ETF information, and a wide array of technical indicators for markets including Hong Kong, China (A-shares), and the United States. This skill is essential for developers building financial analysis tools or automated trading strategies within the Openclaw Skills ecosystem. By leveraging the deepentropy/tvscreener library, this tool enables high-fidelity market scanning and field discovery. It simplifies the process of fetching complex technical ratings and moving averages, making it a cornerstone for data-driven financial decision-making.
tvscreener Use Cases
- Fetching real-time price and volume data for specific HK, US, or A-share symbols.
- Analyzing technical indicators such as RSI, MACD, and Bollinger Bands for market trend identification.
- Filtering stocks based on custom criteria like price changes or specific technical ratings.
- Discovering available TradingView fields and indicators for customized market research.
- Monitoring A-share ETFs and major stocks like Tencent or Moutai using pre-built Openclaw Skills scripts.
How tvscreener Works
- The user installs the required Python dependencies and the tvscreener library.
- Queries are initiated via provided shell scripts or Python scripts targeting specific markets such as HONGKONG, CHINA, or US.
- The skill interfaces with TradingView screeners to fetch raw data based on symbols, fields, and filters.
- Technical indicators are computed or retrieved directly from the screener's output.
- The resulting data is returned in a structured format suitable for further analysis or agent processing within the Openclaw Skills environment.
tvscreener Setup
Ensure you are using Python 3.10 or higher. Install the necessary package using pip:
python3 -m pip install -U tvscreener
You can verify the installation and connectivity by running the included regression test script:
bash scripts/test_markets.sh
tvscreener Data Schema & Taxonomy
The skill organizes market data into clear categories for easy consumption:
| Category | Field Examples | Description |
|---|---|---|
| Core Market | PRICE, VOLUME, CHANGE_PERCENT | Basic real-time market price and volume metrics. |
| Technicals | RSI_14, MACD_LEVEL, STOCHASTIC | momentum and trend-based oscillators. |
| Averages | SMA_20, EMA_50, SMA_200 | Simple and Exponential moving averages. |
| Descriptive | NAME, EXCHANGE, SYMBOL | Essential identification metadata for assets. |
| Ratings | MOVING_AVERAGES_RATING | Aggregated technical buy/sell sentiment ratings. |
tvscreener Advanced Features
- Comprehensive multi-market support for HONGKONG, CHINA, and US exchanges within Openclaw Skills.
- Field discovery tool to search and identify specific indicator keywords via the discover_fields.py script.
- Support for interval-based technical analysis (e.g., RSI|60) to view data across different timeframes.
- Flexible filtering logic allowing users to use comparison operators like equal, greater than, or less than for refined results.
- Direct Python API access for building custom complex financial logic beyond the provided shell scripts.
SKILL.md
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