A comprehensive multi-market stock scanning system that performs technical indicator analysis and generates scored reports directly in your Obsidian vault.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install tradingviewscanner
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 tradingviewscanner 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 Stock Scanner?
Stock Scanner is a professional-grade technical analysis tool designed for traders who manage watchlists within Obsidian. By leveraging TradingView data, it performs high-speed scans across A-shares, Hong Kong, US, and Japanese markets. This Openclaw Skills integration bridges the gap between raw market data and actionable insights by calculating 14 distinct technical signals, including MA crossovers, RSI, MACD, and volume breakouts.
The skill provides a systematic scoring engine that evaluates stocks on a scale of 0-100, helping users filter through market noise to find high-probability setups. It is specifically built to work with Obsidian, reading your existing watchlist CSV files and outputting beautifully formatted Markdown and Excel reports for daily review.
Stock Scanner Use Cases
- Daily technical screening of personal stock watchlists across global markets.
- Automated generation of technical signal reports (Daily Technical Analysis Reports).
- Identifying trend reversals, overbought/oversold conditions, and volume breakouts.
- Multi-market portfolio monitoring within a unified Obsidian research environment.
How Stock Scanner Works
- The AI agent initializes the environment and ensures all necessary Openclaw Skills dependencies are installed.
- It reads the user's watchlist CSV located within the specified Obsidian vault path.
- The system fetches real-time OHLCV daily candle data from TradingView for every ticker in the list.
- A specialized Python engine calculates 14 technical indicators and assigns a weighted score to each stock.
- Technical signals are aggregated into a Markdown report (and optional Excel file).
- The final report is saved back to the Obsidian vault and presented to the user through the chat interface.
Stock Scanner Setup
First, ensure you have the required Python libraries installed:
pip install tradingview_ta pandas numpy requests openpyxl --break-system-packages
To run the scanner manually through your terminal, use the following command structure:
python /path/to/skill/scripts/scanner.py \
--csv "<obsidian_vault>/<watchlist_path>" \
--output "<obsidian_vault>/<output_dir>" \
--workers 6
You will need to define your obsidian_vault path and watchlist_path during the first run.
Stock Scanner Data Schema & Taxonomy
The skill relies on a standardized CSV format for the watchlist and produces structured Markdown reports.
Watchlist CSV Requirements
| Column | Required | Description | Example |
|---|---|---|---|
| ticker | Yes | TradingView formatted symbol | AAPL, 0700.HK, 600519.SS |
| name | No | Friendly name of the stock | Apple, Tencent |
| market | No | Market identifier | US, HK, A-Share |
Output Files
- Markdown Report: A daily summary containing signal tables and the composite scores.
- Excel Export (Optional): A spreadsheet version of the scan for deeper data manipulation.
Stock Scanner Advanced Features
- Multi-threaded execution with support for 6 concurrent workers to bypass rate limits efficiently.
- Comprehensive 100-point scoring system covering Trend, Momentum, and Volume/Price dynamics.
- Support for Weekly K-line resonance and daily/weekly trend synchronization.
- Automation ready: Can be scheduled via local cron jobs for fully autonomous daily reporting.
- Regional suffix support for precise market targeting (.SS/.SZ for China, .HK for Hong Kong, .T for Japan).
SKILL.md
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