An AI trading coach that converts broker CSV exports into professional review reports with 8-dimensional scoring and deep pattern insights.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install trading-coach
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 trading-coach 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 Trading Coach?
Trading Coach is a specialized tool designed for serious traders who want to move beyond basic profit and loss tracking. By utilizing Openclaw Skills, this agent automates the tedious process of reconstructing trade lifecycles from raw broker data. It supports major platforms like Futu, Tiger Securities, and CITIC, making it a versatile choice for global investors.
The core of the skill lies in its ability to synthesize complex market data into professional-grade reports. It doesn't just show you what happened; it explains why. By analyzing entries and exits against technical indicators and risk parameters, this Openclaw Skills implementation provides a data-driven path to improving your trading discipline and market edge.
Trading Coach Use Cases
- Automatically converting Futu or Tiger Securities CSV exports into structured trade journals.
- Evaluating the quality of entries and exits based on RSI, MACD, and Bollinger Bands.
- Detecting behavioral biases such as impulsive trading or chasing overbought stocks.
- Calculating accurate FIFO-based profit and loss statistics for complex portfolios.
- Generating deep-dive AI reports to identify the root causes of trading losses.
How Trading Coach Works
- The user provides a broker-generated CSV file containing trade history.
- The system imports the data, automatically detecting the broker format and encoding (UTF-8 or GBK).
- It executes a FIFO (First-In-First-Out) matching algorithm to pair buys and sells into completed position cycles.
- Each position is processed through a scoring engine that evaluates performance across 8 weighted dimensions.
- An AI analysis layer interprets the scores to identify 10 dimensions of insight, such as risk control and holding duration.
- The tool outputs a comprehensive summary including win rates, P/L, warnings, and specific improvement suggestions.
Trading Coach Setup
To get started with this skill, ensure you have a Python environment ready. Follow these steps to install the necessary Openclaw Skills components:
# Clone the repository
git clone https://github.com/BENZEMA216/tradingcoach.git ~/tradingcoach
cd ~/tradingcoach
# Initialize environment and install dependencies
python3 -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt && cp config_template.py config.py
# Execute the analysis pipeline
python scripts/import_trades.py /path/to/trades.csv
python scripts/run_matching.py
python scripts/score_positions.py --all
python scripts/analyze_scores.py
Trading Coach Data Schema & Taxonomy
The skill organizes trading data into a structured taxonomy for precise evaluation. The following table describes the primary data points processed by these Openclaw Skills:
| Data Category | Purpose | Included Metrics |
|---|---|---|
| Raw Trades | Import baseline | Symbol, Side, Price, Quantity, Time |
| Position Lifecycle | Performance tracking | Entry/Exit Time, Duration, Net P/L |
| Quality Scores | Technical audit | RSI/MACD alignment, R:R Ratio, Slippage |
| AI Insights | Strategic advice | Pattern recognition, Root cause analysis |
Trading Coach Advanced Features
- Intelligent broker detection supporting Futu (CN/EN), Tiger, CITIC, and Huatai formats.
- Weighted scoring system covering Entry Quality (18%), Exit Quality (17%), and Risk Management (12%).
- Automated MAE/MFE (Maximum Adverse/Favorable Excursion) tracking to refine stop-losses.
- Multi-dimensional pattern recognition to detect news-driven consistency and market environment adaptation.
- Behavioral audit features to flag impulsive trades and lack of discipline.
SKILL.md
Loading
Related Openclaw Skills
RSS AI Reader
An intelligent RSS and Atom feed reader that uses LLMs to generate summaries and delivers them through multiple notification channels.
Options Analyzer
A professional-grade options strategy analyzer providing real-time market data, Greeks calculation, and intelligent strategy recommendations.
Clawdio
Clawdio provides auditory perception for AI agents, converting human audio into structured data, semantic reports, and machine-readable markdown.
Clawdio
Clawdio transforms Twitter Spaces and voice conversations into structured, machine-readable intelligence for AI agents.
Tavily AI Search
A specialized search engine skill designed to provide Large Language Models with clean, structured web data and synthesized AI answers.
Instagram Reel Downloader for WhatsApp
Download Instagram Reels via browser automation and send them as WhatsApp-ready videos using Openclaw Skills.
Featured*
