A sophisticated visual monitoring system for Slay the Spire 2 that utilizes screen capture and OCR to provide real-time combat data and DPS statistics.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install sts2-vision
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 sts2-vision 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 STS2 Vision Monitor?
STS2 Vision Monitor is a powerful extension designed for the Slay the Spire 2 ecosystem. It bridges the gap between raw gameplay and actionable data by employing computer vision to monitor the game state directly from the screen. By integrating this into your Openclaw Skills collection, you gain the ability to track health points, damage output, and complex combat metrics without needing direct memory access to the game client.
This skill is particularly valuable for players looking to optimize their deck builds or streamers who want to provide live statistics to their audience. It leverages modern Python libraries to ensure low-latency performance, turning visual pixels into structured JSON data for immediate analysis.
STS2 Vision Monitor Use Cases
- Tracking real-time DPS (Damage Per Second) to evaluate deck efficiency during combat.
- Automating combat data logging for long-term strategy analysis and run comparisons.
- Monitoring player HP levels to trigger external alerts or automated reactions.
- Generating structured JSON combat reports for integration with personal gaming dashboards.
How STS2 Vision Monitor Works
- The skill identifies and hooks into the active Slay the Spire 2 game window.
- It captures high-frequency screenshots of specific Regions of Interest (ROIs) defined in the configuration.
- The raw image data is processed using OpenCV and OCR engines to extract numerical values like HP and damage numbers.
- Extracted data is fed into a statistical engine that calculates real-time DPS and cumulative combat totals.
- The final metrics are outputted as structured JSON reports for use in other Openclaw Skills or external tools.
STS2 Vision Monitor Setup
To get started with this monitor, ensure you have the necessary Python dependencies installed and your game window is visible.
# Install required dependencies
pip install mss opencv-python numpy
# Note: pytesseract may be required for specific OCR tasks
# Calibrate the Regions of Interest (ROI)
python sts2_vision/main.py --calibrate
# Launch the monitoring system
python sts2_vision/main.py
STS2 Vision Monitor Data Schema & Taxonomy
The skill organizes its configuration and output through a structured file system and JSON schema. Key components include:
| Component | Description |
|---|---|
config.json |
Defines FPS, window target, and coordinate-based ROIs for visual tracking. |
Real-time Stats |
Live stream of HP and Damage values extracted from the screen. |
Combat Reports |
Cumulative session data exported in JSON format for analysis. |
ROI Schema Example:
player1_hp: Defined by x, y coordinates and width/height dimensions.
STS2 Vision Monitor Advanced Features
- Custom ROI Calibration: Precise tool to map specific areas of the game UI for data extraction.
- High-Frequency Sampling: Configurable FPS settings to balance system load with data accuracy.
- Extensible OCR Engine: Support for pytesseract and other vision processing backends within Openclaw Skills.
- JSON Exporting: Automated generation of machine-readable combat logs for post-game review.
SKILL.md
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