Render, preprocess, detect patterns, and annotate chart images.
npx skills add https://github.com/mahmoud20138/Tradecraft --skill chart-vision
Please help me install this Agent Skill. Skill: chart-vision Source: https://github.com/mahmoud20138/Tradecraft/tree/main/plugins/tradecraft/skills/chart-vision Command: npx skills add https://github.com/mahmoud20138/Tradecraft --skill chart-vision
Chart data and visuals often live in images or screenshots. This skill provides an end-to-end pipeline to render OHLCV data into high-quality charts, preprocess screenshots to clean noise, detect candlestick and classical chart patterns, identify trendlines and S/R zones, and annotate results back onto the chart for reporting and analysis.
Render an OHLCV chart from data or a screenshot, then preprocess, detect patterns and trendlines, and output an annotated chart image.
High-intent search queries and answers about installing and using this skill.
To detect candlestick patterns from a chart screenshot, you can preprocess the image to clean noise and then apply vision-based pattern detection. This pipeline identifies classical chart patterns and outputs an annotated chart image for analysis.
Yes, you can render OHLCV data into a high-quality chart image using the mplfinance rendering stage. This transforms raw financial data into visual charts that can then be preprocessed, analyzed, and annotated.
The best way to identify trendlines and support resistance zones in an image is through a dedicated trendline and S/R vision analysis stage. This detects key levels directly from chart visuals and overlays them as annotations.
Yes, the chart image analysis pipeline works with OpenCV and scikit-image for preprocessing. These libraries are used to clean screenshot noise and prepare images for accurate pattern detection and annotation overlay.
You overlay annotations onto a chart for reporting by running detected patterns and trendline results through an annotation overlay stage. This generates a final annotated chart image that highlights candlestick patterns and S/R zones.
A limitation of vision-based pattern detection on financial charts is its reliance on image preprocessing quality; noisy screenshots can hinder accurate candlestick pattern identification and trendline analysis, requiring clean inputs for reliable annotated outputs.
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