Analyze OHLCV market data to detect BOS, ChoCH, order blocks, and FVG patterns.
npx skills add https://github.com/OpenSucker/OpenSucker --skill smc-opensucker
Please help me install this Agent Skill. Skill: smc Source: https://github.com/OpenSucker/OpenSucker/tree/main/skills/vibe_skills/smc Command: npx skills add https://github.com/OpenSucker/OpenSucker --skill smc-opensucker
This Skill enables users to analyze market structure and generate trade signals based on institutional concepts, helping traders identify entry and exit points with greater confidence.
Provide OHLCV data for various assets; the Skill will analyze the market structure and output trading signals based on detected patterns.
High-intent search queries and answers about installing and using this skill.
To generate institutional trading signals, you provide OHLCV market data to analyze market structure using concepts like BOS, ChoCH, order blocks, and FVG. The system detects precise patterns to output buy or sell signals aligned with smart money behaviors.
Market structure analysis detects trend reversals and continuations by identifying Break of Structure (BOS) and Change of Character (ChoCH) signals. These pattern detections assess institutional trend dynamics to determine potential market direction shifts.
The best way to identify order blocks and fair value gaps is by analyzing OHLCV data for institutional order zones. The system detects these fair value gaps (FVG) to refine trade entries and pinpoint optimal execution levels.
Yes, you can use this market analysis for diverse market scenarios by inputting OHLCV data for various assets. It ensures detected institutional patterns meet the robustness required for real-time analysis across different financial markets.
Yes, you need OHLCV data to run smart money analysis. Providing Open, High, Low, Close, and Volume data allows the system to evaluate market structure and generate precise institutional trading signals.
Smart money concepts offer market analysis by tracking institutional footprints like order blocks and structure breaks, whereas traditional indicators often lag. This approach provides earlier entry and exit signals based on actual institutional trading behaviors.
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