Detect market structure shifts and liquidity imbalances in OHLCV data.
npx skills add https://github.com/santoosaraujo/vibe-trading-claude --skill smc-santoosaraujo
Please help me install this Agent Skill. Skill: smc Source: https://github.com/santoosaraujo/vibe-trading-claude/tree/main/.claude/skills/smc Command: npx skills add https://github.com/santoosaraujo/vibe-trading-claude --skill smc-santoosaraujo
This Skill addresses the difficulty of identifying institutional market behavior by automating the detection of complex price action patterns that signal trend shifts and continuations.
Use the smc skill to analyze the latest market data for BTC-USDT and identify current structural signals.
High-intent search queries and answers about installing and using this skill.
To detect Break of Structure (BOS) and Change of Character (ChoCH) in OHLCV market data, this Skill automates institutional market structure analysis to map trend shifts and continuations using the smartmoneyconcepts library and pandas for data manipulation.
The best way to identify Fair Value Gaps (FVG) and Order Blocks for algorithmic trading is using this Skill to pinpoint liquidity imbalances in financial time-series data, generating high-probability entry and exit signals by filtering out market noise.
Yes, you can use pandas and numpy to scan multiple assets for institutional trading signals. This Skill leverages these dependencies to process OHLCV datasets, requiring both structural confirmation and FVG alignment to filter out noise.
Yes, the Python smartmoneyconcepts library supports liquidity imbalance detection in financial time-series. This Skill implements it to automatically identify complex price action patterns that signal institutional trend shifts and continuations.
Automated market structure analysis helps filter out noise in algorithmic trading by requiring both structural confirmation and FVG alignment to validate institutional behavior, addressing the difficulty of identifying high-probability entry and exit zones manually.
santoosaraujoAggregate trend, mean-reversion, and volume-price indicators into composite trading signals.
ebrahim-saniDetect BOS, ChoCH, FVG, and order block signals from OHLCV pandas DataFrames.
kayzaaCalculate portfolio risk metrics including VaR, Sharpe ratio, and position sizing.
0xZKnwAnalyze OHLCV market data to detect structural breaks, liquidity zones, and price imbalances.
