smc

Detect BOS, ChoCH, and FVG signals from OHLCV data.

Updated Apr 9, 2026
One-click install
npx skills add https://github.com/JacobHsu/vibe-trading-agent --skill smc-jacobhsu
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: smc
Source: https://github.com/JacobHsu/vibe-trading-agent/tree/main/agent/src/skills/smc
Command: npx skills add https://github.com/JacobHsu/vibe-trading-agent --skill smc-jacobhsu

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Traders lack automated tools to interpret institutional structure shifts, so this Skill translates BOS, ChoCH, and FVG occurrences into clear long, short, or stand-aside signals to reduce analysis noise.

Core Features & Use Cases

  • Structure Detection: Identifies break of structure and change of character patterns using smartmoneyconcepts to reveal trend continuation and reversal points.
  • FVG Alignment: Applies fair value gap filtering so that only signals with supporting liquidity imbalances surface, improving conviction.
  • Use Case: Run the engine on BTC-USDT daily candles to quantify how often ChoCH triggers align with BOS confirmations and FVGs for swing trading.

Quick Start

Ask the smc skill to analyze BTC-USDT daily candles and return any long or short bias.

Frequently Asked Questions about smc

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I detect smart money concepts like BOS and ChoCH from OHLCV data?

Detect smart money concepts like BOS and ChoCH from OHLCV data by applying the smartmoneyconcepts library to process candlestick arrays, identifying structural shifts and translating them into clear long or short bias signals.

What is a fair value gap filter and how does it improve trading signal conviction?

A fair value gap filter improves trading signal conviction by cross-referencing BOS and ChoCH triggers with supporting liquidity imbalances, ensuring only structure shifts backed by FVG alignment surface to reduce market noise.

Can I run institutional structure detection on crypto and equity instruments?

You can run institutional structure detection on crypto and equity instruments by feeding daily OHLCV candles, such as BTC-USDT, into the signal engine to quantify trend continuation and reversal points across markets.

Do I need pandas and numpy to build an SMC signal engine?

You need pandas and numpy to build an SMC signal engine because the smartmoneyconcepts integration requires OHLCV preprocessing pipelines to structure candlestick data before detecting institutional patterns.

How to automate change of character pattern recognition for swing trading?

Automate change of character pattern recognition for swing trading by running the SMC engine on daily candles to quantify how often ChoCH triggers align with BOS confirmations and fair value gaps.

What are the limitations of using smartmoneyconcepts for trend reversal filtering?

Limitations of using smartmoneyconcepts for trend reversal filtering include signal lag inherent to OHLCV candle close requirements and potential false ChoCH triggers when FVG alignment is absent in volatile market conditions.