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smc

Analyze OHLCV market data to detect structural breaks, liquidity zones, and price imbalances.

Updated Jun 30, 2026
Search Tags:#market analysis#finance#technical analysis#trading#ict#smc
One-click install
npx skills add https://github.com/0xZKnw/vibe-trading-tap --skill smc-0xzknw
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: smc
Source: https://github.com/0xZKnw/vibe-trading-tap/tree/main/agent/src/skills/smc
Command: npx skills add https://github.com/0xZKnw/vibe-trading-tap --skill smc-0xzknw

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires smartmoneyconcepts, pandas, numpy, requests, and includes references (resource) components.

What problem does it solve?

This Skill addresses the difficulty of identifying institutional market behavior by automating the detection of complex price action patterns like structural breaks and liquidity gaps.

Core Features & Use Cases

  • Structural Analysis: Automatically identifies Break of Structure (BOS) and Change of Character (ChoCH) to determine trend direction.
  • Liquidity & Imbalance Detection: Pinpoints Fair Value Gaps (FVG) and Order Blocks (OB) to identify high-probability entry zones.
  • Use Case: A trader can use this to scan multiple assets for institutional-grade signals, filtering out noise by requiring both structural confirmation and FVG alignment.

Quick Start

Use the smc skill to analyze the latest market data for BTC-USDT and identify current structural trends and fair value gaps.

Frequently Asked Questions about smc

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

FAQPage Schema
How do I detect Fair Value Gaps and Order Blocks in OHLCV market data?▼

You can detect Break of Structure and Change of Character patterns by feeding OHLCV market data into this Skill, which automates the identification of structural breaks to determine trend direction and potential reversals.

Can I use pandas and numpy to identify institutional trading patterns like BOS and ChoCH?▼

Yes, you can use pandas and numpy to identify institutional trading patterns like BOS and ChoCH. This Skill relies on these libraries alongside the smartmoneyconcepts package to process market data and automate structural analysis.

What is the best way to scan multiple assets for structural breaks and liquidity zones?▼

The best way to scan multiple assets for structural breaks and liquidity zones is to use this Skill to filter out market noise, requiring both structural confirmation and Fair Value Gap alignment to generate high-probability trading signals.

Does this technical analysis approach support trend identification across various asset classes?▼

Yes, this technical analysis approach supports trend identification across various asset classes. It analyzes financial market data to detect institutional price action patterns for trend identification and reversal detection.

Do I need the smartmoneyconcepts library to analyze market structure and price imbalances?▼

Yes, you need the smartmoneyconcepts library to analyze market structure and price imbalances. It is a required dependency alongside pandas and numpy to process OHLCV data and generate actionable trading signals.

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