smc-python-library

Analyze ICT/SMC indicators on OHLC DataFrames with a Pandas API.

10|2|Updated Mar 8, 2026
One-click install
npx skills add https://github.com/mahmoud20138/Tradecraft --skill smc-python-library
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: smc-python-library
Source: https://github.com/mahmoud20138/Tradecraft/tree/main/plugins/tradecraft/skills/smc-python-library
Command: npx skills add https://github.com/mahmoud20138/Tradecraft --skill smc-python-library

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Analyses ICT/SMC indicators on OHLC data to support decision-making in trading workflows.

Core Features & Use Cases

  • Implements 8 indicators (FVG, Swing Highs/Lows, BOS/CHoCH, Order Blocks, Liquidity, Previous High/Low, Sessions, Retracements) for price analysis.
  • Provides a Pandas-friendly API to compute indicators on OHLC DataFrames and integrate into trading workflows.
  • Use case: detect confluence of indicators to identify high-probability trade setups on historical or streaming data.

Quick Start

Install the library with pip and import the smc module to analyze OHLC data.

Frequently Asked Questions about smc-python-library

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

FAQPage Schema
How do I calculate ICT SMC indicators on OHLC data in Python?▼

To calculate ICT SMC indicators on OHLC data in Python, use this library to apply concepts like FVG, BOS/CHoCH, Order Blocks, and liquidity directly to Pandas DataFrames for trading analysis.

What is confluence detection in SMC trading algorithms?▼

Confluence detection in SMC trading algorithms is identifying overlapping signals from indicators like Order Blocks, Fair Value Gaps, and liquidity to find high-probability trade setups on OHLC time series.

Can I use this SMC Python library with existing Pandas data pipelines?▼

Yes, you can use this SMC Python library with existing Pandas data pipelines because it provides a modular API designed to compute indicators directly on OHLC DataFrames across intraday to daily horizons.

What's the best way to detect Fair Value Gaps and Order Blocks in a Pandas DataFrame?▼

The best way to detect Fair Value Gaps and Order Blocks in a Pandas DataFrame is using this library's modular API, which computes 8 SMC indicators including FVG and OB on OHLC time series.

Does this Python ICT indicators library support streaming data analysis?▼

Yes, this Python ICT indicators library supports streaming data analysis, enabling confluence detection of SMC indicators on both historical and streaming OHLC data within trading workflows.