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technical-basic

Aggregate trend, mean-reversion, and volume-price indicators into composite trading signals.

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

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, numpy, requests.

What problem does it solve?

This skill addresses the challenge of interpreting complex market data by synthesizing multiple technical indicators into a single, actionable trading signal.

Core Features & Use Cases

  • Three-Dimensional Analysis: Combines trend (EMA/ADX), mean-reversion (Bollinger Bands/RSI), and volume-price (OBV) metrics.
  • Composite Voting: Generates clear long, short, or neutral signals based on a multi-factor voting mechanism.
  • Use Case: A trader can use this to automatically filter out noise in volatile markets by requiring confirmation from both trend strength and volume participation before executing a trade.

Quick Start

Use the technical-basic skill to generate trading signals for the BTC-USDT pair using the latest market data.

Frequently Asked Questions about technical-basic

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

FAQPage Schema
How do I calculate composite trading signals from OHLCV market data?▼

To calculate composite trading signals from OHLCV market data, aggregate trend, mean-reversion, and volume-price indicators using multi-factor voting logic to determine long, short, or neutral market positions.

What is multi-factor voting logic in technical analysis?▼

Multi-factor voting logic in technical analysis synthesizes separate trend, mean-reversion, and volume-price metrics into a single actionable trading signal to filter market noise and confirm trade validity.

How do I combine RSI and ADX indicators to filter market noise?▼

Combine RSI and ADX indicators to filter market noise by implementing a three-dimensional analysis that requires confirmation from both trend strength and volume participation before generating a trade signal.

Can I use pandas and numpy to automate technical indicator analysis?▼

Yes, you can use pandas and numpy to automate technical indicator analysis by processing OHLCV market data arrays and calculating Wilder EWM smoothing for various financial instruments.

Does Wilder EWM smoothing work for generating cryptocurrency trading signals?▼

Wilder EWM smoothing works for generating cryptocurrency trading signals by calculating composite metrics across trend, mean-reversion, and volume-price dimensions for instruments like BTC-USDT.

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