Skills

Market Breadth Analyzer

Quantifies market breadth health using TraderMonty's public CSV data.

Install

npx skills add tradermonty/claude-trading-skills --skill market-breadth-analyzer -g -a claude-code -y
Category
Engineering
Updated
3d ago
License
MIT
Context cost
Mediumabout 1,649 tokens
Runs scripts
Yes, review before use

What it does

Quantifies market breadth health using TraderMonty's public CSV data. Generates a 0-100 composite score across 6 components (100 = healthy). No API key required. Use when user asks about market breadth, participation rate, advance-decline health, whether the rally is broad-based, or general market health assessment.

Market Breadth Analyzer Skill

Purpose

Quantify market breadth health using a data-driven 6-component scoring system (0-100). Uses TraderMonty's publicly available CSV data to measure how broadly the market is participating in a rally or decline.

Score direction: 100 = Maximum health (broad participation), 0 = Critical weakness.

No API key required - uses freely available CSV data from GitHub Pages.

When to Use This Skill

English:

  • User asks "Is the market rally broad-based?" or "How healthy is market breadth?"
  • User wants to assess market participation rate
  • User asks about advance-decline indicators or breadth thrust
  • User wants to know if the market is narrowing (fewer stocks participating)
  • User asks about equity exposure levels based on breadth conditions

Japanese:

  • 「マーケットブレッドスはどうですか?」「市場の参加率は?」
  • 「上昇は広がっている?」「一部の銘柄だけの上昇?」
  • ブレッドス指標に基づくエクスポージャー判断
  • 市場の健康度をデータで確認したい

Prerequisites

  • Python 3.9+ with requests library (for fetching CSV data)
  • Internet access to reach GitHub Pages URLs
  • No API keys required - uses freely available public CSV data

Difference from Breadth Chart Analyst

AspectMarket Breadth AnalyzerBreadth Chart Analyst
Data SourceCSV (automated)Chart images (manual)
API RequiredNoneNone
OutputQuantitative 0-100 scoreQualitative chart analysis
Components6 scored dimensionsVisual pattern recognition
RepeatabilityFully reproducibleAnalyst-dependent

Execution Workflow

Phase 1: Execute Python Script

Run the analysis script. If using a nested or date-stamped --output-dir in cron runs, create it first; the history writer expects the directory to already exist.

Read the whole SKILL.md on GitHub

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