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 Difference from Breadth Chart Analyst Aspect Market Breadth Analyzer Breadth Chart Analyst Data Source CSV (automated) Chart images (manual) API Required None None Output Quantitative 0-100 score Qualitative chart analysis Components 6 scored dimensions Visual pattern recognition Repeatability Fully reproducible Analyst-dependent Execution Workflow Phase 1: Execute Python Script Run the analysis script: python3 skills/market-breadth-analyzer/scripts/market_breadth_analyzer.py \ --detail-url "https://tradermonty.github.io/market-breadth-analysis/market_breadth_data.csv" \ --summary-url "https://tradermonty.github.io/market-breadth-analysis/market_breadth_summary.csv" The script will: Fetch detail CSV (~2,500 rows, 2016-present) and summary CSV (8 metrics) Validate data freshness (warn if > 5 days old) Calculate all 6 component scores (with automatic weight redistribution if any component lacks data) Generate composite score with zone classification Track score history and compute trend (improving/deteriorating/stable) Output JSON and Markdown reports Phase 2: Present Results Present the generated Markdown report to the user, highlighting: Composite score and health zone Strongest and weakest components Recommended equity exposure level Key breadth levels to watch Any data freshness warnings 6-Component Scoring System
Component Weight Key Signal 1 Breadth Level & Trend 25% Current 8MA level + 200MA trend direction + 8MA direction modifier 2 8MA vs 200MA Crossover 20% Momentum via MA gap and direction 3 Peak/Trough Cycle 20% Position in breadth cycle 4 Bearish Signal 15% Backtested bearish signal flag 5 Historical Percentile 10% Current vs full history distribution 6 S&P 500 Divergence 10% Multi-window (20d + 60d) price vs breadth divergence Weight Redistribution: If any component lacks sufficient data (e.g., no peak/trough markers detected), it is excluded and its weight is proportionally redistributed among the remaining components. The report shows both original and effective weights. Score History: Composite scores are persisted across runs (keyed by data date). The report includes a trend summary (improving/deteriorating/stable) when multiple observations are available. Health Zone Mapping (100 = Healthy) Score Zone Equity Exposure Action 80-100 Strong 90-100% Full position, growth/momentum favored 60-79 Healthy 75-90% Normal operations 40-59 Neutral 60-75% Selective positioning, tighten stops 20-39 Weakening 40-60% Profit-taking, raise cash 0-19 Critical 25-40% Capital preservation, watch for trough Data Sources Detail CSV: market_breadth_data.csv ~2,500 rows from 2016-02 to present Columns: Date, S&P500_Price, Breadth_Index_Raw, Breadth_Index_200MA, Breadth_Index_8MA, Breadth_200MA_Trend, Bearish_Signal, Is_Peak, Is_Trough, Is_Trough_8MA_Below_04 Summary CSV: market_breadth_summary.csv 8 aggregate metrics (average peaks, average troughs, counts, analysis period) Both are publicly hosted on GitHub Pages - no authentication required. Output Files JSON: market_breadth_YYYY-MM-DD_HHMMSS.json Markdown: market_breadth_YYYY-MM-DD_HHMMSS.md History: market_breadth_history.json (persists across runs, max 20 entries) Reference Documents references/breadth_analysis_methodology.md Full methodology with component scoring details Threshold explanations and zone definitions Historical context and interpretation guide When to Load References First use: Load methodology reference for framework understanding Regular execution: References not needed - script handles scoring