Uptrend Analyzer

Analyzes market breadth using Monty’s Uptrend Ratio Dashboard data to diagnose the current market environment. Generates a 0-100 composite score from 5 components (breadth, sector participation, rotation, momentum, historical context). Use when asking about market breadth, uptrend ratios, or whether the market environment supports equity exposure. No API key required.

No API

Download Skill Package (.skill) View Source on GitHub

Table of Contents

1. Overview

Uptrend Analyzer Skill

2. When to Use

English:

  • User asks “Is the market breadth healthy?” or “How broad is the rally?”
  • User wants to assess uptrend ratios across sectors
  • User asks about market participation or breadth conditions
  • User needs exposure guidance based on breadth analysis
  • User references Monty’s Uptrend Dashboard or uptrend ratios

3. Prerequisites

  • API Key: None required
  • Python 3.9+ recommended

4. Quick Start 

python3 skills/uptrend-analyzer/scripts/uptrend_analyzer.py

5. Workflow

Phase 1: Execute Python Script

Run the analysis script (no API key needed):

python3 skills/uptrend-analyzer/scripts/uptrend_analyzer.py

The script will:

  1. Download CSV data from Monty’s GitHub repository
  2. Calculate 5 component scores
  3. Generate composite score and reports

Phase 2: Present Results

Present the generated Markdown report to the user, highlighting:

  • Composite score and zone classification
  • Exposure guidance (Full/Normal/Reduced/Defensive/Preservation)
  • Sector heatmap showing strongest and weakest sectors
  • Key momentum and rotation signals

6. Resources

References:

  • skills/uptrend-analyzer/references/uptrend_methodology.md

Scripts:

  • skills/uptrend-analyzer/scripts/data_fetcher.py
  • skills/uptrend-analyzer/scripts/report_generator.py
  • skills/uptrend-analyzer/scripts/scorer.py
  • skills/uptrend-analyzer/scripts/uptrend_analyzer.py

Same-run provenance

Pass --run-id daily-20261017-unique to both required market-regime-daily producers. Without it each producer generates its own unique ID. JSON includes schema 1.0 data_provenance with actual primary timeseries business date, UTC retrieval time, source and run ID. Unknown adjustment, point-in-time, survivorship and corporate-action flags are false. Auxiliary summary dates are unverified; this does not certify the freshness of every composite input. Missing or malformed primary dates stop report generation.

Pass the exact JSON paths printed by these invocations to Exposure Coach’s --require-provenance --run-id … --as-of … mode. Run IDs are caller-provided consistency markers, not authenticity or point-in-time proof.