This skill should be used when analyzing sector and industry performance charts to assess market positioning and rotation patterns. Use this skill when the user provides performance chart images (1-week or 1-month timeframes) for sectors or industries and requests market cycle assessment, sector rotation analysis, or strategic positioning recommendations based on performance data. All analysis and output are conducted in English.
Permissions
Just instructions. No commands, network, or file access.
Files
SKILL.md
sector-analyst
This skill should be used when analyzing sector and industry performance charts to assess market positioning and rotation patterns. Use this skill when the user provides performance chart images (1-week or 1-month timeframes) for sectors or industries and requests market cycle assessment, sector rotation analysis, or strategic positioning recommendations based on performance data. All analysis and output are conducted in English.
Sector Analyst
Overview
This skill enables comprehensive analysis of sector and industry performance charts to identify market cycle positioning and predict likely rotation scenarios. The analysis combines observed performance data with established sector rotation principles to provide objective market assessment and probabilistic scenario forecasting.
When to Use This Skill
Use this skill when:
User provides sector performance charts (typically 1-week and 1-month timeframes)
User provides industry performance charts showing relative performance data
User requests analysis of current market cycle positioning
User asks for sector rotation assessment or predictions
User needs probability-weighted scenarios for market positioning
Example user requests:
"Analyze these sector performance charts and tell me where we are in the market cycle"
"Based on these performance charts, what sectors should outperform next?"
"What's the probability of a defensive rotation based on this data?"
"Review these sector and industry charts and provide scenario analysis"
Analysis Workflow
Follow this structured workflow when analyzing sector/industry performance charts:
Step 1: Data Collection and Observation
First, carefully examine all provided chart images to extract:
Sector-level performance: Identify which sectors (Technology, Financials, Consumer Discretionary, etc.) are outperforming/underperforming
Industry-level performance: Note specific industries showing strength or weakness
Timeframe comparison: Compare 1-week vs 1-month performance to identify trend consistency or divergence
Magnitude of moves: Assess the size of relative performance differences
Breadth of movement: Determine if performance is concentrated or broad-based
Think in English while analyzing the charts. Document specific numerical performance figures for key sectors and industries.
Step 2: Market Cycle Assessment
Load the sector rotation knowledge base to inform analysis:
Read references/sector_rotation.md to access market cycle and sector rotation frameworks
Compare observed performance patterns against expected patterns for each cycle phase:
Early Cycle Recovery
Mid Cycle Expansion
Late Cycle
Recession
Identify which cycle phase best matches current observations by:
Mapping outperforming sectors to typical cycle leaders
Mapping underperforming sectors to typical cycle laggards
Assessing consistency across multiple sectors
Evaluating alignment with defensive vs cyclical sector performance
Step 3: Current Situation Analysis
Synthesize observations into an objective assessment:
State which market cycle phase current performance most closely resembles
Highlight supporting evidence (which sectors/industries confirm this view)
Note any contradictory signals or unusual patterns
Assess confidence level based on consistency of signals
Use data-driven language and specific references to performance figures.
Step 4: Scenario Development
Based on sector rotation principles and current positioning, develop 2-4 potential scenarios for the next phase:
For each scenario:
Describe the market cycle transition
Identify which sectors would likely outperform
Identify which sectors would likely underperform
Specify the catalysts or conditions that would confirm this scenario
Assign a probability (see Probability Assessment Framework in sector_rotation.md)
Scenarios should range from most likely (highest probability) to alternative/contrarian scenarios.
Step 5: Output Generation
Create a structured Markdown document with the following sections:
Required Sections:
Executive Summary: 2-3 sentence overview of key findings
Current Situation: Detailed analysis of current performance patterns and market cycle positioning
Supporting Evidence: Specific sector and industry performance data supporting the cycle assessment
Scenario Analysis: 2-4 scenarios with descriptions and probability assignments
Recommended Positioning: Strategic and tactical positioning recommendations based on scenario probabilities
Key Risks: Notable risks or contradictory signals to monitor
Output Format
Save analysis results as a Markdown file with naming convention: sector_analysis_YYYY-MM-DD.md
Use this structure:
# Sector Performance Analysis - [Date]## Executive Summary
[2-3 sentences summarizing key findings]
## Current Situation### Market Cycle Assessment
[Which cycle phase and why]
### Performance Patterns Observed#### 1-Week Performance
[Analysis of recent performance]
#### 1-Month Performance
[Analysis of medium-term trends]
#### Sector-Level Analysis
[Detailed breakdown by sector]
#### Industry-Level Analysis
[Notable industry-specific observations]
## Supporting Evidence### Confirming Signals- [List data points supporting cycle assessment]
### Contradictory Signals- [List any conflicting indicators]
## Scenario Analysis### Scenario 1: [Name] (Probability: XX%)**Description**: [What happens]
**Outperformers**: [Sectors/industries]
**Underperformers**: [Sectors/industries]
**Catalysts**: [What would confirm this scenario]
### Scenario 2: [Name] (Probability: XX%)
[Repeat structure]
[Additional scenarios as appropriate]
## Recommended Positioning### Strategic Positioning (Medium-term)
[Sector allocation recommendations]
### Tactical Positioning (Short-term)
[Specific adjustments or opportunities]
## Key Risks and Monitoring Points
[What to watch that could invalidate the analysis]
---
*Analysis Date: [Date]**Data Period: [Timeframe of charts analyzed]*
Key Analysis Principles
When conducting analysis:
Objectivity First: Let the data guide conclusions, not preconceptions
Probabilistic Thinking: Express uncertainty through probability ranges
Multiple Timeframes: Compare 1-week and 1-month data for trend confirmation
Relative Performance: Focus on relative strength, not absolute returns
Breadth Matters: Broad-based moves are more significant than isolated movements
No Absolutes: Markets rarely follow textbook patterns exactly
Historical Context: Reference typical rotation patterns but acknowledge uniqueness
Probability Guidelines
Apply these probability ranges based on evidence strength:
70-85%: Strong evidence with multiple confirming signals across sectors and timeframes
50-70%: Moderate evidence with some confirming signals but mixed indicators
30-50%: Weak evidence with limited or conflicting signals
15-30%: Speculative scenario contrary to current indicators but possible
Total probabilities across all scenarios should sum to approximately 100%.
Resources
references/
sector_rotation.md - Comprehensive knowledge base covering market cycle phases, typical sector performance patterns, and probability assessment frameworks
assets/
Sample charts demonstrating the expected input format:
sector_performance.jpeg - Example sector-level performance chart (1-week and 1-month)
industory_performance_1.jpeg - Example industry performance chart (outperformers)
industory_performance_2.jpeg - Example industry performance chart (underperformers)
These samples illustrate the type of visual data this skill analyzes. User-provided charts may vary in format but should contain similar relative performance information.
Important Notes
All analysis thinking should be conducted in English
Output Markdown files must be in English
Reference the sector rotation knowledge base for each analysis
Maintain objectivity and avoid confirmation bias
Update probability assessments if new data becomes available
Charts typically show performance over 1-week and 1-month periods
