An advanced AI analysis tool that interprets sector performance charts to identify market cycles and predict rotation patterns.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install sector-analyst
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install sector-analyst using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Sector Analyst?
The Sector Analyst skill is a specialized technical module designed for financial analysis and market positioning. It empowers AI agents to process visual performance data from sector and industry charts, translating raw performance figures into strategic insights. By integrating this skill into Openclaw Skills, developers can automate the assessment of market cycles—including early recovery, mid-cycle expansion, late cycle, and recession phases.
This skill goes beyond simple data extraction by applying professional sector rotation principles. It analyzes relative strength across multiple timeframes, specifically 1-week and 1-month periods, to provide a probabilistic outlook on market movements. Whether you are building a fintech dashboard or an automated investment researcher, this skill provides the logical framework needed to turn chart images into actionable, structured intelligence.
Sector Analyst Use Cases
- Assessing current market cycle positioning based on relative sector strength.
- Predicting which sectors are likely to outperform or underperform in the next rotation phase.
- Generating automated, data-driven market analysis reports from visual chart inputs.
- Performing probability-weighted scenario analysis for strategic asset allocation.
- Identifying divergences between short-term (1-week) and medium-term (1-month) industry trends.
How Sector Analyst Works
- The AI scans user-provided sector and industry performance charts to extract numerical performance data and identify leading/lagging groups.
- It cross-references these observations with the sector rotation knowledge base found in the Openclaw Skills reference library.
- The skill maps the observed patterns against established market cycle frameworks to determine the most likely current phase.
- It generates multiple forward-looking scenarios, assigning probability percentages based on the consistency and breadth of the signals.
- The final output is compiled into a structured Markdown document containing an executive summary, evidence-based assessments, and tactical positioning recommendations.
Sector Analyst Setup
To get started with the Sector Analyst, ensure your environment has the required reference documentation and asset directories.
# Initialize the directory structure for your analysis agent
mkdir -p references assets
# Ensure the required knowledge base is present
# Place your sector_rotation.md framework in the references folder
# Add your performance chart images (JPEG/PNG) to the assets folder
# Example: assets/sector_performance_2023_10.jpeg
Configure your agent to access these local files to provide the necessary context for the Openclaw Skills processing engine.
Sector Analyst Data Schema & Taxonomy
The Sector Analyst skill utilizes a structured approach to data management and reporting:
| Component | Format | Description |
|---|---|---|
| Input Data | Visual Charts | 1-week and 1-month relative performance images for sectors/industries. |
| Knowledge Base | Markdown | references/sector_rotation.md defining cycle phases and rotation rules. |
| Output Report | Markdown | sector_analysis_YYYY-MM-DD.md containing structured analysis. |
| Probability Logic | Taxonomy | 70-85% (Strong), 50-70% (Moderate), 30-50% (Weak), 15-30% (Speculative). |
| File Metadata | Date-stamped | Reports are organized by date to track market evolution over time. |
Sector Analyst Advanced Features
- Multi-timeframe divergence detection to identify turning points in market sentiment.
- Probability-weighted scenario modeling for risk management and contrarian analysis.
- Automated industry-to-sector mapping to verify the breadth of market moves.
- Integration with the Openclaw Skills framework for multi-agent financial research workflows.
- Objective signal assessment to minimize confirmation bias in market cycle forecasting.
SKILL.md
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