A professional-grade analytical skill for performing comprehensive fundamental, technical, and comparative research on US-listed stocks.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install us-stock-analysis
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 us-stock-analysis 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 US Stock Analysis?
The US Stock Analysis skill for Openclaw Skills provides a robust framework for evaluating American equities by synthesizing real-time market data with structured financial methodologies. It allows developers and analysts to automate the retrieval of financial statements, valuation metrics, and technical indicators, turning raw data into sophisticated investment intelligence. This skill is designed to handle everything from quick ticker summaries to exhaustive investment reports that include bull and bear cases.
By integrating with web search tools, this skill ensures that your analysis is always based on the most recent quarterly filings, analyst ratings, and price action. Whether you are looking for a deep dive into a company's business quality or a tactical assessment of its current chart patterns, this tool provides the analytical depth required for professional-level financial research.
US Stock Analysis Use Cases
- Generating comprehensive investment reports for US tickers like AAPL, TSLA, or NVDA.
- Comparing multiple stocks side-by-side to identify the best relative value within a sector.
- Evaluating company financial health using automated calculations for ROE, debt-to-equity, and free cash flow.
- Identifying tactical trading opportunities through automated technical analysis of RSI, MACD, and moving averages.
- Screening recent news and SEC filings to identify potential catalysts or underlying risks.
How US Stock Analysis Works
- The agent initiates a targeted web search to gather current price data, financial statements, and recent news for the specified ticker.
- Fundamental data is processed against structured frameworks to evaluate business quality, profitability trends, and historical valuation.
- Technical indicators and chart patterns are extracted from recent trading data to determine market trends and key support/resistance levels.
- Findings are cross-referenced with internal templates and metric definitions to ensure consistency and accuracy.
- The skill synthesizes all data points into a formatted response, ranging from a concise table to a full multi-section investment report.
US Stock Analysis Setup
To utilize this skill within Openclaw Skills, ensure your agent has access to a web search tool and the following reference documents in its workspace:
# Ensure the /references directory is populated
ls references/
# technical-analysis.md
# fundamental-analysis.md
# financial-metrics.md
# report-template.md
No additional API keys are required beyond those used for your agent's search and LLM capabilities.
US Stock Analysis Data Schema & Taxonomy
The US Stock Analysis skill organizes data into a multi-layered schema for high readability:
| Layer | Key Metrics | Metadata |
|---|---|---|
| Core Trading | Price, Volume, Market Cap | Ticker, Timestamp |
| Fundamental | P/E, EPS, Revenue, Margins, Debt | Fiscal Quarter, Source |
| Technical | RSI, MACD, Moving Averages (50/200) | Timeframe, Trend Signal |
| Qualitative | Moat, Risks, Management Quality | Analyst Sentiment |
| Comparative | Peer Ratios, Relative Strength | Competitor Tickers |
US Stock Analysis Advanced Features
- Multi-agent compatibility for distributed research tasks across Openclaw Skills.
- Support for complex side-by-side comparison tables with color-coded relative strength indicators.
- Automated generation of bear and bull case scenarios to mitigate bias in investment research.
- Dynamic fair value estimation based on historical averages and peer group multiples.
- Integration with specialized reference files for standardized metric definitions and report formatting.
SKILL.md
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