trading-analysis▌
gracefullight/stock-checker · updated May 10, 2026
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Professional investment reports combining real-time market data, technical indicators, and AI-powered analysis.
- ›Calculates 10+ technical indicators (RSI, MACD, Moving Averages, Bollinger Bands) and generates 4 types of high-resolution charts (price, indicators, volatility, dashboard)
- ›Accepts stock ticker symbols with optional client name and custom report title; processes multiple symbols in a single request
- ›Outputs institutional-grade Markdown reports with executive summary, technic
Trading Analysis & Investment Report Generator
This skill generates comprehensive investment reports combining real-time market data, technical analysis, Claude AI insights, and professional visualizations.
What This Skill Does
- Downloads real-time market data from Yahoo Finance
- Calculates 10+ technical indicators (RSI, MACD, Moving Averages, Bollinger Bands, etc.)
- Analyzes market conditions using Claude AI
- Generates 4 types of professional charts (price, indicators, volatility, dashboard)
- Creates institutional-grade investment reports in Markdown format
- Exports structured data in JSON format
When to Use This Skill
Use this skill when the user requests:
- Investment reports or analysis for specific stocks/ETFs
- Market analysis with technical indicators
- Trading recommendations based on current market conditions
- Professional reports for clients or portfolio review
- Comparative analysis across multiple symbols
Input Requirements
Required:
symbol: Stock ticker (e.g., SPY, AAPL, TSLA, QQQ)
Optional:
client_name: Name of the client/investor (default: "Institutional Investors")report_title: Custom report title (auto-generated if not provided)period: Historical data period (default: "6mo")
Output Files
The skill generates the following files in the reports/ directory:
-
Markdown Report (
{SYMBOL}_analysis_report_{timestamp}.md)- Executive summary with sentiment and recommendation
- Market overview with price tables
- Technical analysis with indicators
- AI-powered market intelligence
- Investment recommendations with entry/exit criteria
- Risk assessment
- Chart references
-
JSON Data (
{SYMBOL}_analysis_report_{timestamp}_data.json)- Structured data for programmatic access
- All metrics and analysis results
-
Charts (PNG format, 300 DPI):
{SYMBOL}_price_chart.png: Price with moving averages{SYMBOL}_indicators_chart.png: RSI and MACD{SYMBOL}_volatility_chart.png: Historical volatility{SYMBOL}_summary_dashboard.png: Performance dashboard
Example Usage
Simple request: "Generate an investment report for SPY"
Detailed request: "Create a market analysis report for AAPL for Acme Capital with the title 'Q4 2025 AAPL Investment Strategy'"
Multiple symbols: "Generate investment reports for SPY, QQQ, and DIA"
Report Quality
- Format: Institutional-grade, suitable for client presentations
- Data Accuracy: Real-time market data with verified calculations
- Visual Quality: High-resolution charts (300 DPI, print-ready)
- AI Analysis: Claude-powered market sentiment and risk assessment
- Completeness: Executive summary, technical analysis, recommendations, disclaimers
Technical Details
- Data Source: Yahoo Finance API
- AI Model: Claude 3.7 Sonnet (configurable)
- Chart Resolution: 300 DPI (print quality)
- Report Format: GitHub-flavored Markdown
- Processing Time: ~15-30 seconds per symbol
Safety & Disclaimers
All reports automatically include:
- Investment disclaimer
- Risk warnings
- Clarification that this is informational, not financial advice
- Recommendation to consult qualified financial advisors
Notes
- Requires valid Anthropic API key in
.envfile - Requires internet connection for market data
- Historical data limited by Yahoo Finance availability
- AI analysis is based on technical data, not fundamental analysis
How to use trading-analysis on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add trading-analysis
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches trading-analysis from GitHub repository gracefullight/stock-checker and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate trading-analysis. Access the skill through slash commands (e.g., /trading-analysis) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.5★★★★★60 reviews- ★★★★★Lucas Choi· Dec 20, 2024
trading-analysis has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Pratham Ware· Dec 16, 2024
trading-analysis reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Advait Liu· Dec 16, 2024
Solid pick for teams standardizing on skills: trading-analysis is focused, and the summary matches what you get after install.
- ★★★★★Isabella Diallo· Dec 12, 2024
Keeps context tight: trading-analysis is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Advait White· Nov 27, 2024
We added trading-analysis from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Maya Brown· Nov 11, 2024
Keeps context tight: trading-analysis is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Yash Thakker· Nov 7, 2024
I recommend trading-analysis for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Zaid Haddad· Nov 7, 2024
trading-analysis is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Camila Srinivasan· Nov 3, 2024
trading-analysis has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Isabella Garcia· Nov 3, 2024
trading-analysis fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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