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stock-analysis▌

bruce-shi/ticker-cli · updated Apr 8, 2026

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$npx skills add https://github.com/bruce-shi/ticker-cli --skill stock-analysis
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summary

A powerful CLI tool for trading analysis that provides stock quotes, charts, technical indicators, news, and more.

skill.md

Stock Analysis Skill

A powerful CLI tool for trading analysis that provides stock quotes, charts, technical indicators, news, and more.

Basic Usage

npx ticker-cli <command> [options]

Available Commands

Command Description
quote Get real-time stock quotes
chart Get chart/historical data
indicator Calculate technical indicators (SMA, EMA, RSI, MACD, BB)
summary Get comprehensive quote summary
news Get latest stock news
insights Get stock insights and analysis
options Get options chain data
recommendations Get analyst recommendations
screener Screen stocks (most actives, gainers, losers, etc.)
search Search for stock symbols

Quick Examples

# Get quote for single or multiple stocks
npx ticker-cli quote AAPL
npx ticker-cli quote AAPL MSFT GOOGL

# Get historical chart data
npx ticker-cli chart AAPL -p 1mo
npx ticker-cli chart AAPL --start 2025-01-01 --end 2025-12-31

# Calculate technical indicators
npx ticker-cli indicator AAPL sma -p 3mo
npx ticker-cli indicator AAPL rsi -p 3mo
npx ticker-cli indicator AAPL macd -p 6mo
npx ticker-cli indicator AAPL sma -p 1mo -i 1h

# Get news and insights
npx ticker-cli news AAPL --limit 20
npx ticker-cli insights AAPL

# Screen stocks
npx ticker-cli screener -q most_actives
npx ticker-cli screener -q day_gainers

Report Generation Guides

For detailed instructions on generating reports, see the references folder:

Technical Indicators Reference

Indicator Description Default Length
sma Simple Moving Average 20
ema Exponential Moving Average 20
rsi Relative Strength Index 14
macd Moving Average Convergence Divergence 12/26/9
bb Bollinger Bands 20

Screener Queries

Available predefined queries:

  • most_actives - Most actively traded stocks
  • day_gainers - Top gainers of the day
  • day_losers - Top losers of the day
  • undervalued_growth_stocks - Undervalued stocks with growth potential
  • undervalued_large_caps - Undervalued large cap stocks
  • growth_technology_stocks - Growing tech stocks
  • top_mutual_funds - Top performing mutual funds
how to use stock-analysis

How to use stock-analysis on Cursor

AI-first code editor with Composer

1

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 stock-analysis
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/bruce-shi/ticker-cli --skill stock-analysis

The skills CLI fetches stock-analysis from GitHub repository bruce-shi/ticker-cli and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/stock-analysis

Reload or restart Cursor to activate stock-analysis. Access the skill through slash commands (e.g., /stock-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.

Additional Resources

›View source code on GitHub›Skills CLI documentation›Learn more about Cursor›What are agent skills?

List & Monetize Your Skill

Submit your Claude Code skill and start earning

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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. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 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▌

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.7★★★★★57 reviews
  • ★★★★★Pratham Ware· Dec 28, 2024

    Useful defaults in stock-analysis — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • ★★★★★Arjun Khan· Dec 28, 2024

    stock-analysis has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • ★★★★★Fatima Gupta· Dec 28, 2024

    Solid pick for teams standardizing on skills: stock-analysis is focused, and the summary matches what you get after install.

  • ★★★★★Yusuf Bansal· Dec 12, 2024

    Useful defaults in stock-analysis — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • ★★★★★Lucas Thomas· Dec 8, 2024

    We added stock-analysis from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • ★★★★★Amina Verma· Dec 4, 2024

    stock-analysis is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • ★★★★★Arjun Haddad· Nov 27, 2024

    stock-analysis reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • ★★★★★Lucas White· Nov 23, 2024

    Solid pick for teams standardizing on skills: stock-analysis is focused, and the summary matches what you get after install.

  • ★★★★★Yuki Ghosh· Nov 19, 2024

    Keeps context tight: stock-analysis is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • ★★★★★Yusuf Brown· Nov 19, 2024

    stock-analysis is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

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