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FrancyJGLisboa
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stock-analyzer-cskill

Generate technical stock analysis and trading signals from RSI, MACD, and Bollinger calculations.

2.2k|248|Updated Oct 18, 2025
Search Tags:#investment#financial data#portfolio management#automated reports#technical indicators#market trends#stock analysis
One-click install
npx skills add https://github.com/FrancyJGLisboa/agent-skill-creator --skill stock-analyzer-cskill
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: stock-analyzer-cskill
Source: https://github.com/FrancyJGLisboa/agent-skill-creator/tree/main/references/examples/stock-analyzer-cskill
Command: npx skills add https://github.com/FrancyJGLisboa/agent-skill-creator --skill stock-analyzer-cskill

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests, pandas, numpy, matplotlib, and includes scripts (resource) and references (resource) components.

What problem does it solves? Manually tracking stock market data, calculating technical indicators, and generating comprehensive reports is a time-consuming and complex task. This skill automates the entire financial analysis process, providing you with instant insights and freeing you from tedious data crunching.

Core Features & Use Cases

  • Real-time Stock Data: Automatically fetches up-to-date stock market data from reliable financial APIs, ensuring your analysis is always based on the latest information.
  • Advanced Technical Analysis: Calculates key technical indicators such as RSI, MACD, and Bollinger Bands, helping you identify trends and potential trading signals.
  • Automated Reporting & Alerts: Generates professional, easy-to-understand reports and sets up alerts for significant market movements or indicator crossovers, so you never miss a critical event.
  • Use Case: Get a daily, personalized report on your investment portfolio's performance, including technical signals, risk assessments, and market news summaries, delivered automatically to your preferred channel.

Quick Start

1. Install the skill

/plugin marketplace add ./references/examples/stock-analyzer-cskill

2. Then, ask for analysis

"Analyze AAPL stock performance and trends" "Generate a report for my portfolio"

Frequently Asked Questions about stock-analyzer-cskill

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I calculate technical indicators like RSI, MACD, and Bollinger Bands for stock analysis?▼

Technical indicators calculate market momentum and trend signals from price data. This skill automates RSI, MACD, and Bollinger Band computations using pandas and numpy, extracting actionable trading signals without manual calculations.

Can I automate stock analysis reports and receive alerts for market movements?▼

Yes. This skill generates automated technical analysis reports and configures alerts for significant price movements or indicator crossovers, delivering structured outputs suitable for agent workflows and notification channels.

How do I compare technical signals across multiple stocks and ETFs simultaneously?▼

Multi-security comparison applies the same technical indicators across multiple securities, generating comparative analysis and signals. This skill processes stock and ETF data in parallel, surfacing relative trends and cross-asset patterns.

What data sources and formats does automated stock analysis require?▼

Stock analysis requires real-time or historical price data fetched via financial APIs through the requests library. The skill ingests ticker symbols and date ranges, outputting structured datasets compatible with portfolio tracking and agent workflows.

Can I use technical analysis for both individual stocks and portfolio monitoring?▼

Yes. The skill applies technical indicators and signal generation to individual securities and aggregated portfolios, supporting use cases from single-stock monitoring to comprehensive portfolio performance tracking with risk assessments.

What are the limitations of technical indicators for predicting market trends?▼

Technical indicators lag price action and perform poorly during volatile or low-liquidity conditions. Chart patterns and indicator signals work best in trending markets; this skill surfaces signals but does not guarantee predictions in choppy or gap-prone environments.

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