trading-analysis 是做什麼的？
為股票和ETF生成專業投資報告。當用戶請求市場分析、投資報告、股票分析或金融工具（SPY、AAPL、TSLA等）的交易建議時使用。建立具有技術指標、AI驅動洞察、圖表和投資建議的機構級報告。
生成股票和ETF的專業投資報告。當用戶需要市場分析、投資報告、股票分析或交易建議（例如SPY、AAPL、TSLA等金融工具）時使用。建立具技術指標、AI驅動洞察、圖表和投資建議的機構級報告。
這是一個專門用於生成股票和ETF專業投資報告的技能。它能夠回應市場分析、投資報告、股票分析或交易建議等請求，並為SPY、AAPL、TSLA等金融工具產出機構級報告。該技能整合了技術指標、AI驅動的市場洞察、視覺化圖表和具體的投資建議，幫助開發者或AI代理用戶快速獲取全面且專業的財務分析。支援多種平台，如Claude Code、Cursor等，透過讀取相關的SKILL.md文件來理解其工作流程。使用此技能時，用戶只需提供目標股票或ETF代號，即可自動生成詳細報告，大幅節省手動研究和分析的時間。
npx skills add https://github.com/gracefullight/stock-checker/tree/main/skills/trading-analysisInstalled? Explore more 研究與資料分析 skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
為股票和ETF生成專業投資報告。當用戶請求市場分析、投資報告、股票分析或金融工具（SPY、AAPL、TSLA等）的交易建議時使用。建立具有技術指標、AI驅動洞察、圖表和投資建議的機構級報告。
This repo contains 3 individual skills — each has its own dedicated page.
Backtest crypto and traditional trading strategies against historical data. Calculates performance metrics (Sharpe, Sortino, max drawdown), generates equity curves, and optimizes strategy parameters. Use when user wants to test a trading strategy, validate signals, or compare approaches. Trigger with phrases like "backtest strategy", "test trading strategy", "historical performance", "simulate trades", "optimize parameters", or "validate signals".
Analyze stocks and cryptocurrencies using Yahoo Finance data. Supports portfolio management (create, add, remove assets), crypto analysis (Top 20 by market cap), and periodic performance reports (daily/weekly/monthly/quarterly/yearly). 8 analysis dimensions for stocks, 3 for crypto. Use for stock analysis, portfolio tracking, earnings reactions, or crypto monitoring.
Get stock prices, quotes, fundamentals, earnings, options, dividends, and analyst ratings using Yahoo Finance. Uses yfinance library - no API key required.
USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.
Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.
Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
Agent skill repository discovered by 10x-chat research.
Review backend code for quality, security, maintainability, and best practices based on established checklist rules. Use when the user requests a review, analysis, or improvement of backend files (e.g., `.py`) under the `api/` directory. Do NOT use for frontend files (e.g., `.tsx`, `.ts`, `.js`). Supports pending-change review, code snippets review, and file-focused review.