菜单
Retrieve stock price data and performance metrics using the Octagon Claude plugin. Use when analyzing daily closing prices, trading volume, price trends, historical performance, and comparing stock movements over specific time periods.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/OctagonAI/octagon-claude-plugin --skill stock-performance命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
Validate Octagon connector health and run a lightweight smoke test across the main Octagon Claude plugin workflows. Use when checking whether the Octagon connector is configured correctly, debugging auth, or verifying tool availability.
Set up or reconnect the Octagon Claude plugin through the hosted Octagon AI connector. Use when the user wants to connect Octagon, repair a broken connection, confirm what auth path the plugin uses, or get started with Octagon tools in Claude.
Check whether the Octagon Claude plugin is connected and summarize the current Octagon tool surface. Use when the user asks what Octagon can do now, whether the plugin is healthy, or whether the connector is configured correctly.
正在显示 SKILL.md
基于 SOC 职业分类
| name | stock-performance |
| description | Retrieve stock price data and performance metrics using the Octagon Claude plugin. Use when analyzing daily closing prices, trading volume, price trends, historical performance, and comparing stock movements over specific time periods. |
Retrieve daily closing prices, trading volume, and performance metrics for public companies using the Octagon Claude plugin.
Ensure the Octagon Claude plugin is installed and configured in Claude Code before invoking this skill.
Determine the following before querying:
Use the octagon-agent tool with a natural language prompt:
Retrieve the daily closing prices for <TICKER> over the last <N> days.
MCP Call Format:
{
"server": "octagon-claude-plugin",
"toolName": "octagon-agent",
"arguments": {
"prompt": "Retrieve the daily closing prices for AAPL over the last 30 days."
}
}
The agent returns structured price data including:
| Date | Closing Price | Volume |
|---|---|---|
| 2026-02-02 | $270.01 | 73,677,607 |
| 2026-01-30 | $259.48 | 92,443,408 |
| 2026-01-29 | $258.28 | 67,253,009 |
| ... | ... | ... |
Data Sources: octagon-stock-data-agent, octagon-web-search-agent
See references/interpreting-results.md for guidance on:
Daily Closing Prices:
Retrieve the daily closing prices for AAPL over the last 30 days.
Extended Historical Data:
Get historical stock prices for MSFT for the past 90 days.
Volume Analysis:
Retrieve daily trading volume for TSLA over the last 2 weeks.
Price Range:
What are the high and low prices for NVDA over the past month?
Multi-Stock Comparison:
Compare the stock performance of AAPL, MSFT, and GOOGL over the last 30 days.
52-Week Analysis:
What is the 52-week high and low for AMZN?
| Metric | Description |
|---|---|
| Closing Price | End-of-day price |
| Opening Price | Start-of-day price |
| High | Intraday high |
| Low | Intraday low |
| Adjusted Close | Dividend/split adjusted |
| Metric | Description |
|---|---|
| Daily Volume | Shares traded per day |
| Average Volume | Typical daily volume |
| Relative Volume | Current vs. average |
| Volume Trend | Direction over time |
| Metric | Calculation |
|---|---|
| Daily Return | (Close - Prior Close) / Prior Close |
| Period Return | (End - Start) / Start |
| Cumulative Return | Running return over period |
| Annualized Return | Period return scaled to 1 year |
| Pattern | Characteristics |
|---|---|
| Uptrend | Higher highs, higher lows |
| Downtrend | Lower highs, lower lows |
| Sideways | Range-bound movement |
| Breakout | Move beyond range |
| Measure | Description |
|---|---|
| Price Range | High - Low over period |
| Daily Range | Average daily high-low |
| Standard Deviation | Price dispersion |
| Beta | Relative to market |
| Level | Description |
|---|---|
| Support | Price floor, buying interest |
| Resistance | Price ceiling, selling pressure |
| Moving Averages | Dynamic support/resistance |
| Round Numbers | Psychological levels |
| Pattern | Interpretation |
|---|---|
| High Volume + Price Up | Strong buying conviction |
| High Volume + Price Down | Strong selling pressure |
| Low Volume + Price Up | Weak rally, may reverse |
| Low Volume + Price Down | Lack of selling interest |
| Indicator | Usage |
|---|---|
| Volume Spike | Unusual activity, potential catalyst |
| Volume Dry-up | Consolidation, waiting mode |
| Volume Trend | Confirms price trend |
| On-Balance Volume | Cumulative volume direction |
| Focus | Use Case |
|---|---|
| Recent Performance | Current momentum |
| Trading Signals | Entry/exit timing |
| News Impact | Event analysis |
| Volatility | Risk assessment |
| Focus | Use Case |
|---|---|
| Trend Identification | Direction confirmation |
| Seasonality | Cyclical patterns |
| Earnings Impact | Quarterly effects |
| Sector Rotation | Relative performance |
| Focus | Use Case |
|---|---|
| Major Trends | Secular moves |
| 52-Week Range | Valuation context |
| Recovery/Decline | Major shifts |
| Dividend Yield | Income analysis |
| Metric | What to Compare |
|---|---|
| Return | Relative performance |
| Volatility | Risk comparison |
| Correlation | Movement similarity |
| Volume | Liquidity comparison |
| Benchmark | Usage |
|---|---|
| S&P 500 | Large cap reference |
| Sector ETF | Industry context |
| Nasdaq | Tech comparison |
| Russell 2000 | Small cap reference |
Consider context: Market conditions affect individual stocks.
Adjust for events: Earnings, dividends, splits affect prices.
Use volume confirmation: Price moves need volume support.
Multiple timeframes: Longer and shorter perspectives.
Compare to peers: Relative performance matters.
Watch key levels: Round numbers, 52-week highs/lows.