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Retrieve stock price change statistics across multiple time periods using Octagon MCP. Use when analyzing short-term and long-term returns, comparing performance across timeframes, and evaluating momentum and historical growth.
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/OctagonAI/skills --skill stock-price-change명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
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SOC 직업 분류 기준
SKILL.md 표시 중
| name | stock-price-change |
| description | Retrieve stock price change statistics across multiple time periods using Octagon MCP. Use when analyzing short-term and long-term returns, comparing performance across timeframes, and evaluating momentum and historical growth. |
Retrieve comprehensive price change statistics across multiple time periods using the Octagon MCP server.
Ensure Octagon MCP is configured in your AI agent (Cursor, Claude Desktop, Windsurf, etc.). See references/mcp-setup.md for installation instructions.
Determine the ticker symbol for the company you want to analyze (e.g., AAPL, MSFT, GOOGL).
Use the octagon-agent tool with a natural language prompt:
Get stock price change statistics for the symbol <TICKER>.
MCP Call Format:
{
"server": "octagon-mcp",
"toolName": "octagon-agent",
"arguments": {
"prompt": "Get stock price change statistics for the symbol AAPL."
}
}
The agent returns price change data across multiple timeframes:
| Time Period | Percentage Change |
|---|---|
| 1 Day | 4.06% |
| 5 Days | 4.80% |
| 1 Month | -0.37% |
| 3 Months | -0.13% |
| 6 Months | 33.42% |
| Year-to-Date (YTD) | -0.37% |
| 1 Year | 18.42% |
| 3 Years | 79.03% |
| 5 Years | 100.02% |
| 10 Years | 1,043.14% |
| All-Time High | 210,270.08% |
Key Insight: Strong long-term growth with 10-year return of 1,043.14%, but recent short-term performance slightly negative.
Data Sources: octagon-stock-data-agent
See references/interpreting-results.md for guidance on:
Basic Query:
Get stock price change statistics for the symbol AAPL.
Multiple Stocks:
Compare price change statistics for AAPL, MSFT, and GOOGL.
Specific Focus:
What is the 1-year and 5-year return for TSLA?
YTD Performance:
What is the year-to-date performance of NVDA?
Long-Term Growth:
What is the 10-year cumulative return for AMZN?
| Period | Use Case |
|---|---|
| 1 Day | Daily momentum |
| 5 Days | Weekly trend |
| 1 Month | Recent performance |
| 3 Months | Quarterly trend |
| Period | Use Case |
|---|---|
| 6 Months | Half-year momentum |
| YTD | Calendar year performance |
| 1 Year | Annual return |
| Period | Use Case |
|---|---|
| 3 Years | Business cycle |
| 5 Years | Market cycle |
| 10 Years | Secular trend |
| All-Time | Total return since inception |
| Return (1 Year) | Classification |
|---|---|
| >50% | Exceptional |
| 25-50% | Very strong |
| 10-25% | Strong |
| 0-10% | Moderate |
| -10 to 0% | Weak |
| <-10% | Poor |
| Return (10 Year) | Classification |
|---|---|
| >500% | Exceptional |
| 200-500% | Very strong |
| 100-200% | Strong |
| 50-100% | Moderate |
| 0-50% | Below average |
| <0% | Poor |
| Pattern | Interpretation |
|---|---|
| All periods positive | Strong consistent uptrend |
| Short negative, long positive | Pullback in uptrend |
| Short positive, long negative | Bounce in downtrend |
| All periods negative | Consistent downtrend |
| Signal | Pattern |
|---|---|
| Accelerating | Returns increasing across periods |
| Decelerating | Returns decreasing across periods |
| Stable | Consistent returns across periods |
| Reversal | Sign change between periods |
From AAPL data:
Interpretation: Long-term compounder with recent consolidation.
Annualized Return = (1 + Total Return)^(1/Years) - 1
From AAPL data:
| Annual Return | Rating |
|---|---|
| >25% | Exceptional |
| 15-25% | Very strong |
| 10-15% | Strong |
| 7-10% | Market-like |
| <7% | Below market |
| Benchmark | What to Compare |
|---|---|
| S&P 500 | Market performance |
| Sector ETF | Industry performance |
| Peers | Competitive position |
Alpha = Stock Return - Benchmark Return
If AAPL 1-year return is +18.42% and S&P 500 is +10%:
| Pattern | Interpretation |
|---|---|
| Long > Short | Healthy uptrend |
| Positive all periods | Consistent strength |
| Improving short-term | Momentum building |
| Pattern | Interpretation |
|---|---|
| Long << Short | Mean reversion risk |
| Long > 0, Short < 0 | Trend weakening |
| All negative | Fundamental issues |
Distance = (ATH - Current) / ATH × 100%
| Position | Interpretation |
|---|---|
| At ATH | Maximum strength |
| 0-10% below | Near highs |
| 10-20% below | Correction |
| 20-40% below | Bear market |
| >40% below | Severe decline |
What are the returns for AAPL across all time periods?
Is MSFT in an uptrend or downtrend based on recent returns?
What is the 10-year cumulative return for the FAANG stocks?
Is NVDA showing positive momentum in the short-term?
Compare 1-year returns for major tech stocks.
Don't rely on one period: Use multiple timeframes.
Compare to benchmarks: Returns mean more in context.
Consider consistency: Smooth vs. volatile returns.
Annualize long-term: For fair comparison.
Watch for divergence: Short vs. long-term signals.
Factor in dividends: Total return vs. price return.
| Skill | Combined Use |
|---|---|
| stock-quote | Current price context |
| stock-performance | Daily price data |
| stock-historical-index | vs. market returns |
| financial-metrics-analysis | Fundamentals behind returns |