skills/octagonai/skills/stock-performance

stock-performance

SKILL.md

Stock Performance

Retrieve daily closing prices, trading volume, and performance metrics for public companies using the Octagon MCP server.

Prerequisites

Ensure Octagon MCP is configured in your AI agent (Cursor, Claude Desktop, Windsurf, etc.). See references/mcp-setup.md for installation instructions.

Workflow

1. Identify Analysis Parameters

Determine the following before querying:

  • Ticker: Stock symbol (e.g., AAPL, MSFT, GOOGL)
  • Time Period: Number of days or date range
  • Metrics (optional): Price, volume, returns

2. Execute Query via Octagon MCP

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-mcp",
  "toolName": "octagon-agent",
  "arguments": {
    "prompt": "Retrieve the daily closing prices for AAPL over the last 30 days."
  }
}

3. Expected Output

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

4. Interpret Results

See references/interpreting-results.md for guidance on:

  • Analyzing price trends
  • Evaluating volume patterns
  • Calculating returns
  • Identifying support/resistance levels

Example Queries

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?

Key Metrics

Price Metrics

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

Volume Metrics

Metric Description
Daily Volume Shares traded per day
Average Volume Typical daily volume
Relative Volume Current vs. average
Volume Trend Direction over time

Return Metrics

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

Price Analysis Framework

Trend Analysis

Pattern Characteristics
Uptrend Higher highs, higher lows
Downtrend Lower highs, lower lows
Sideways Range-bound movement
Breakout Move beyond range

Volatility Assessment

Measure Description
Price Range High - Low over period
Daily Range Average daily high-low
Standard Deviation Price dispersion
Beta Relative to market

Support/Resistance

Level Description
Support Price floor, buying interest
Resistance Price ceiling, selling pressure
Moving Averages Dynamic support/resistance
Round Numbers Psychological levels

Volume Analysis

Volume Patterns

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

Volume Indicators

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

Time Period Analysis

Short-Term (1-30 Days)

Focus Use Case
Recent Performance Current momentum
Trading Signals Entry/exit timing
News Impact Event analysis
Volatility Risk assessment

Medium-Term (1-6 Months)

Focus Use Case
Trend Identification Direction confirmation
Seasonality Cyclical patterns
Earnings Impact Quarterly effects
Sector Rotation Relative performance

Long-Term (1+ Years)

Focus Use Case
Major Trends Secular moves
52-Week Range Valuation context
Recovery/Decline Major shifts
Dividend Yield Income analysis

Comparative Analysis

Peer Comparison

Metric What to Compare
Return Relative performance
Volatility Risk comparison
Correlation Movement similarity
Volume Liquidity comparison

Benchmark Comparison

Benchmark Usage
S&P 500 Large cap reference
Sector ETF Industry context
Nasdaq Tech comparison
Russell 2000 Small cap reference

Analysis Tips

  1. Consider context: Market conditions affect individual stocks.

  2. Adjust for events: Earnings, dividends, splits affect prices.

  3. Use volume confirmation: Price moves need volume support.

  4. Multiple timeframes: Longer and shorter perspectives.

  5. Compare to peers: Relative performance matters.

  6. Watch key levels: Round numbers, 52-week highs/lows.

Use Cases

  • Trading analysis: Entry and exit timing
  • Performance tracking: Portfolio monitoring
  • Event analysis: Earnings, news impact
  • Volatility assessment: Risk evaluation
  • Peer comparison: Relative performance
Weekly Installs
25
GitHub Stars
11
First Seen
Feb 7, 2026
Installed on
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