AgentSkillsCN

stock-performance

利用Octagon MCP获取股票价格数据与各项表现指标。当您需要分析每日收盘价、成交量、价格走势、历史表现,或在特定时间段内对比股票的涨跌时,此技能将助您一臂之力。

SKILL.md
--- frontmatter
name: stock-performance
description: Retrieve stock price data and performance metrics using Octagon MCP. Use when analyzing daily closing prices, trading volume, price trends, historical performance, and comparing stock movements over specific time periods.

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:

code
Retrieve the daily closing prices for <TICKER> over the last <N> days.

MCP Call Format:

json
{
  "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:

DateClosing PriceVolume
2026-02-02$270.0173,677,607
2026-01-30$259.4892,443,408
2026-01-29$258.2867,253,009
.........

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:

code
Retrieve the daily closing prices for AAPL over the last 30 days.

Extended Historical Data:

code
Get historical stock prices for MSFT for the past 90 days.

Volume Analysis:

code
Retrieve daily trading volume for TSLA over the last 2 weeks.

Price Range:

code
What are the high and low prices for NVDA over the past month?

Multi-Stock Comparison:

code
Compare the stock performance of AAPL, MSFT, and GOOGL over the last 30 days.

52-Week Analysis:

code
What is the 52-week high and low for AMZN?

Key Metrics

Price Metrics

MetricDescription
Closing PriceEnd-of-day price
Opening PriceStart-of-day price
HighIntraday high
LowIntraday low
Adjusted CloseDividend/split adjusted

Volume Metrics

MetricDescription
Daily VolumeShares traded per day
Average VolumeTypical daily volume
Relative VolumeCurrent vs. average
Volume TrendDirection over time

Return Metrics

MetricCalculation
Daily Return(Close - Prior Close) / Prior Close
Period Return(End - Start) / Start
Cumulative ReturnRunning return over period
Annualized ReturnPeriod return scaled to 1 year

Price Analysis Framework

Trend Analysis

PatternCharacteristics
UptrendHigher highs, higher lows
DowntrendLower highs, lower lows
SidewaysRange-bound movement
BreakoutMove beyond range

Volatility Assessment

MeasureDescription
Price RangeHigh - Low over period
Daily RangeAverage daily high-low
Standard DeviationPrice dispersion
BetaRelative to market

Support/Resistance

LevelDescription
SupportPrice floor, buying interest
ResistancePrice ceiling, selling pressure
Moving AveragesDynamic support/resistance
Round NumbersPsychological levels

Volume Analysis

Volume Patterns

PatternInterpretation
High Volume + Price UpStrong buying conviction
High Volume + Price DownStrong selling pressure
Low Volume + Price UpWeak rally, may reverse
Low Volume + Price DownLack of selling interest

Volume Indicators

IndicatorUsage
Volume SpikeUnusual activity, potential catalyst
Volume Dry-upConsolidation, waiting mode
Volume TrendConfirms price trend
On-Balance VolumeCumulative volume direction

Time Period Analysis

Short-Term (1-30 Days)

FocusUse Case
Recent PerformanceCurrent momentum
Trading SignalsEntry/exit timing
News ImpactEvent analysis
VolatilityRisk assessment

Medium-Term (1-6 Months)

FocusUse Case
Trend IdentificationDirection confirmation
SeasonalityCyclical patterns
Earnings ImpactQuarterly effects
Sector RotationRelative performance

Long-Term (1+ Years)

FocusUse Case
Major TrendsSecular moves
52-Week RangeValuation context
Recovery/DeclineMajor shifts
Dividend YieldIncome analysis

Comparative Analysis

Peer Comparison

MetricWhat to Compare
ReturnRelative performance
VolatilityRisk comparison
CorrelationMovement similarity
VolumeLiquidity comparison

Benchmark Comparison

BenchmarkUsage
S&P 500Large cap reference
Sector ETFIndustry context
NasdaqTech comparison
Russell 2000Small 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