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Stock Analysis Skills

核心功能:采用10模块分析框架(含宏观、技术、基本面、估值等维度),遵循数据优先、平衡客观等原则,通过模块打分生成综合评级,给出明确投资建议。典型场景:用户请求分析个股、研究公司、做基本面分析或投资评估时触发。输入为股票代码/公司名,输出为结构化研报,含多维度分析、风险提示及可操作判定。

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最近更新 2026-06-16 15:35:13
分类:数据依赖:联网浏览搜索 / 读写文件 / 内部调用大模型应用场景:市场分析 / 报告撰写 / 财务 / 数据处理

安装技能

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执行命令安装此 skill: npx secure-skills-cli add stock-analysis-skills
Metadata
name
stock-analysis
description
This skill should be used when the user asks to "analyze a stock", "research a company", "give me a research report on [ticker]", "run stock analysis on [company]", "do fundamental analysis of [ticker]", "evaluate [company] for investment", "what do you think of [ticker]", "analyze [AAPL / TSLA / NVDA / etc.]", "deep dive on [company]", or any request for structured equity research, investment thesis, or financial analysis of a publicly traded company.
version
0.1.0

Stock Analysis Pro — Analytical Framework

This skill provides the methodology, analytical standards, and scoring logic for producing institutional-quality equity research reports across 10 structured modules. It is loaded automatically whenever a stock or company analysis is requested.


Core Analytical Principles

Apply these principles across every module of every report:

  • Data-first: Ground every assertion in current financial data, market data, or explicitly sourced intelligence. Do not make claims without evidence.
  • Multi-dimensional: No single factor determines an investment case. Integrate macro, technical, fundamental, valuation, and sentiment signals before forming a view.
  • Balanced: Present both bull and bear cases within each module. Avoid confirmation bias — if the data contradicts the prevailing narrative, say so.
  • Transparent: Explicitly flag data gaps, estimation uncertainty, and the limits of web-sourced information. Use ⚠️ where data is unavailable or estimated.
  • Actionable: Every module ends with a Key Takeaway. The final scorecard delivers a clear, justified investment stance — not "it depends."

The 10-Module Framework

Each module addresses a distinct analytical dimension and contributes to the overall investment verdict:

# Module Core Question
1 Macro Analysis Is the external environment a tailwind or headwind?
2 Stock Trend Analysis What is price action signaling about near-term direction?
3 Company Competency Is the business fundamentally strong with a durable moat?
4 Valuation Analysis Is the stock priced fairly relative to intrinsic value and peers?
5 Earnings & Analyst Forecast Are earnings growing and consistently beating expectations?
6 Competitor Benchmarking How does the company rank against its direct peers?
7 Risk Analysis What could go wrong and how severe are the consequences?
8 ESG & Governance Is the company sustainable and well-governed for the long run?
9 Catalyst & Event Tracker What near-term events could move the stock materially?
10 Investment Summary What is the bottom-line investment verdict with full rationale?

Scoring Logic (Module Scorecard)

Rate each module from 1 to 5 based on the analytical findings:

Score Meaning
5 Strongly positive signal — clear tailwind or outstanding quality
4 Moderately positive — good, with minor concerns
3 Neutral — mixed signals or insufficient differentiation
2 Moderately negative — notable headwinds or weaknesses
1 Strongly negative — significant concern, major red flag

Risk Profile (Module 7) is scored inversely: 5 = very low risk, 1 = very high risk.

The Overall Score is a simple average of the 9 module scores (excluding the summary module). Weighting guidance:

  • For short-term theses: weight Technical Trend and Catalysts more heavily
  • For long-term theses: weight Macro, Company Competency, Valuation, and ESG more heavily

Investment Stance Thresholds

Map the overall module scorecard average to a recommended analyst stance:

Overall Score Analyst Stance
4.5 – 5.0 ⭐⭐⭐⭐⭐ Strong Buy
3.5 – 4.4 ⭐⭐⭐⭐ Buy
2.5 – 3.4 ⭐⭐⭐ Hold
1.5 – 2.4 ⭐⭐ Reduce
1.0 – 1.4 ⭐ Avoid

Always articulate what would need to change for the stance to upgrade or downgrade by one level.


Data Source Hierarchy

Prioritize higher-quality sources when gathering data. Prefer recency over breadth.

  1. Company SEC filings: 10-K (annual), 10-Q (quarterly), 8-K (material events)
  2. Company investor relations pages and official earnings press releases
  3. Analyst consensus platforms: FactSet, Bloomberg, Refinitiv, LSEG (via web search)
  4. Financial data aggregators: Morningstar, Yahoo Finance, Macrotrends, Wisesheets
  5. Investment research platforms: Seeking Alpha, The Motley Fool, GuruFocus
  6. ESG rating agencies: MSCI ESG Ratings, Sustainalytics, S&P Global ESG
  7. Industry and macro data: IMF, World Bank, Federal Reserve, OECD, industry associations
  8. News and events: Reuters, Bloomberg, Financial Times, Wall Street Journal

Key Analytical Standards

Apply these standards consistently across all modules:

Financial metrics:

  • Use trailing twelve months (TTM) for income statement metrics unless forward estimates are more relevant
  • Compare multiples to both sector median and 3–5 year historical average for the same company
  • When multiples are not meaningful (e.g., negative P/E due to losses), use EV/Sales or note the limitation
  • Free cash flow yield (FCF / Market Cap) is often a more reliable signal than reported earnings multiples

Technical analysis:

  • Treat indicators as confirming or diverging signals — not standalone buy/sell triggers
  • RSI interpretation: >70 = overbought territory; <30 = oversold territory; divergence with price direction is more informative than absolute level alone
  • MACD: focus on signal line crossovers and histogram trend (expanding vs. contracting momentum)
  • Golden Cross (50-day MA crossing above 200-day MA) and Death Cross (crossing below) are significant trend signals
  • Volume confirmation: price moves on high relative volume are more reliable than low-volume moves

Valuation (DCF guidance):

  • Use a 2-stage or 3-stage model: near-term explicit forecast period (5 years) + terminal value
  • WACC should reflect sector risk: typically 8–10% for large-cap defensive, 10–14% for growth/tech, 12–16% for speculative/small-cap
  • Terminal growth rate: 2–3% for stable businesses, aligned with long-run nominal GDP growth; avoid rates above 4% without explicit justification
  • Sensitivity-test the DCF on WACC ± 1% and terminal growth rate ± 0.5% to show the fair value range

Risk assessment:

  • Assign risk levels (Low / Medium / High) based on both likelihood and severity of impact
  • A High risk designation requires at least one of: (a) high probability of occurrence, (b) potentially company-threatening consequence, or (c) a clear near-term trigger
  • ESG risk should consider both the direct financial impact of ESG failings and the reputational/regulatory overhang

Reference Files

Load these reference files for deeper methodology when needed:

  • references/macro-framework.md — Detailed macro analysis methodology: GDP, rates, inflation, regulatory landscape
  • references/technical-analysis.md — Technical indicator interpretation guide with signal tables
  • references/fundamental-framework.md — Company competency and earnings analysis methodology
  • references/valuation-framework.md — Valuation methodology including DCF construction and relative valuation
  • references/risk-esg-framework.md — Risk rating criteria and ESG/governance assessment standards