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us-stock-analyzer

作者 finskills · GitHub ↗ · v1.0.1 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install finskills-us-stock-analyzer
功能描述
Perform institutional-grade analysis of any US-listed stock using real-time and fundamental data from the Finskills API.
使用说明 (SKILL.md)

US Stock Analyzer

Perform institutional-grade analysis of any US-listed stock using real-time and fundamental data from the Finskills API. Delivers a structured investment report covering business quality, financial health, valuation, analyst consensus, and key risks — all in a single conversation turn.


Setup

API Key requiredRegister at https://finskills.net to get your free key (Pro plan for full functionality).
Set your key as: FINSKILLS_API_KEY=your_key_here
All requests use header: X-API-Key: \x3Cyour_api_key>


When to Activate This Skill

Activate when the user:

  • Asks to "analyze", "research", "evaluate", or "deep dive" into a specific stock
  • Provides a ticker symbol and asks for an investment opinion
  • Requests a buy/sell/hold assessment on a US equity
  • Asks for fundamental analysis, valuation, or earnings quality review

Required Information

Before starting, resolve:

  1. Ticker symbol — e.g., AAPL, NVDA, MSFT. Ask if not provided.
  2. Analysis depth — Quick (Level 1), Standard (Level 2, default), or Deep (Level 3).
  3. Investment horizon — Short-term (\x3C 3 months), medium (3–12 months), long-term (> 12 months). Default: long-term.

Data Retrieval — Finskills API Calls

Make the following API calls in parallel (all require X-API-Key header):

1. Real-Time Quote

GET https://finskills.net/v1/stocks/quote/{SYMBOL}

Extract: price, change, changePercent, volume, marketCap, week52High, week52Low, avgVolume

2. Company Profile

GET https://finskills.net/v1/stocks/profile/{SYMBOL}

Extract: name, sector, industry, description, employees, website, country, exchange

3. Financial Statements (3–5 years)

GET https://finskills.net/v1/stocks/financials/{SYMBOL}

Extract from income statement: revenue, grossProfit, operatingIncome, netIncome, eps
Extract from balance sheet: totalDebt, cashAndEquivalents, totalAssets, totalEquity
Extract from cash flow: operatingCashFlow, freeCashFlow, capitalExpenditures

4. Analyst Recommendations

GET https://finskills.net/v1/stocks/recommendations/{SYMBOL}

Extract: strongBuy, buy, hold, sell, strongSell counts; consensus rating; mean target price; price target range

5. Earnings History & Estimates

GET https://finskills.net/v1/stocks/earnings/{SYMBOL}

Extract: last 4 quarters of EPS (actual vs estimate, beat/miss); next quarter EPS estimate; revenue estimates

6. Institutional Holders (optional, Level 2+)

GET https://finskills.net/v1/stocks/holders/{SYMBOL}

Extract: top 5 holders, total institutional ownership %, recent changes (bought/sold)


Analysis Workflow

Step 1 — Data Validation

Confirm all API calls returned success: true. Note which data provider served each call (source field). Flag any stale data (cached > 24h for quotes).

Step 2 — Business Quality Assessment

Score each dimension 1–5:

Dimension Signals to Look For
Competitive Moat Market leadership, pricing power, switching costs, network effects
Management Quality Capital allocation history, FCF conversion, debt management
Revenue Quality Recurring/subscription vs one-time, customer concentration
Growth Trajectory YoY revenue growth trend (accelerating/decelerating/stable)

Calculate a composite Business Quality Score (BQS) = average of the four dimensions.

Step 3 — Financial Health Scorecard

Compute and interpret:

Metric Formula Benchmark
Gross Margin grossProfit / revenue Industry-specific
Operating Margin operatingIncome / revenue > 15% healthy
FCF Margin freeCashFlow / revenue > 10% excellent
Net Debt / EBITDA (totalDebt − cash) / EBITDA \x3C 2x conservative
ROE netIncome / totalEquity > 15% strong
FCF Yield freeCashFlow / marketCap > 4% attractive
Current Ratio currentAssets / currentLiabilities > 1.5 healthy

Flag any metric outside healthy range with a ⚠️ symbol.

Step 4 — Valuation Analysis

Calculate:

Ratio Formula Context
P/E (TTM) price / EPS_TTM vs sector average
Forward P/E price / EPS_NextYear_estimate vs 5-yr historical avg
EV/EBITDA (marketCap + netDebt) / EBITDA \x3C 15x value zone
P/FCF marketCap / freeCashFlow vs growth peers
PEG Ratio P/E / EPS_3yr_growth \x3C 1.0 undervalued

Classify valuation as: Deep Value / Fair Value / Premium / Stretched

Provide a range-based fair value estimate using at least two methods (DCF implied from FCF yield, and P/E reversion to sector mean).

Step 5 — Earnings Quality & Analyst Coverage

Analyze earnings history (last 4 quarters):

  • Beat rate: percentage of quarters beating EPS estimates
  • Average surprise magnitude (positive/negative)
  • Revenue trend vs EPS trend (divergence signals accounting risk)

Analyst consensus summary:

  • Consensus rating label (Strong Buy / Buy / Hold / Underperform / Sell)
  • Mean price target vs current price (implied upside/downside %)
  • Breadth: number of analysts covering the stock
  • Target price range (bull case vs bear case)

Step 6 — Risk Identification

Systematically identify:

  • Balance sheet risk: leverage, debt maturity, liquidity
  • Earnings risk: customer concentration, cyclicality, margin pressure trends
  • Macro risk: interest rate sensitivity, FX exposure, commodity input costs
  • Regulatory/ESG risk: industry-specific regulatory environment
  • Valuation risk: how much multiple compression would hurt total return

Step 7 — Investment Verdict

Based on all data, output:

  • Rating: STRONG BUY / BUY / HOLD / AVOID / SELL
  • 12-Month Price Target: derived from valuation analysis (base case)
  • Bull Case / Bear Case: target under favorable / adverse scenario
  • Confidence Level: HIGH / MEDIUM / LOW (based on data completeness and earnings predictability)

Output Format

═══════════════════════════════════════════════════
  US STOCK ANALYSIS REPORT — {TICKER} ({DATE})
═══════════════════════════════════════════════════

📌 COMPANY SNAPSHOT
  {Company Name} | {Sector} | {Industry}
  Price: ${price}  Change: {change}%  Market Cap: ${marketCap}
  52-Week Range: ${week52Low} — ${week52High}

📊 BUSINESS QUALITY SCORE: {BQS}/5
  ◦ Competitive Moat:   {score}/5 — {brief rationale}
  ◦ Management Quality: {score}/5 — {brief rationale}
  ◦ Revenue Quality:    {score}/5 — {brief rationale}
  ◦ Growth Trajectory:  {score}/5 — {brief rationale}

💰 FINANCIAL HEALTH
  Revenue Growth (YoY): {%}  |  Gross Margin: {%}  |  Operating Margin: {%}
  FCF Margin: {%}  |  Net Debt/EBITDA: {x}  |  ROE: {%}
  [⚠️ Flag any concerns]

📐 VALUATION
  TTM P/E: {x}  |  Forward P/E: {x}  |  EV/EBITDA: {x}
  P/FCF: {x}    |  PEG: {x}
  Assessment: {Deep Value / Fair Value / Premium / Stretched}
  Fair Value Range: ${low} — ${high}

📈 ANALYST CONSENSUS
  Rating: {consensus}  |  Mean Target: ${target}  ({upside}% upside)
  Distribution: {strongBuy}SB / {buy}B / {hold}H / {sell}S / {strongSell}SS
  Analysts: {count}  |  Target Range: ${low} — ${high}

📋 EARNINGS QUALITY
  Beat Rate: {%} ({n}/{total} quarters)  |  Avg Surprise: {+/-}%
  Next Quarter EPS Estimate: ${estimate}

⚠️ KEY RISKS
  1. {Risk 1}
  2. {Risk 2}
  3. {Risk 3}

🎯 INVESTMENT VERDICT
  Rating:         {STRONG BUY / BUY / HOLD / AVOID / SELL}
  12M Target:     ${target}  (Base: ${base} | Bull: ${bull} | Bear: ${bear})
  Confidence:     {HIGH / MEDIUM / LOW}
  Horizon:        {investment horizon}

  Thesis Summary: {2–3 sentence bull case}
  Key Risks:      {1–2 sentence risk summary}
═══════════════════════════════════════════════════

Formatting Rules

  • Always show data source (source field from API response) in a footnote.
  • If an API call fails, note "Data unavailable" for that section — do not omit the section header.
  • Round monetary values to 2 decimal places; percentages to 1 decimal place.
  • Do not provide financial advice. Frame all outputs as analytical research.

Limitations

  • Financial statements may lag by 1 quarter (SEC filing cadence).
  • Analyst targets represent consensus forecasts, not guarantees.
  • This skill does not execute trades or interact with brokerage accounts.
安全使用建议
This skill appears to do what it says: fetch data from finskills.net and produce financial analyses. Before installing, verify the following: (1) Confirm the registry metadata vs SKILL.md discrepancy — ensure the platform will prompt for FINSKILLS_API_KEY at install/runtime. (2) Use an API key with least privilege and billing limits (create a dedicated key for the skill, not a broad account key). (3) Review the upstream repo (https://github.com/finskills/us-stock-analyzer) for any code changes or hidden behavior before trusting a packaged version. (4) Test by running the skill with a throwaway key or limited quota and monitor network calls to finskills.net. (5) Check the Finskills API terms and what data the provider logs or shares (privacy/billing). If you find additional required env vars, unexpected endpoints, or included code files that perform disk/network operations, re-evaluate — those would raise the risk to 'suspicious'.
功能分析
Type: OpenClaw Skill Name: finskills-us-stock-analyzer Version: 1.0.1 The skill is a legitimate tool for performing US stock analysis using the Finskills API (finskills.net). It retrieves financial data, analyst ratings, and company profiles to generate structured reports. There is no evidence of data exfiltration, malicious command execution, or prompt injection attacks; all activities are strictly aligned with the stated purpose of financial research.
能力标签
cryptorequires-sensitive-credentials
能力评估
Purpose & Capability
The name/description match the runtime instructions: all data is fetched from the Finskills API and used to compute financial scores and valuations. The declared required credential (FINSKILLS_API_KEY) in SKILL.md is appropriate for the stated purpose. The main inconsistency is registry metadata claiming no required env vars while SKILL.md explicitly requires an API key.
Instruction Scope
SKILL.md only instructs the agent to call Finskills endpoints and compute financial metrics. It does not direct the agent to read local files, other environment variables, or to send data to third-party endpoints outside finskills.net. The analysis workflow is narrow and well-scoped to the stated purpose.
Install Mechanism
This is an instruction-only skill with no install spec and no code files — lowest-risk install surface. There are no downloads or archive extracts described.
Credentials
SKILL.md requires a single API key (FINSKILLS_API_KEY), which is proportionate to a service that calls an external API. However, the registry metadata omitted required env vars, creating an incoherence that should be resolved before trusting the package listing.
Persistence & Privilege
The skill does not request always:true and has no install-time persistence instructions. It does not ask to modify other skills or system-wide settings.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install finskills-us-stock-analyzer
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /finskills-us-stock-analyzer 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.1
- Added formal skill manifest (YAML frontmatter) specifying name, version, author, homepage, and credentials. - Improved formatting of setup instructions for greater clarity; moved API registration link to a more prominent position. - No changes to analysis methodology or output format. - No functional or code changes detected; changes are documentation and metadata only.
v1.0.0
US Stock Analyzer skill initial release. - Generate institutional-grade analysis on any US-listed stock in a single turn using real-time and fundamental data via Finskills API. - Structured investment reports include business quality scoring, financial health, valuation, analyst consensus, earnings quality, and risk identification. - Supports analysis depth (quick/standard/deep) and customizable investment horizon; prompts user for ticker if missing. - Detailed setup, activation cues, data extraction steps, and report formatting guidelines provided. - All API requests require a Finskills Pro API key and proper authentication via header. - Handles incomplete or unavailable data gracefully, maintaining output consistency.
元数据
Slug finskills-us-stock-analyzer
版本 1.0.1
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 2
常见问题

us-stock-analyzer 是什么?

Perform institutional-grade analysis of any US-listed stock using real-time and fundamental data from the Finskills API. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 78 次。

如何安装 us-stock-analyzer?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install finskills-us-stock-analyzer」即可一键安装,无需额外配置。

us-stock-analyzer 是免费的吗?

是的,us-stock-analyzer 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

us-stock-analyzer 支持哪些平台?

us-stock-analyzer 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 us-stock-analyzer?

由 finskills(@finskills)开发并维护,当前版本 v1.0.1。

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