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/stock-eval

Evaluate US stocks with comprehensive fundamental and valuation analysis

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investskill
25034 skills
Install
$ npx -y skills add yennanliu/investskill --skill stock-eval --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/stock-eval

Context preview

The summary Claude sees to decide when to auto-load this skill.

Evaluate US stocks with comprehensive fundamental and valuation analysis

SKILL.md

stock-eval.SKILL.md
description: Evaluate US stocks with comprehensive fundamental and valuation analysis

US Stock Evaluation

⚠️ Data Verification — Do This Before Any Analysis

Before running any analysis, always retrieve the latest market data for the ticker:

1. **Fetch current price** — use web search or ask the user for the live price, 52-week range, and market cap. Never assume a price from training data. 2. **Confirm key figures** — recent earnings, revenue, key ratios (P/E, P/S, etc.) as applicable to this skill. 3. **State your data source** — fill in the `Data & Sources` header (next section) so the origin, as-of date, retrieval path, and confidence of every figure are explicit at the top of the output. 4. **Flag stale data explicitly** — if live data is unavailable, display this warning before proceeding:

> ⚠️ **Live data unavailable.** The following analysis uses training-data estimates which may be significantly out of date. Verify all prices and metrics before making any decisions.

Never silently substitute training-data estimates for current prices. When in doubt, ask the user to paste the latest quote.

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📋 Data & Sources Header — Open Every Output With It

The first thing in the output is this provenance block, filled in — never left as placeholders. It is the standard documented on the [Data & Accuracy](https://yennanliu.github.io/InvestSkill/data-and-accuracy.html) page and the first thing `result-validator` looks for:

Data & Sources
  As of:      <date the figures represent, e.g. 2026-06-30>
  Source:     <primary docs — SEC EDGAR 10-K/10-Q, company IR, FRED, exchange data …>
  Retrieval:  <pasted by user | web/tool retrieval | model memory>
  Confidence: <HIGH | MEDIUM | LOW>
  • `Retrieval: model memory` must be paired with `Confidence: LOW` — memory is a placeholder until confirmed against a primary source.
  • Mixed sources: list each with its own as-of date rather than blending them.
  • Sources disagree on the same figure (a closing price, a deal term): prefer the primary source (SEC filing, company release, exchange data) over an aggregator, then the most recent dated one. Show both values with their sources and dates, say which you used and why, and never average them.
  • Data the user pasted is reported as `pasted by user`; do not upgrade its confidence beyond what the user's own source supports.

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Perform comprehensive stock evaluation combining fundamental analysis, valuation modeling, quality scoring, and risk assessment to produce investment-grade conclusions.

Analysis Components

1. Company Overview

  • Business model and competitive advantages (moat assessment)
  • Market position, addressable market size, and industry trends
  • Revenue mix by segment and geographic exposure
  • Key products, services, and customer concentration
  • Competitive dynamics and threat of disruption

2. Financial Health

  • Revenue and earnings growth trends (3-year and 5-year CAGR)
  • Profit margins: gross margin, operating margin, net margin
  • Margin trends: expanding, stable, or compressing
  • Balance sheet strength: cash, total debt, net debt, book value
  • Liquidity: current ratio, quick ratio, cash conversion cycle
  • Cash flow analysis: operating cash flow, free cash flow, FCF yield
  • Capital expenditure requirements (maintenance vs. growth capex)
  • Working capital management efficiency

3. Valuation Metrics

| Metric | Current | 1-Year Ago | 5-Year Avg | Sector Avg | |-----------------|---------|------------|------------|------------| | P/E (TTM) | | | | | | P/E (Forward) | | | | | | PEG Ratio | | | | | | Price/Book | | | | | | Price/Sales | | | | | | EV/EBITDA | | | | | | EV/FCF | | | | | | Dividend Yield | | | | | | Payout Ratio | | | | |

4. Key Ratios

| Ratio | Current | Industry Avg | Assessment | |------------------------|---------|--------------|------------| | Return on Equity (ROE) | | | | | Return on Assets (ROA) | | | | | Return on Inv. Capital | | | | | Gross Margin | | | | | Operating Margin | | | | | Net Margin | | | | | Current Ratio | | | | | Quick Ratio | | | | | Debt-to-Equity | | | | | Interest Coverage | | | | | Asset Turnover | | | |

5. Peer Comparison

  • Direct peer comparison within industry on key valuation multiples
  • Historical valuation trends vs. own 5-year history
  • Sector performance context and relative positioning
  • Market share trends vs. competitors

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Deep Financial Statement Analysis

This section provides line-item rigor absorbed from dedicated fundamental analysis workflows. Use when a deeper statement-level breakdown is required.

Income Statement Line-Item Framework

**Revenue Analysis**

  • Break revenue into organic growth vs. acquisition-driven growth vs. FX tailwind/headwind
  • Identify top revenue segments by size and growth rate; flag any segment growing faster or slower than the consolidated total
  • Assess revenue quality: recurring subscription/contract revenue vs. transactional/one-time revenue
  • Operating leverage test: does revenue growth outpace operating expense growth? Calculate incremental operating margin = ΔOperating Income / ΔRevenue

**C

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