/compare

description: Compare 2–5 stocks head to head on one table — business quality, growth, valuation, balance sheet, momentum, risks and catalysts — then argue the pick: which one, why, what would flip it, and whether owning more than one adds anything

Head-to-Head Compare

⚠️ 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** — for **every** ticker, on the **same as-of date**: price, enterprise value (market cap + debt + leases − cash), TTM revenue, EBIT, free cash flow and stock-based compensation, invested capital for ROIC, net debt and interest expense, 3-year revenue history, NTM consensus revenue and EPS, and the last guidance change. Note each company's fiscal year-end and calendarize to a common trailing-twelve-month window — comparing one company's March year with another's December year is comparing two different economies. A comparison in which one ticker's figures are a quarter staler than the others' is biased toward whichever side the missing quarter favours. 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 ⚠️ **Live data unavailable.** The following analysis uses training-data estimates which may be significantly out of date.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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🌐 Output Language — `--lang zh-TW`

English is the default. With `--lang zh-TW` — or when the user writes in Traditional Chinese and asks for a Chinese answer — write the whole analysis in Traditional Chinese (繁體中文, Taiwan usage), keeping it machine-checkable:

• **Translate** every heading, narrative paragraph, table header and bullet. Give each metric's English name in brackets the first time it appears — 自由現金流（Free Cash Flow, FCF） — so the reader can match it to the glossary and to English analyses.
• **Keep in English** tickers, figures and units, SEC form and item names (10-K Item 7, Form 4), the four `Data & Sources` field labels (`As of`, `Source`, `Retrieval`, `Confidence` — the Retrieval value may be written in Chinese, e.g. 使用者提供), and the Investment Signal box and JSON footer exactly as specified — field names and the BULLISH / NEUTRAL / BEARISH, HIGH / MEDIUM / LOW, BUY / HOLD / SELL, STRONG / MODERATE / WEAK values. Tools parse them.
• Title the invalidation section **論點失效條件（Thesis Invalidation）**, and close with the disclaimer in Chinese: **免責聲明：** 僅供教育用途，非投資建議。
• Use Taiwan financial terms: 殖利率、本益比、營業利益率、自由現金流、聯準會、選擇權、買權／賣權、除息日、預扣稅.

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Overview

The most common real question an investor asks is not "is this stock good?" but **"I can only buy one of these — which?"** Running `stock-eval` three times answers the wrong question: three independent scores on three different days, each with its own assumptions, and no argument about the *trade-off* between them. `stock-screener` ranks dozens of names mechanically but does not argue; `competitor-analysis` studies one company's moat against its rivals but does not pick.

**This skill puts 2–5 tickers on one table, scores each dimension on the same explicit scale, and then argues the pick.** It produces a 0–10 sub-score per dimension with the formula shown, a weighted composite per ticker, and then the part that matters: *which one, why that one, what single fact would flip the choice, whether owning more than one adds diversification or just doubles the same bet,* and a **"same business, different price"** check that asks why the market prices two similar companies differently before calling the cheaper one a bargain.

**How it differs from its neighbours:**

| Skill | Question it answers | Unit of analysis | |-------|---------------------|------------------| | `stock-screener` | Which of these 20–50 names deserve a closer look? | Many names, mechanical ranking | | **`compare`** | **Which of these 2–5 should I own, and why?** | **Few names, argued pick** | | `competitor-analysis` | How strong is *this* company's position against its rivals? | One company, its industry | | `stock-eval` / `stock-valuation` | Is *this* stock good / cheap on its own? | One company, absolute |

Run `stock-screener` to get from many to few; run `compare` to get from few to one; run `stoc