LaunchKit · 2026
Back to Skills

stock-evaluator

Comprehensive evaluation of potential stock investments combining valuation analysis, fundamental research.

15
4.3k downloads
by @demandgap

Setup & Installation

openclaw skills install @demandgap/stock-evaluator

Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:

npx clawhub install stock-evaluator

What This Skill Does

Evaluates stocks you are considering buying by combining valuation methods (DCF, relative, Peter Lynch), fundamental analysis across 5-10 years of company filings, and technical indicators including Ichimoku Cloud. Produces a buy/hold/sell recommendation with a specific entry price, position size, and conviction rating. Outputs a React dashboard with 60+ metrics covering financial health, earnings quality, insider activity, and scores against eight legendary investor frameworks.

Combines quantitative scoring (Piotroski F-Score, Altman Z-Score, Beneish M-Score), eight investor persona frameworks, and Ichimoku technical analysis into one standardized dashboard, replacing what would otherwise require separate tools and manual synthesis.

When to use it

  • Deciding whether to buy a stock sitting on your watchlist
  • Getting a specific entry price and position size before committing capital
  • Checking if a low-P/E stock is genuine value or a value trap
  • Comparing two investment candidates to choose where to deploy funds
  • Finding three to five better alternatives when a target stock looks overvalued

Example Workflow

Here's how your AI assistant might use this skill in practice.

INPUT

User asks: Should I buy ASML stock right now?

AGENT
  1. 1Searches for ASML price, P/E, market cap, analyst targets, and recent SEC filings
  2. 2Calculates Piotroski F-Score, Altman Z-Score, Beneish M-Score, and Value Trap Score from sourced financial data
  3. 3Scores the stock against eight investor frameworks (Buffett, Lynch, Graham, Dalio, and others) on a 0-10 scale
  4. 4Runs DCF, peer relative, and Peter Lynch valuation methods to derive fair value and margin of safety
  5. 5Produces a buy/hold/sell recommendation with entry range, stop loss, and position size, then renders the quant React dashboard
OUTPUT

BUY recommendation with €680-€710 entry range, 3-5% position size, 12-month base case target of €820, stop loss at €640, and a full React dashboard showing all 60+ metrics across eight metric sections