Stock report

Skill erhwenkuo/stock_skills/.claude/skills/stock-report

An undervalued stock screening system. Screens for undervalued stocks across 60+ regions using the Yahoo Finance API (yfinance). Runs as Claude Code Skills — just speak in natural language and the right function executes automatically.

Install

npx -y skills add erhwenkuo/stock_skills --skill stock-report

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
3 stars3 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Detailed report for individual stocks and ETFs. Generates a financial analysis report from a ticker symbol. Individual stocks show valuation, undervaluation score, and shareholder return rate. ETFs show expense ratio, AUM, and fund size.

SKILL.md

2.6 KB, as published. Nobody here has run it

Individual Stock Report Skill

Extract the ticker symbol from $ARGUMENTS and run the following command.

python3 /Users/kikuchihiroyuki/stock-skills/.claude/skills/stock-report/scripts/generate_report.py $ARGUMENTS

Output Contents

Sector & Industry
Price Information: Current price, market cap
Valuation: P/E, P/B, dividend yield, ROE, ROA, earnings growth rate
Undervaluation Score: 0-100 score + judgment (undervalued/slightly undervalued/fair/overvalued)
Shareholder Returns (KIK-375): Dividend yield + buyback yield = total shareholder return rate
Contrarian Signals (KIK-504/533): Contrarian score (0-100) + grade (A/B/C/D) + 3-axis breakdown (technical/valuation/fundamental divergence)
Industry Context (KIK-433, when Neo4j connected): Auto-display tailwinds and risks from recent industry research in the same sector

ETF Auto-Detection (KIK-469)

Automatically detects ETFs (quoteType=ETF) and outputs an ETF-specific report instead of the individual stock report:

Fund Overview: Category, fund family, AUM (net assets), expense ratio
Expense Ratio Assessment: Ultra-low cost (<=0.1%) / Low cost (<=0.5%) / Slightly high (<=1.0%) / High cost (>1.0%)
Performance: Current price, dividend yield, beta, 52-week range
Fund Size: Large ($10B+) / Mid ($1B+) / Small ($100M+) / Micro (<$100M)

Display the result as-is.

Knowledge Integration Rules (KIK-466)

When get_context.py output contains the following, integrate with the report result:

Screening appearance count: "Top 3 screenings in a row → repeatedly noticed stock"
Purchase history (BOUGHT): If currently held: "As a held stock: unrealized gain +12%, thesis alignment is good"
Past reports: Diff from previous figures. "P/E: 12.3→8.5 (improved), ROE: 15%→12% (declined)"
Investment notes: Incorporate concerns and thesis into the report. "Concern note: inventory risk → latest quarter shows inventory reduction confirmed"
Research history: Reference key points from the previous research and highlight changes

Prompting to Record Analysis Conclusions

When the response includes specific investment opinions for valuation/undervaluation/value-trap assessments:

💡 Would you like to record this analysis as an investment note?