How do I install the Stock Report skill?

Run npx skillmds@latest add erhwenkuo/stock-report in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Stock Report safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Stock Report?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Stock Report free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Stock Report?

erhwenkuo (@erhwenkuo) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Stock Report by erhwenkuo — Agent Skill

Name: Stock Report
Author: erhwenkuo

Stock Report

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.

erhwenkuo Updated Sep 17, 2026

File contents

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?

---name: stock-reportdescription: 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.---# Individual Stock Report SkillExtract the ticker symbol from $ARGUMENTS and run the following command.```bashpython3 /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 ConclusionsWhen the response includes specific investment opinions for valuation/undervaluation/value-trap assessments:> 💡 Would you like to record this analysis as an investment note?

Frequently asked questions