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Tencent SkillHub ยท Data Analysis

Equity Analyst Test

Analyze Korean stock fundamentals, news, and technicals using a strict weighted framework to score investment attractiveness and give BUY/HOLD/AVOID recommen...

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High Signal

Analyze Korean stock fundamentals, news, and technicals using a strict weighted framework to score investment attractiveness and give BUY/HOLD/AVOID recommen...

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Install for OpenClaw

Quick setup
  1. Download the package from Yavira.
  2. Extract the archive and review SKILL.md first.
  3. Import or place the package into your OpenClaw setup.

Requirements

Target platform
OpenClaw
Install method
Manual import
Extraction
Extract archive
Prerequisites
OpenClaw
Primary doc
SKILL.md

Package facts

Download mode
Yavira redirect
Package format
ZIP package
Source platform
Tencent SkillHub
What's included
references/framework.md, scripts/analyze.py, SKILL.md

Validation

  • Use the Yavira download entry.
  • Review SKILL.md after the package is downloaded.
  • Confirm the extracted package contains the expected setup assets.

Install with your agent

Agent handoff

Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.

  1. Download the package from Yavira.
  2. Extract it into a folder your agent can access.
  3. Paste one of the prompts below and point your agent at the extracted folder.
New install

I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.

Upgrade existing

I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.

Trust & source

Release facts

Source
Tencent SkillHub
Verification
Indexed source record
Version
1.0.0

Documentation

ClawHub primary doc Primary doc: SKILL.md 20 sections Open source page

Equity Analyst Skill

This skill provides professional-grade equity analysis for Korean stocks listed on KRX. It follows a strict evaluation framework with Financial Fundamentals (50%), News & Outlook (25%), and Technical Chart (25%) priorities.

When to Use This Skill

User requests stock analysis with specific ticker or company name (e.g., "์‚ผ์„ฑ์ „์ž ๋ถ„์„ํ•ด์ค˜", "SKํ•˜์ด๋‹‰์Šค ํˆฌ์ž ๋งค๋ ฅ๋„ ์•Œ๋ ค์ค˜") User asks for investment recommendation (BUY/HOLD/AVOID) with supporting reasoning Need systematic, conservative, logic-driven evaluation based on financial metrics Do NOT use for: Non-Korean stocks, cryptocurrency, or when user wants casual/opinion-based advice without rigorous framework.

Quick Start

Identify the stock ticker (e.g., 005930 for ์‚ผ์„ฑ์ „์ž, 000660 for SKํ•˜์ด๋‹‰์Šค) Use browser tool to navigate to Naver Finance page: https://finance.naver.com/item/main.naver?code={ticker} Extract required data (see Data Requirements below) Apply evaluation framework (see Framework section) Generate structured report in specified format

Data Requirements

Collect the following data from Naver Finance main page:

Financial Metrics

PER (Price Earnings Ratio) PBR (Price Book-value Ratio) ROE (Return on Equity) - ์ง€๋ฐฐ์ฃผ์ฃผ ๊ธฐ์ค€ Operating Margin (์˜์—…์ด์ต๋ฅ ) Debt Ratio (๋ถ€์ฑ„๋น„์œจ) Revenue Growth (๋งค์ถœ ์„ฑ์žฅ๋ฅ ) - recent multi-year trend (2024โ†’2025 ์˜ˆ์ƒ ์‚ฌ์šฉ)

News & Outlook (summary)

Recent major news headlines (last few days) Earnings outlook (์ปจ์„ผ์„œ์Šค, ์˜ˆ์ƒ) Industry tailwinds/headwinds Analyst sentiment changes

Technical/Chart Conditions (summary)

Trend direction (์ƒ์Šน/ํšก๋ณด/ํ•˜๋ฝ) Current price position relative to 52-week high/low Volume characteristics (ํ™•์žฅ/์ˆ˜์ถ•/๋ณดํ†ต) Any notable patterns (support/resistance, etc.) Note: Bollinger Band and other complex indicators are NOT required. Keep chart description simple: trend + current state.

Evaluation Framework

Follow these steps EXACTLY in order:

STEP 1: FINANCIAL SCORE (50%)

Score each sub-category 0-100: A. Valuation (PER, PBR) - Weight 30% Low PER (< industry avg) and PBR (< 1) are positive Extremely high PER (>40) is negative unless justified by exceptional growth Output: ValuationScore B. Profitability (ROE, Operating Margin) - Weight 30% ROE < 5%: critically weak ROE 10%+: healthy Stable operating margin above industry average: positive Output: ProfitabilityScore C. Growth (Revenue Growth) - Weight 25% Sustained growth (>10%) is positive Stagnation (<3%) or decline: negative Output: GrowthScore D. Stability (Debt Ratio) - Weight 15% Low debt (<50%) is positive High leverage (>100%) is negative Output: StabilityScore FinancialScore = Valuationร—0.30 + Profitabilityร—0.30 + Growthร—0.25 + Stabilityร—0.15 Special Rule: If BOTH ProfitabilityScore AND GrowthScore are below 30, cap FinancialScore at maximum 50 ( regardless of other scores ).

STEP 2: NEWS & OUTLOOK SCORE (25%)

Evaluate qualitative factors: Earnings outlook strength Product/service momentum Analyst sentiment direction Industry tailwinds vs headwinds Rules: Strong positive catalysts (new contracts, regulatory approval, market expansion) raise score Neutral or "wait-and-see" tone: 40-55 Hype without financial backing: MUST NOT score high (max 60) Negative catalysts ( lawsuits, customer loss, industry downturn) lower score Output: NewsScore (0-100)

STEP 3: TECHNICAL / CHART SCORE (25%)

Evaluate timing and market behavior: Trend direction (up/sideways/down) Volume expansion/contraction Signs of accumulation or distribution Current price position (near support/resistance) Rules: Charts determine TIMING, not value Strong fundamentals + weak charts = still low chart score Technicals must NEVER override poor fundamentals Focus on whether now is a good entry/exit timing based on chart alone Output: ChartScore (0-100)

FINAL SCORE

FinalScore = (FinancialScore ร— 0.50) + (NewsScore ร— 0.25) + (ChartScore ร— 0.25)

Verdict Categories

BUY: 80โ€“100 (strong conviction) BUY_LEAN: 65โ€“79 (cautious buy) HOLD: 45โ€“64 (wait/accumulate on dips) AVOID: below 45 (too risky or unattractive)

Output Format

  • Return EXACTLY this structure:
  • 1. Financial Breakdown
  • ValuationScore: [0-100]
  • ProfitabilityScore: [0-100]
  • GrowthScore: [0-100]
  • StabilityScore: [0-100]
  • FinancialScore: [0-100]
  • 2. NewsScore: [0-100]
  • 3. ChartScore: [0-100]
  • 4. Final Investment Attractiveness Score: XX / 100
  • 5. Verdict: [BUY|BUY_LEAN|HOLD|AVOID]
  • 6. Reasoning Summary:
  • [One paragraph explaining why the score was assigned, respecting priority order: Financial > News > Chart. Be conservative, logic-driven. Do NOT give investment advice.]

Example 1: SKํ•˜์ด๋‹‰์Šค (from real data)

  • 1. Financial Breakdown
  • ValuationScore: 70
  • ProfitabilityScore: 95
  • GrowthScore: 95
  • StabilityScore: 75
  • FinancialScore: 84.5
  • 2. NewsScore: 70
  • 3. ChartScore: 55
  • 4. Final Investment Attractiveness Score: 73.5 / 100
  • 5. Verdict: BUY_LEAN
  • 6. Reasoning Summary:
  • SKํ•˜์ด๋‹‰์Šค๋Š” ์žฌ๋ฌด์ œํ‘œ๊ฐ€ ๋งค์šฐ ๊ฐ•๋ ฅํ•ฉ๋‹ˆ๋‹ค. ROE 43.20%, ์˜์—…์ด์ต๋ฅ  46.67%, 43.7%์˜ ๋งค์ถœ ์„ฑ์žฅ๋ฅ ์€ ์—…๊ณ„ ์ตœ์ƒ์œ„ ์ˆ˜์ค€์ด๋ฉฐ, PER 17.11๋ฐฐ๋Š” ์ƒ๋Œ€์ ์œผ๋กœ ์ €ํ‰๊ฐ€๋˜์–ด ์žˆ์Šต๋‹ˆ๋‹ค. ๋ถ€์ฑ„๋น„์œจ 64.12%๋Š” ๋ฐ˜๋„์ฒด ์—…์ฒด๋กœ์„œ ์ ์ •๋ฒ”์œ„ ๋‚ด์— ์žˆ์Šต๋‹ˆ๋‹ค. ๋‰ด์Šค ์ธก๋ฉด์—์„œ๋Š” HBM4 ๊ณต๊ธ‰๊ณผ AI memory ์ˆ˜์š” ์ฆ๊ฐ€๊ฐ€ ์ฃผ๊ฐ€์— ๊ธ์ •์ ์ด๋‚˜, ์™ธ๊ตญ์ธ ๋งค๋„์„ธ๊ฐ€ ์ผ๋ถ€ ๋ถ€์ •์  ์˜ํ–ฅ์„ ๋ฏธ์น˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ๊ธฐ์ˆ ์  ์ธก๋ฉด์—์„œ๋Š” ์žฅ๊ธฐ ์ƒ์Šน์ถ”์„ธ๋Š” ์œ ์ง€๋˜๊ณ  ์žˆ์œผ๋‚˜, ๋‹จ๊ธฐ์ ์œผ๋กœ ์กฐ์ • ๊ตญ๋ฉด์— ์žˆ์–ด ๋งค์ˆ˜ ํƒ€์ด๋ฐ์— ์‹ ์ค‘์„ ๊ธฐํ•  ํ•„์š”๊ฐ€ ์žˆ์Šต๋‹ˆ๋‹ค. ์žฌ๋ฌด์  ์šฐ์ˆ˜์„ฑ๊ณผ ์„ฑ์žฅ์„ฑ์—๋„ ๋ถˆ๊ตฌ, ๋‹จ๊ธฐ ์ฐจํŠธ์˜ ๋ถˆํ™•์‹ค์„ฑ์œผ๋กœ ์ธํ•ด "buy with caution" ์ƒํƒœ๋กœ ํ‰๊ฐ€๋ฉ๋‹ˆ๋‹ค.

Example 2: Weak Fundamentals

... (similar structure) ... ValuationScore: 25 (PER 150, PBR 8.5 - extremely overvalued) ProfitabilityScore: 20 (ROE 2%, margin negative) ... Verdict: AVOID ...

Scripts

The skill includes these scripts: scripts/analyze.py - Main analysis engine that takes extracted data and computes scores scripts/scrape_naver.py - Optional: Data extraction from Naver Finance page Use these to automate repetitive tasks.

References

Detailed evaluation criteria and examples: references/framework.md

Notes

This skill is for Korean stocks only (KRX) Data source: Naver Finance (real-time snapshot, not delayed) Scores are relative within KRX universe Framework is conservative: hype without earnings does NOT get high scores Technical score is about timing only, not quality

Troubleshooting

Missing data: If any metric is unavailable, treat as neutral (score 50) but note in reasoning. Conflicting signals: Follow priority order: Financial > News > Chart. Low financial score can NOT be compensated by good news or chart. Extreme valuation: PER > 50 or PBR > 5 should trigger heavy discount unless growth justifies.

Category context

Data access, storage, extraction, analysis, reporting, and insight generation.

Source: Tencent SkillHub

Largest current source with strong distribution and engagement signals.

Package contents

Included in package
2 Docs1 Scripts
  • SKILL.md Primary doc
  • references/framework.md Docs
  • scripts/analyze.py Scripts