Agent skill

Dividend Stock Analysis

by HKUDS in HKUDS/Vibe-Trading

Separates durable dividends from yield traps by checking yield quality, payout coverage, balance sheet strength, dividend history and valuation, with sector-specific payout measures.

MITAuto-check passedBusiness, Finance & HR

Install Dividend Stock Analysis

skills CLI
$ npx skills add HKUDS/Vibe-Trading --skill dividend-analysis -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install HKUDS/Vibe-Trading dividend-analysis --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/HKUDS/Vibe-Trading.git skills-src && mkdir -p .claude/skills && cp -r skills-src/agent/src/skills/dividend-analysis .claude/skills/dividend-analysis && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
dividend-analysis
GitHub stars
35k
Token cost
~2k tokens
SKILL.md length
912 words
Files
1
Skills in repo
89
Repo updated
First seen
Licence
MIT

At a glance

Separates durable dividends from yield traps by checking yield quality, payout coverage, balance sheet strength, dividend history and valuation, with sector-specific payout measures.

  • Works in 5 steps: Normalize the Dividend → Check Coverage → Diagnose Dividend Growth Quality → …
  • Screening for high-yield stocks without falling into yield traps
  • SKILL.md covers Purpose, Core Questions, Key Metrics and Analysis Workflow, plus 5 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Analysis never stops at the headline yield. The agent asks whether the payout is covered by earnings, operating cash flow and free cash flow, whether the balance sheet can survive a downturn, how management has treated the dividend through cycles, and whether valuation still leaves room for total return after taxes and reinvestment. A metrics table gives formulas with healthy and warning signals for yield, earnings payout, free-cash-flow payout, cash flow coverage, dividend growth, debt load and combined buyback and dividend yield.

Payout measures are adapted for REITs, utilities, banks, MLPs and insurers, for example AFFO payout for REITs and distributable cash flow for MLPs. The workflow begins by normalizing the dividend: using the forward indicated amount, separating special from ordinary dividends, identifying the payment frequency, and accounting for depositary ratios, withholding tax and currency for ADRs and cross-listed shares.

When your agent uses it

  • Screening for high-yield stocks without falling into yield traps
  • Checking whether a company's dividend is covered by free cash flow
  • Planning an income or dividend-growth portfolio
  • Working out ex-dividend mechanics and dividend normalization for ADRs

Example prompts

  • “Is the dividend of this utility sustainable? Check the payout against earnings and free cash flow.”
  • “Screen these five stocks for yield traps and rank them by dividend safety.”
  • “Which payout metric should I use for a REIT instead of the earnings payout ratio?”
  • “Explain how the ex-dividend date affects the share price and who receives the payment.”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Normalize the Dividend
  2. Check Coverage
  3. Diagnose Dividend Growth Quality
  4. Check Balance Sheet Flexibility
  5. Separate Dividend Yield from Total Return

What it can do on your machine

Read from SKILL.md and the folder at commit 14cabaf. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are python and markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Dividend Stock Analysis loads about 2k tokens when it runs. Until then it costs about 50 tokens; SKILL.md has 912 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~50
When it runs · the whole SKILL.md, loaded when a task matches
~2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from HKUDS/Vibe-Trading at commit 14cabaf, republished under its MIT licence (© HKUDS). 912 words, ~2,025 tokens.

Download SKILL.mdSave it as .claude/skills/dividend-analysis/SKILL.md (or your agent's skills folder).
name
dividend-analysis
description
Dividend stock analysis for income, dividend-growth, and shareholder-return strategies, including yield quality, payout sustainability, ex-dividend mechanics, and yield-trap checks.
category
analysis

Dividend Analysis

Purpose

Use this skill when the user asks about dividend stocks, income portfolios, dividend growth, high-yield screening, payout safety, ex-dividend dates, or whether a dividend is sustainable. The goal is to separate durable shareholder returns from yield traps.

Dividend analysis should never stop at headline yield. A good answer explains how the dividend is funded, how stable the underlying business is, whether management has room to keep paying, and how valuation changes the expected total return.

Core Questions

  1. What is the current cash yield, and is it normal for this company or sector?
  2. Is the payout covered by earnings, operating cash flow, and free cash flow?
  3. Is the balance sheet strong enough to absorb a down cycle?
  4. Has management grown, held, cut, or suspended the dividend across cycles?
  5. Does the valuation still leave room for total return after taxes and reinvestment assumptions?

Key Metrics

MetricFormulaHealthy SignalWarning Signal
Dividend yieldannual DPS / current priceAbove peer median with stable coverageExtremely high vs history or peers
Earnings payout ratiodividends / net income, or DPS / EPS30-70% for mature non-financialsAbove 90%, negative earnings
Free-cash-flow payoutdividends / FCFBelow 70% through a cycleDividend exceeds FCF for 2+ years
CFO coverageoperating cash flow / dividends paidAbove 1.5xBelow 1.0x
Dividend CAGRDPS growth over 3/5/10 yearsPositive and below EPS/FCF growthGrowth funded by leverage
Net debt / EBITDAnet debt / EBITDASector-appropriate leverageLeverage rising while payout rises
Buyback plus dividend yield(dividends + net buybacks) / market capBalanced capital returnBuybacks funded by debt at high valuation

For REITs, utilities, banks, MLPs, and insurers, adapt the payout metric to the sector. For example, use AFFO payout for REITs, distributable cash flow for MLPs, and regulatory capital ratios for banks and insurers.

Analysis Workflow

Step 1: Normalize the Dividend
  • Use forward indicated dividend for recurring payments.
  • Separate ordinary dividends from special dividends.
  • Check whether the latest declared dividend is annual, semiannual, quarterly, monthly, or irregular.
  • For ADRs and cross-listed shares, account for depositary ratios, withholding tax, and FX conversion.
python
annual_dividend = regular_dividend_per_period * payments_per_year
dividend_yield = annual_dividend / current_price
Step 2: Check Coverage

Start with earnings coverage, then confirm with cash coverage.

python
earnings_payout = dividends_paid / net_income
fcf_payout = dividends_paid / free_cash_flow
cfo_coverage = operating_cash_flow / dividends_paid

Interpretation:

  • Good: net income, CFO, and FCF all cover dividends across multiple years.
  • Watch: earnings cover dividends but FCF does not, especially during capex-heavy periods.
  • Avoid: dividends are paid while both earnings and FCF are negative, unless there is a clear one-time reason and a strong balance sheet.
Step 3: Diagnose Dividend Growth Quality

Dividend growth is high quality when it follows business growth.

python
dividend_cagr = (dps_end / dps_start) ** (1 / years) - 1
eps_cagr = (eps_end / eps_start) ** (1 / years) - 1
fcf_cagr = (fcf_end / fcf_start) ** (1 / years) - 1

Quality rules:

  • Dividend CAGR below EPS and FCF CAGR usually leaves room for future increases.
  • Dividend CAGR above EPS/FCF CAGR means payout ratio is expanding.
  • Flat dividend with rising FCF may imply hidden capacity or conservative management.
  • Repeated small increases can still be fragile if leverage is rising.
Step 4: Check Balance Sheet Flexibility

Look for the ability to maintain dividends during stress.

ItemWhy It Matters
Cash and short-term investmentsNear-term cushion
Net debt / EBITDADebt burden against operating earnings
Interest coverageAbility to service debt before shareholder returns
Debt maturity wallRefinancing risk in high-rate environments
Credit rating or covenant languageExternal constraints on payout policy
Show full SKILL.md (380 more words)Show less
Step 5: Separate Dividend Yield from Total Return

Dividend stocks can underperform if the yield comes from a falling price. Always connect income to valuation and growth.

python
expected_total_return = dividend_yield + expected_eps_growth + valuation_rerating

Do not present this as a guarantee. Use it as a scenario framework.

Yield-Trap Checklist

Flag a potential yield trap when several of these are true:

  • Dividend yield is more than 2x the company's 5-year median or sector median.
  • Payout ratio is above 90%, or FCF payout is above 100%.
  • Revenue, EPS, or FCF has declined for 2+ years.
  • Net debt / EBITDA is rising while interest coverage is falling.
  • Management has recently issued equity or debt while maintaining dividends.
  • The stock price fell before the yield became attractive.
  • Dividend history includes cuts, suspensions, or frequent special dividends labeled as ordinary income.
  • Sector faces structural pressure, regulation risk, or commodity down-cycle exposure.

Strategy Types

Dividend Growth

Prioritize moderate yield, strong dividend CAGR, low payout ratio, and durable business quality.

Good for users seeking compounding and lower cut risk.

High-Yield Quality

Prioritize yield, but require cash coverage, balance sheet resilience, and sector-aware payout norms.

Good for users seeking current income, but the answer must discuss cut risk.

Shareholder Yield

Combine dividends, net buybacks, and debt reduction.

Useful when companies return capital mostly through buybacks rather than cash dividends.

python
shareholder_yield = dividend_yield + net_buyback_yield + debt_paydown_yield
Dividend Capture

Buying before the ex-dividend date only to collect the dividend is not a free-money strategy. Prices usually adjust around the ex-dividend date, and taxes, spreads, and slippage can erase the gross dividend.

Use this only as an event-risk analysis, not as a default recommendation.

Data Sources

MarketUseful Fields
A-sharesTushare dividend, daily_basic.dv_ttm, fina_indicator, cashflow
US/HKyfinance Ticker.dividends, Ticker.info, financial statements, cash flow
ETFsdistribution yield, SEC yield, holdings yield, expense ratio, distribution history
REITsFFO, AFFO, occupancy, debt maturities, AFFO payout

When live data is unavailable, state the limitation and provide the analysis template instead of inventing dividend figures.

Output Template

markdown
### Dividend Analysis: [ticker/company]

**Verdict:** [sustainable / watchlist / yield-trap risk]

| Metric | Value | Interpretation |
|--------|-------|----------------|
| Dividend yield | ... | ... |
| Earnings payout | ... | ... |
| FCF payout | ... | ... |
| Dividend growth | ... | ... |
| Balance sheet | ... | ... |

**What supports the dividend**
- ...

**What could break the dividend**
- ...

**Scenario view**
- Base: ...
- Downside: ...
- Upside: ...

**Research note:** This is investment research, not live trading advice.

Common Mistakes

  • Treating high yield as cheap valuation without checking why the price fell.
  • Mixing special dividends with regular dividends.
  • Comparing REIT payout ratios to ordinary industrial companies.
  • Ignoring withholding tax, ADR ratios, currency conversion, or ETF expense drag.
  • Forgetting that ex-dividend capture is usually offset by price adjustment and transaction costs.
  • Recommending a dividend stock without discussing total return and dividend-cut risk.

© HKUDS, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in agent/src/skills/dividend-analysis of HKUDS/Vibe-Trading.

Open the folder on GitHubat commit 14cabaf

Compare with similar skills

Dividend Stock Analysis next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Dividend Stock Analysis compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Dividend Stock Analysis this skillHKUDS/Vibe-Trading35k—~2kAutomated safety check: PassMIT
AI-Trader Market IntelHKUDS/AI-Trader23k—~1.1kAutomated safety check: PassNone
Stock Deep Analysis Workflowwbh604/UZI-Skill7.1k—~9.1kAutomated safety check: NotesMIT
Zhengxi Fund Manager Views Librarylyra81604/zhengxi-views1.7k—~1.6kAutomated safety check: PassMIT
Supply Chain Bottleneck Hunterxbtlin/ai-berkshire17k—~2.6kAutomated safety check: PassMIT
Deep Company Article Seriesxbtlin/ai-berkshire17k—~2kAutomated safety check: PassMIT

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Questions about Dividend Stock Analysis

What does Dividend Stock Analysis do?

Separates durable dividends from yield traps by checking yield quality, payout coverage, balance sheet strength, dividend history and valuation, with sector-specific payout measures. Analysis never stops at the headline yield. The agent asks whether the payout is covered by earnings, operating cash flow and free cash flow, whether the balance sheet can survive a downturn, how management has treated the dividend through cycles, and whether valuation still leaves room for total return after taxes and reinvestment.

When should I use Dividend Stock Analysis?

Dividend Stock Analysis fits situations like: screening for high-yield stocks without falling into yield traps; checking whether a company's dividend is covered by free cash flow; planning an income or dividend-growth portfolio; working out ex-dividend mechanics and dividend normalization for ADRs.

How do I install Dividend Stock Analysis in Claude Code?

Run `npx skills add HKUDS/Vibe-Trading --skill dividend-analysis -a claude-code`. Or copy the skill folder (agent/src/skills/dividend-analysis in HKUDS/Vibe-Trading) into .claude/skills/dividend-analysis in your project. Claude Code loads it when a task matches its description.

How do I install Dividend Stock Analysis in Codex?

Run `npx skills add HKUDS/Vibe-Trading --skill dividend-analysis -a codex`. Or copy the skill folder (agent/src/skills/dividend-analysis in HKUDS/Vibe-Trading) into .agents/skills/dividend-analysis in your project. Codex loads it when a task matches its description.

Can I use Dividend Stock Analysis in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add HKUDS/Vibe-Trading --skill dividend-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/dividend-analysis, .gemini/skills/dividend-analysis, .github/skills/dividend-analysis and .opencode/skills/dividend-analysis in your project.

What does Dividend Stock Analysis need to run?

SKILL.md names no scripts, command-line tools or credentials: Dividend Stock Analysis is instructions for the agent only.

Does Dividend Stock Analysis access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Dividend Stock Analysis safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Dividend Stock Analysis use?

Dividend Stock Analysis is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Dividend Stock Analysis use?

About 2k tokens (SKILL.md is roughly 8.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Dividend Stock Analysis?

Skills that share tags, products or a category with Dividend Stock Analysis: AI-Trader Market Intel (HKUDS/AI-Trader, 23k stars), Stock Deep Analysis Workflow (wbh604/UZI-Skill, 7.1k stars), Zhengxi Fund Manager Views Library (lyra81604/zhengxi-views, 1.7k stars) and Supply Chain Bottleneck Hunter (xbtlin/ai-berkshire, 17k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Dividend Stock Analysis?

HKUDS (a GitHub organization) maintains it in HKUDS/Vibe-Trading, which has 34,949 GitHub stars. The repository holds 89 skills in this directory. The repository was last updated on October 8, 2026.

Source: HKUDS/Vibe-Trading on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.