Agent skill · Testing & QA

longbridge-dividend-screen

High-dividend stock screen via Longbridge — analyse high-dividend-yield strategies for A-shares / HK / US, filter for sustainable payout (reasonable payout ratio, free-cash-flow coverage), stable dividend history, and evaluate long-term total return potential. Triggers: "高分红", "股息率", "红利股", "高股息", "分红稳定", "现金分红", "股息策略", "红利策略", "高分紅", "股息率", "紅利股", "高股息", "分紅穩定", "現金分紅", "high dividend", "dividend yield", "dividend stock", "income stock", "dividend strategy", "payout ratio", "free cash flow coverage", "dividend growth", "dividend stability".

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill longbridge-dividend-screen --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 6 KB
Bundled scripts: none
Version: 1.0.0
Declared author: longbridge
Path: skills/analysis/longbridge-dividend-screen/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# longbridge-dividend-screen Prompt-only analysis skill. Screens an index universe for high-dividend stocks with sustainable payouts, stable dividend history, and free-cash-flow coverage. Evaluates total return potential (price appreciation + dividend income) for income-oriented investors. > **Response language**: match the user's input language — Simplified Chinese / Traditional Chinese / English. ## When to use - *"帮我筛选高分红股票"* / *"篩選高分紅股票"* / *"screen for high-dividend stocks"* - *"A股红利股有哪些"* / *"A股紅利股"* / *"high-dividend A-shares"* - *"港股高股息标的"* / *"港股高股息標的"* / *"HK high-dividend stocks"* - *"股息率高且分红稳定的公司"* / *"股息率高且分紅穩定的公司"* / *"high yield with stable dividends"* - *"红利策略选股"* / *"紅利策略選股"* / *"dividend strategy stock picking"* ## Workflow 1. **Identify universe**: confirm market (A-share / HK / US) and index pool (CSI 300 / CSI Dividend / HSI / Hang Seng High Dividend / S&P 500 / S&P Dividend Aristocrats). 2. Fetch constituent list from the chosen index. 3. For each constituent (≤20 per batch), fetch dividend data and financial KPIs concurrently. 4. Apply dividend quality filters and score each stock. 5. Present ranked shortlist with sustainability analysis. ## CLI Run `longbrid

What's inside
Steps it walks through
  1. When to use
  2. Workflow
  3. CLI
  4. Dividend Quality Filters
  5. Output template
  6. Error handling
  7. MCP fallback
  8. Related skills
  9. File layout
Ships with 1 file
  • metadata.json
Commands it runs
Step 1: constituent list (JSON key is "stocks")
longbridge constituent <INDEX> --format json
Step 2: per constituent (run concurrently, batch ≤20)
longbridge dividend <SYMBOL> --format json             # dividend history, yield, DPS
longbridge calc-index <SYMBOL> --format json           # PE, PB, ROE, dps_rate, market cap
longbridge financial-report <SYMBOL> --kind CF --format json   # cash flow statement (FCF)
More from claude-skill-registry
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About this skill
What does the longbridge-dividend-screen skill do?

High-dividend stock screen via Longbridge — analyse high-dividend-yield strategies for A-shares / HK / US, filter for sustainable payout (reasonable payout ratio, free-cash-flow coverage), stable dividend history, and evaluate long-term total return potential. Triggers: "高分红", "股息率", "红利股", "高股息", "分红稳定", "现金分红", "股息策略", "红利策略", "高分紅", "股息率", "紅利股", "高股息", "分紅穩定", "現金分紅", "high dividend", "dividend yield", "dividend stock", "income stock", "dividend strategy", "payout ratio", "free cash flow coverage", "dividend growth", "dividend stability".

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill longbridge-dividend-screen --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going