high-dividend-strategy

high-dividend-strategy is a skill for Claude Code, Codex from Geeksfino/finskills. It costs 75 tokens per session (1,296 once invoked), scanned A, original, Apache-2.0.

A workflow for analysing high-dividend stocks in China’s A-share market, where shares are traded on mainland Chinese exchanges. It evaluates dividend income, sustainability, valuation, and longer-term total return.

In plain words
What is it for?
Use it to screen or rank dividend stocks and compare dividend yield, dividend growth, five-year total return, payout ratios, cash-flow coverage, valuation, and state-owned-enterprise reform exposure.
Why use it?
It organises several checks that investors need before relying on a dividend, including profits, cash flow, debt, earnings stability, and dividend history. This helps distinguish a high stated yield from a potentially sustainable payout.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to screen or rank dividend stocks and compare dividend yield, dividend growth, five-year total return, payout ratios, cash-flow coverage, valuation, and state-owned-enterprise reform exposure.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/geeksfino/finskills/high-dividend-strategy
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Geeksfino/finskills --skill high-dividend-strategy
Clone the repo
git clone --depth 1 https://github.com/Geeksfino/finskills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for high-dividend-strategy

README.md
[![agentmods](https://agentmods.dev/badge/skills/geeksfino/finskills/high-dividend-strategy/github.svg)](https://agentmods.dev/skills/geeksfino/finskills/high-dividend-strategy)
Your own site
<a href="https://agentmods.dev/skills/geeksfino/finskills/high-dividend-strategy"><img src="https://agentmods.dev/badge/skills/geeksfino/finskills/high-dividend-strategy/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for high-dividend-strategy

Your own site · 80×15
<a href="https://agentmods.dev/skills/geeksfino/finskills/high-dividend-strategy"><img src="https://agentmods.dev/badge/skills/geeksfino/finskills/high-dividend-strategy.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 75 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,296 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00075 $0.01296
Opus 5 $0.00037 $0.00648
Sonnet 5 $0.00015 $0.00259
Haiku 4.5 $0.00007 $0.00130

Measured 12d ago against content hash 72440ef06215, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

high-dividend-strategy scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

China-market/high-dividend-strategy/SKILL.md · 87 lines

What it actually says

高股息策略分析器

扮演以红利为核心的投资组合经理。分析A股市场高股息股票,评估分红可持续性、长期总回报及收入稳定性。

工作流程

第一步:确定参数

与用户确认:

  1. 分析范围 — 中证红利指数成分股、上证红利指数、全市场筛选、或自定义列表
  2. 回溯期 — 默认:近5年回报分析(A股分红历史较短,10年以上数据有限)
  3. 结果数量 — 默认:前10只
  4. 排名优先级 — 股息率、分红增长、可持续性、总回报、或综合评分
  5. 板块偏好 — 是否偏好国企改革受益标的

第二步:计算核心指标

对每只候选股票计算以下指标。详细计算方法参见 references/calculation-methodology.md

指标 计算方式
近5年总回报 股价涨跌 + 累计现金分红(假设分红再投资)
当前股息率 近12个月每股现金分红 / 当前股价
分红增长率 每股分红5年复合增长率
分红率(利润口径) 每股分红 / 每股收益
分红率(现金流口径) 现金分红总额 / 自由现金流
自由现金流覆盖 自由现金流 / 现金分红总额

第三步:评估分红可持续性

评估分红能否持续或增长:

维度 评估内容
利润分红率空间 分红率 < 70%(公用事业/银行可放宽至80%)
现金流覆盖 自由现金流覆盖分红 ≥ 1.3倍
资产负债率 负债水平合理,非借债分红
盈利稳定性 盈利波动小,抗周期能力强
分红历史 连续分红年数,分红政策明确性
国企改革催化 国资委分红率提升要求的受益程度

详细评分标准参见 references/calculation-methodology.md

第四步:排名

按综合评分排名:

因素 权重(综合) 权重(收入型) 权重(成长型)
总回报(5年) 25% 15% 30%
当前股息率 20% 30% 10%
分红增长率 20% 15% 30%
可持续性评分 25% 30% 20%
估值水平(PE/PB) 10% 10% 10%

第五步:呈现结果

以结构化报告呈现,格式参见 references/output-template.md

  1. 摘要 — A股红利市场概况、利率环境、主要发现
  2. 方法论 — 分析范围、时间段、再投资假设、排名权重
  3. 个股分析 — 每只股票完整分析
  4. 对比表 — 横向对比所有指标
  5. 收入测算 — 假设10万元投资的未来分红收入预测
  6. 风险提示

数据增强

如需实时市场数据支撑分析,请使用金融数据工具包技能(findata-toolkit-cn)。该工具包提供A股实时行情、财务指标、董监高增减持、北向资金、宏观数据等功能,所有数据源免费,无需API密钥。

重要注意事项

  • A股分红特点:多数公司每年仅分红一次(年报后),少数半年分红。与美股季度分红习惯不同。
  • 送股/转增 ≠ 现金分红:送红股和资本公积转增股本不产生现金收入,仅增加股数。本分析仅关注现金分红。
  • 持有期税率:A股个人投资者分红税率与持有期挂钩 — 持有超1年免税、1个月至1年税率10%、不足1个月税率20%。长期持有策略可显著提升税后收益。
  • 国企分红改革:国资委近年持续推动央企/国企提升分红比例至30%以上,这是结构性利好红利策略的政策催化。
  • 高股息陷阱:股息率高可能是因股价大幅下跌导致,而非分红丰厚。务必配合可持续性分析。
  • 利率环境:低利率环境(存款利率低、理财收益率低)是高股息策略的宏观利好,但利率上行时红利股可能跑输。
  • 行业集中度:A股高股息标的集中在银行、煤炭、公用事业、石化等行业,需警惕集中度风险。
Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 87 lines · 75 tokens per session scan A 72440ef06215

Subscribe to this mod's changes

high-dividend-strategy is a skill published in the GitHub repository Geeksfino/finskills (279 stars, last pushed 6mo ago), licensed Apache-2.0. It adds 75 tokens to every session and 1,296 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

sector-rotation

An analysis framework for comparing industries in the Chinese A-share stock market, using business conditions, price momentum, valuation, and money flows. It produces rankings and higher- or lower-allocation suggestions.

HKUDS/Vibe-Trading · 39 tokens

strategy-pivot-designer

Detect backtest iteration stagnation and generate structurally different strategy pivot proposals when parameter tuning reaches a local optimum.

tradermonty/claude-trading-skills · 28 tokens

twitter-reader

Read Twitter/X for financial research using opencli (read-only). Use this skill whenever the user wants to read their Twitter feed, search for financial tweets, view bookmarks, look up user profiles, or gather market sentiment from Twitter/X. Triggers include: "check my feed", "search Twitter for", "show my…

himself65/finance-skills · 161 tokens

chenhao-limit-up

A framework for judging Chinese A-share stocks that have reached the daily price-rise limit, using market mood, sector leadership, and trading momentum.

questflowai/investorskills · 44 tokens

trading-risk-gate

Unified pre-trade safety gate: Ruin check (Law #1), ergodicity audit, and win-rate dominance validation. Absorbs: ergodicity-check, law-of-ruin, win-rate-dominance.

winstonkoh87/Athena-Public · 53 tokens

furusato

A Japanese hometown-tax donation manager for furusato nozei, a system where donations to municipalities can qualify for an income-tax or local-tax deduction. It reads donation receipts, stores donation records, and calculates deduction limits.

kazukinagata/shinkoku · 102 tokens