Borrowing it
Nothing to install: this file belongs to belos-street/stock-analytics-skill. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/belos-street/stock-analytics-skill/main/.agents/skills/dividend-low-vol-etf/SKILL.mdgit clone --depth 1 https://github.com/belos-street/stock-analytics-skillWrote 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.
[](https://agentmods.dev/skills/belos-street/stock-analytics-skill/dividend-low-vol-etf)<a href="https://agentmods.dev/skills/belos-street/stock-analytics-skill/dividend-low-vol-etf"><img src="https://agentmods.dev/badge/skills/belos-street/stock-analytics-skill/dividend-low-vol-etf/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.
<a href="https://agentmods.dev/skills/belos-street/stock-analytics-skill/dividend-low-vol-etf"><img src="https://agentmods.dev/badge/skills/belos-street/stock-analytics-skill/dividend-low-vol-etf.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00094 | $0.06104 |
| Opus 5 | $0.00047 | $0.03052 |
| Sonnet 5 | $0.00019 | $0.01221 |
| Haiku 4.5 | $0.00009 | $0.00610 |
Grade A, and why
dividend-low-vol-etf 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.
How it starts
The opening of the file, as written. The whole thing — 375 lines — stays where its author put it; the contents beside it link to each section on GitHub.
标普中国A股大盘红利低波50指数 · 投资策略Skill
本 Skill 专用于 标普中国A股大盘红利低波50指数（SPCLLHCP / SPCLLHCT） 及其唯一对应 ETF —— 红利低波50ETF南方（515450）。
技能核心定位
核心目标
为用户提供标普中国A股大盘红利低波50指数的专业投资策略分析，帮助用户理解该指数的编制逻辑、行业特征与风险收益属性，掌握加仓减仓的时机判断，优化持仓管理。
目标用户
- 稳健型投资者：追求稳定分红和低波动的投资者
- 长期投资者：采用定投策略的长期持有者
- 资产配置者：将该ETF作为组合防御底仓的投资者
- 风险厌恶者：希望降低组合波动性的投资者
技能边界
可提供服务：
- 指数编制规则深度解读
- 估值分析：PE/PB/股息率及历史分位
- 加仓减仓时机判断
- 风险评估：波动率、回撤、行业集中度
- 持仓管理与再平衡建议
不可提供服务：
- 具体买卖指令
- 承诺收益
- 违规荐股
- 内幕信息披露
一、指数基础档案
1.1 指数身份卡
| 项目 | 内容 |
|---|---|
| 指数名称 | 标普中国A股大盘红利低波50指数 |
| 价格指数代码 | SPCLLHCP |
| 全收益指数代码 | SPCLLHCT |
| 发布日期 | 2019年4月1日 |
| 基日 | 2009年1月23日，基点1000 |
| 成分股数量 | 50只 |
| 加权方式 | 股息率加权 |
| 调仓频率 | 每半年（1月底、7月底） |
| 定制方 | 南方基金 × 标普道琼斯指数 |
| 唯一ETF | 515450 红利低波50ETF南方 |
| 基金经理 | 崔蕾（2020-01-17起管理至今） |
| ETF成立日 | 2020年1月17日 |
| ETF费率 | 管理费0.50%/年 + 托管费0.10%/年 |
1.2 编制规则（四步筛选法）
标普红利低波 50 是一只真正纯正的红利低波指数——它先用股息率筛、再用低波动筛，两个因子各司其职，不像中证红利低波那样被高股息主导。
| 步骤 | 规则 | 说明 |
|---|---|---|
| 第1步：划定样本空间 | 从标普中国A股国内大盘指数成分股中选取，剔除ST/*ST、流通市值<10亿、3个月日均成交额<2000万 | 确保大盘蓝筹、流动性充足 |
| 第2步：红利筛选 | 按近12个月股息率从高到低排序，选前100只（单行业不超过20只） | 先锁定高分红池 |
| 第3步：低波筛选 | 在上一步100只中，按过去12个月历史波动率从低到高排序，选前50只 | 再从高分红中挑最稳的 |
| 第4步：缓冲区规则 | 现存成分股若股息率排名前150 且 波动率排名前60，则优先保留 | 降低调仓冲击，保持指数稳定性 |
📎 数据来源：雪球 编制规则详解 | 同花顺 515450资产配置
1.3 权重约束
| 约束项 | 限制值 | 意义 |
|---|---|---|
| 个股权重上限 | 5% | 避免单只股票绑架指数 |
| 个股权重下限 | 0.05% | — |
| 单一行业权重上限 | 30%（GICS分类） | 防止行业过度集中 |
| 加权方式 | 股息率加权 | 分红越高、权重越大 → 天然低买高卖 |
1.4 与中证红利低波（H30269）的核心区别
这是投资者最容易搞混的地方。两者虽然都叫"红利低波"，但编制逻辑差异巨大：
| 维度 | 标普红利低波50（SPCLLHCP） | 中证红利低波（H30269） |
|---|---|---|
| 样本空间 | 标普中国A股大盘指数 | 中证全指 |
| 红利筛选周期 | 近12个月股息率 | 近3年平均股息率 |
| 分红增长要求 | 无 | ✅ 要求每股股利正增长 |
| 调仓频率 | 半年一次（1月/7月） | 一年一次（12月） |
| 行业权重上限 | ✅ 30% | ❌ 无限制 |
| 银行占比 | ~29.5% | ~50% |
| 缓冲区规则 | ✅ 有 | ❌ 无 |
| 对应ETF | 515450 | 512890 |
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.
- 12d ago First seen · 375 lines · 94 tokens per session scan A f50cad9092c5
dividend-low-vol-etf is a skill published in the GitHub repository belos-street/stock-analytics-skill (49 stars, last pushed 1mo ago), licensed MIT. It adds 94 tokens to every session and 6,104 once invoked, about $0.0005 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.
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