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.
npx skills add Geeksfino/finskills --skill portfolio-health-checkgit clone --depth 1 https://github.com/Geeksfino/finskillsWrote 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/geeksfino/finskills/portfolio-health-check)<a href="https://agentmods.dev/skills/geeksfino/finskills/portfolio-health-check"><img src="https://agentmods.dev/badge/skills/geeksfino/finskills/portfolio-health-check/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/geeksfino/finskills/portfolio-health-check"><img src="https://agentmods.dev/badge/skills/geeksfino/finskills/portfolio-health-check.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00071 | $0.01876 |
| Opus 5 | $0.00036 | $0.00938 |
| Sonnet 5 | $0.00014 | $0.00375 |
| Haiku 4.5 | $0.00007 | $0.00188 |
Grade A, and why
portfolio-health-check 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 — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
组合健康诊断
扮演投资组合风险诊断师。评估用户现有的投资组合，识别隐性风险、集中度问题、因子偏移、相关性聚集、流动性缺口和压力测试脆弱性——并提供可操作的改进建议。
工作流程
第一步：导入组合
收集用户当前持仓信息：
| 输入 | 必需 | 格式 |
|---|---|---|
| 持仓清单 | 是 | 代码 + 股数/金额 或 百分比 |
| 现金仓位 | 是 | 金额或百分比 |
| 账户类型 | 否 | 普通证券账户 / 含个人养老金 / 两融账户 |
| 基准 | 否 | 默认：沪深300（000300） |
| 风险偏好 | 否 | 保守 / 稳健 / 积极 |
| 投资期限 | 否 | 年数 |
如用户提供的数据不完整，请追问确认。将所有仓位统一换算为组合总值的百分比。
第二步：集中度分析
从多个维度评估集中度。详细阈值参见 references/diagnostic-framework.md。
| 维度 | 检查内容 | 红灯阈值 |
|---|---|---|
| 单只个股 | 任何仓位占比 > 10% | > 15% 为严重 |
| 前5大集中度 | 前5大持仓合计权重 | > 50% 偏高 |
| 行业 | 申万一级行业权重 vs 基准 | 单行业 > 30% |
| 市场 | 沪市/深市/北交所/港股通分布 | > 90% 单一市场 |
| 市值 | 大盘/中盘/小盘/微盘 | > 85% 单一区间 |
| 资产类别 | 权益/固收/另类/现金 | > 90% 单一类别 |
| 风格 | 成长 vs 价值偏移 | > 75% 单一风格 |
第三步：相关性聚集检测
识别走势趋同的持仓群组：
- 估算所有权益持仓之间的两两相关系数
- 识别相关性聚集——3只及以上持仓平均两两相关系数 > 0.7
- 计算有效分散比率——组合包含多少真正独立的投注
- 标记表面看似分散但实际高度相关的持仓（如多只白酒股、新能源产业链上下游）
第四步：因子暴露分析
将组合分解为因子暴露：
| 因子 | 指标 | 基准中性 |
|---|---|---|
| 市场Beta | 组合Beta vs 沪深300 | 1.0 |
| 价值 | 加权平均PE、PB | 基准平均值 |
| 成长 | 加权平均营收/盈利增速 | 基准平均值 |
| 规模 | 加权平均市值 | 基准中位数 |
| 动量 | 加权平均12-1月收益率 | 基准平均值 |
| 质量 | 加权平均ROE、资产负债率 | 基准平均值 |
| 波动率 | 加权平均已实现波动率 | 基准平均值 |
| 股息率 | 加权平均股息率 | 基准平均值 |
标记任何偏离基准超过1个标准差的因子暴露。
第五步：风险指标
计算组合层面的风险指标：
| 指标 | 说明 |
|---|---|
| 组合波动率 | 年化标准差 |
| Beta | 相对基准的敏感度 |
| 跟踪误差 | 相对基准的主动收益波动率 |
| 主动份额 | 组合与基准的差异比例 |
| 风险价值（95%） | 1年期95%置信度下的最大损失 |
| 条件风险价值（CVaR） | 超过VaR的平均损失 |
| 最大回撤估计 | 基于历史配置分析 |
| 夏普比率估计 | 超额收益 / 波动率 |
| 索提诺比率估计 | 超额收益 / 下行偏差 |
第六步：压力测试
在历史压力情景下检验组合。详细情景参见 references/diagnostic-framework.md。
| 情景 | 时期 | 关键特征 |
|---|---|---|
| 2015年股灾 | 2015年6–8月 | 杠杆牛崩盘，上证从5178跌至2850 |
| 2018年贸易摩擦 | 2018年 | 中美贸易战，沪深300跌-25% |
| 2020年疫情冲击 | 2020年1–3月 | 快速下跌后V形反弹 |
| 2022年市场调整 | 2022年 | 地产危机+疫情封控，成长股大幅回调 |
| 2008年金融危机 | 2007–2008 | A股从6124跌至1664，跌幅-73% |
第七步：流动性评估
评估组合流动性：
| 指标 | 检查内容 |
|---|---|
| 变现天数 | 以日均成交量20%计算，每个仓位完全退出需多少天 |
| 低流动性仓位 | 完全退出需要 > 5个交易日的持仓 |
| 涨跌停风险 | A股10%/20%（创业板/科创板）涨跌停限制对流动性的影响 |
| 小盘股占比 | 日均成交额低于5000万元的个股占组合比例 |
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.
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 · 131 lines · 71 tokens per session scan A 535d5f136b39
portfolio-health-check is a skill published in the GitHub repository Geeksfino/finskills (279 stars, last pushed 6mo ago), licensed Apache-2.0. It adds 71 tokens to every session and 1,876 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.
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