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 vivy-yi/finance-skills --skill fx-exposure-calculationgit clone --depth 1 https://github.com/vivy-yi/finance-skillsWrote 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/vivy-yi/finance-skills/fx-exposure-calculation)<a href="https://agentmods.dev/skills/vivy-yi/finance-skills/fx-exposure-calculation"><img src="https://agentmods.dev/badge/skills/vivy-yi/finance-skills/fx-exposure-calculation/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/vivy-yi/finance-skills/fx-exposure-calculation"><img src="https://agentmods.dev/badge/skills/vivy-yi/finance-skills/fx-exposure-calculation.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 | $0.00109 | $0.02332 |
| Opus 5 | $0.00055 | $0.01166 |
| Sonnet 5 | $0.00022 | $0.00466 |
| Haiku 4.5 | $0.00011 | $0.00233 |
Grade A, and why
fx-exposure-calculation 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 9d 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 — 235 lines — stays where its author put it; the contents beside it link to each section on GitHub.
加载上下文
首次使用时: 读取 ../../CLAUDE.md 获取场景级配置(主要外币币种/历史敞口数据/报告格式)。
/fx-exposure-calculation — 外汇敞口计算
Examples
→ 示例:用户说"帮我算一下本季度末我们的人民币外汇敞口是多少",系统应调用本技能,计算人民币外汇净敞口。
→ 示例:用户说"欧元和美元的敞口要分开算,每种货币的影响因素不一样",系统应调用本技能,执行分币种外汇敞口计算。
→ 示例:用户说"并购了境外子公司后,合并报表的外汇敞口怎么算",系统应调用本技能,计算境外子公司合并层面的外汇敞口。
第一步:敞口识别
交易敞口(Transaction Exposure):
□ 已确认外币交易:
→ 出口销售:[X] 万 USD — 收款日期 [YYYY-MM-DD]
→ 进口采购:[X] 万 EUR — 付款日期 [YYYY-MM-DD]
→ 外汇贷款本息:[X] 万 USD — 到期日 [YYYY-MM-DD]
□ 预期外币现金流([X] 个月内):
→ 预期 USD 收入:[X] 万
→ 预期 USD 支出:[X] 万
→ 预期 EUR 收入:[X] 万
→ 预期 EUR 支出:[X] 万
□ 净交易敞口:
→ USD 净敞口:[X] 万([多头/空头])
→ EUR 净敞口:[X] 万([多头/空头])
→ GBP 净敞口:[X] 万([多头/空头])
会计敞口(Translation Exposure):
□ 海外子公司:
→ 美国子公司:净资产 [X] 万 USD
→ 欧洲子公司:净资产 [X] 万 EUR
→ 东南亚子公司:净资产 [X] 万 SGD
□ 会计敞口汇总:
→ USD 净资产:[X] 万(折算汇率 [X.XXXX])
→ EUR 净资产:[X] 万(折算汇率 [X.XXXX])
□ 汇率敏感性(USD/CNY 变动 1%):
→ 会计折算影响:[+/-X] 万人民币
经济敞口(Economic Exposure):
□ 收入币种结构:
→ 人民币收入:[X]%([X] 万)
→ USD 收入:[X]%([X] 万)
→ EUR 收入:[X]%([X] 万)
→ 其他:[X]%([X] 万)
□ 成本币种结构:
→ 人民币成本:[X]%([X] 万)
→ USD 采购:[X]%([X] 万)
→ EUR 采购:[X]%([X] 万)
□ 经济敞口分析:
→ 人民币贬值 10% 对 EBIT 影响:[+/-X] 万
→ USD 升值 10% 对毛利率影响:[+/-X] 个百分点
第二步:敞口量化
净敞口汇总表:
□ 按币种净敞口:
| 币种 | 交易敞口 | 会计敞口 | 经济敞口 | 合计 | 方向 |
|------|---------|---------|---------|------|------|
| USD | [X]万 | [X]万 | [X]万 | [X]万 | 多头 |
| EUR | [X]万 | [X]万 | — | [X]万 | 空头 |
| GBP | [X]万 | — | — | [X]万 | 中性 |
敞口集中度分析:
□ 单一货币集中度:
→ USD 敞口占总外币敞口:[X]%
→ 风险评级:[高/中/低](> [X]% 为高)
□ 敞口方向分布:
→ 多头敞口:[X]%(看升值)
→ 空头敞口:[X]%(看贬值)
→ 中性:[X]%
第三步:敏感性分析
汇率敏感性矩阵:
□ USD/CNY 敏感性:
| 汇率变动 | 交易影响(万) | 会计影响(万) | 合计(万) |
|---------|-------------|-------------|---------|
| +10% | [X] | [X] | [X] |
| +5% | [X] | [X] | [X] |
| -5% | [-X] | [-X] | [-X] |
| -10% | [-X] | [-X] | [-X] |
□ EUR/CNY 敏感性:
| 汇率变动 | 交易影响(万) | 会计影响(万) | 合计(万) |
|---------|-------------|-------------|---------|
| +10% | [X] | [X] | [X] |
| +5% | [X] | [X] | [X] |
| -5% | [-X] | [-X] | [-X] |
| -10% | [-X] | [-X] | [-X] |
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.
- 9d ago First seen · 235 lines · 109 tokens per session scan A c0dfe6c922a8
fx-exposure-calculation is a skill published in the GitHub repository vivy-yi/finance-skills (29 stars, last pushed 3mo ago), licensed MIT. It adds 109 tokens to every session and 2,332 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 2026-09-03.
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