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 financing-cost-analysisgit 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/financing-cost-analysis)<a href="https://agentmods.dev/skills/vivy-yi/finance-skills/financing-cost-analysis"><img src="https://agentmods.dev/badge/skills/vivy-yi/finance-skills/financing-cost-analysis/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/financing-cost-analysis"><img src="https://agentmods.dev/badge/skills/vivy-yi/finance-skills/financing-cost-analysis.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 | $0.00091 | $0.02211 |
| Opus 5 | $0.00046 | $0.01105 |
| Sonnet 5 | $0.00018 | $0.00442 |
| Haiku 4.5 | $0.00009 | $0.00221 |
Grade A, and why
financing-cost-analysis 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 — 265 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(融资渠道/审批权限/成本上限)。
/financing-cost-analysis — 融资成本分析
Examples
→ 示例:用户说"帮我们算一下目前各类融资工具的实际成本",系统应调用本技能,计算加权融资成本。
→ 示例:用户说"银行贷款要展期,帮我评估一下续借成本和条件变化",系统应调用本技能,评估贷款展期的成本影响。
→ 示例:用户说"发行绿色债券比普通债券便宜多少,帮我量化一下",系统应调用本技能,计算绿色债券融资成本节约。
第一步:获取融资数据
从 [CASH]/[ERP] 获取融资数据:
□ 融资总额:[XXX万]
□ 融资成本:平均 [X]%
□ 授信总额:[XXX万]
□ 已使用授信:[XXX万]
□ 获取字段:
融资类型 | 银行 | 金额 | 利率 | 到期日 | 担保方式
第二步:融资余额结构分析
融资类型分布:
□ 银行借款:[XXX万]([X%])
- 短期借款:[XXX万]([X%])
- 长期借款:[XXX万]([X%])
□ 债券:[XXX万]([X%])
□ 融资租赁:[XXX万]([X%])
□ 其他:[XXX万]([X%])
□ 融资总额:[XXX万]
□ 融资成本:平均 [X]%(目标 < [X]%)
各银行融资分布:
□ [银行A]:[XXX万]([X%]),利率 [X]%
□ [银行B]:[XXX万]([X%]),利率 [X]%
□ [银行C]:[XXX万]([X%]),利率 [X]%
第三步:融资成本分析
融资成本明细:
□ 银行借款利息:[XXX万]/年
□ 债券利息:[XXX万]/年
□ 融资租赁利息:[XXX万]/年
□ 其他融资费用:[XXX万]/年
□ 年度融资总成本:[XXX万]
□ 综合融资成本(IRR):[X]%
□ vs 目标上限 [X]%:[达标/超标]
成本差异分析:
□ 高成本融资:[XXX万](利率 > [X]%)
- [融资A]:[XXX万],利率 [X]%,高于平均 [+X]%
- [融资B]:[XXX万],利率 [X]%,高于平均 [+X]%
□ 低成本融资:[XXX万](利率 < [X]%)
- [融资C]:[XXX万],利率 [X]%,低于平均 [-X]%
成本超标原因分析:
□ 自身资质问题:
→ 信用评级下降
→ 资产负债率过高
→ 现金流紧张
□ 市场环境问题:
→ 银行整体收紧信贷
→ 行业风险高(银行不愿贷)
→ 货币政策收紧
□ 融资结构问题:
→ 短期贷款占比过高(滚动再融资风险)
→ 缺少长期低成本资金
第四步:授信使用分析
授信额度使用:
□ 授信总额:[XXX万]
□ 已使用:[XXX万]([X%])
□ 可用:[XXX万]([X%])
□ [银行A] 授信:[XXX万],已用 [XXX万]([X%]),可用 [XXX万]
□ [银行B] 授信:[XXX万],已用 [XXX万]([X%]),可用 [XXX万]
□ [银行C] 授信:[XXX万],已用 [XXX万]([X%]),可用 [XXX万]
授信健康度:
□ 授信使用率:[X%](目标 < [X]%)
□ 单一银行依赖度:[X%](最高 [银行A])
□ 授信到期分布:均匀/集中
□ 授信健康度评估:[✅ 健康 / ⚠️ 偏紧 / 🔴 紧张]
第五步:到期结构分析
未来 [X] 个月到期分布:
月份 | 到期金额 | 授信状态 | 再融资难度
-----|----------|----------|----------
[月1] | [XXX万] | [正常/紧张] | [低/中/高]
[月2] | [XXX万] | [正常/紧张] | [低/中/高]
[月3] | [XXX万] | [正常/紧张] | [低/中/高]
[X月] | [XXX万] | [正常/紧张] | [低/中/高]
集中到期风险:
□ 最大单月到期:[XXX万]([月X])
□ 是否超过可用授信?[是/否]
□ 是否有再融资预案?[有/无]
□ 集中到期风险:[✅ 可控 / ⚠️ 需关注 / 🔴 高风险]
第六步:生成融资成本分析报告
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 · 265 lines · 91 tokens per session scan A e1064bf3fd16
financing-cost-analysis is a skill published in the GitHub repository vivy-yi/finance-skills (29 stars, last pushed 3mo ago), licensed MIT. It adds 91 tokens to every session and 2,211 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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