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 liquidity-assessmentgit 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/liquidity-assessment)<a href="https://agentmods.dev/skills/vivy-yi/finance-skills/liquidity-assessment"><img src="https://agentmods.dev/badge/skills/vivy-yi/finance-skills/liquidity-assessment/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/liquidity-assessment"><img src="https://agentmods.dev/badge/skills/vivy-yi/finance-skills/liquidity-assessment.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 | $0.00102 | $0.02441 |
| Opus 5 | $0.00051 | $0.01221 |
| Sonnet 5 | $0.00020 | $0.00488 |
| Haiku 4.5 | $0.00010 | $0.00244 |
Grade A, and why
liquidity-assessment 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 — 314 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(流动性要求/预警值/升级矩阵)。
/liquidity-assessment — 流动性评估
Examples
→ 示例:用户说"帮我评估一下公司目前的流动性状况,看有没有风险",系统应调用本技能,执行流动性风险评估。
→ 示例:用户说"如果有银行抽贷,我们能撑多久",系统应调用本技能,执行压力场景下的流动性存续期分析。
→ 示例:用户说"帮我们算一下现金转换周期,看看资金效率如何",系统应调用本技能,计算现金转换周期指标。
第一步:获取流动性数据
从 [CASH]/[ERP] 获取流动性数据:
□ 现金及等价物:[XXX万]
□ 流动资产:[XXX万]
□ 流动负债:[XXX万]
□ 每月刚性支出:[XXX万]
□ 获取字段:
现金 | 流动资产 | 流动负债 | 银行授信 | 每月支出
第二步:计算流动性指标
核心流动性指标:
□ 现金及等价物:[XXX万]
□ 可快速变现资产:[XXX万](现金 + 应收账款 + 理财)
□ 每月刚性支出:[XXX万](工资 + 社保 + 利息 + 到期本金)
□ 可用月数 = 现金 / 每月刚性支出 = [X] 个月
□ 流动资产:[XXX万]
□ 流动负债:[XXX万]
□ 流动比率 = 流动资产 / 流动负债 = [X]
□ 速动资产 = 流动资产 - 存货 = [XXX万]
□ 速动比率 = 速动资产 / 流动负债 = [X]
流动性指标判断:
□ 可用月数:[X] 个月
- 安全值:> [X] 个月
- 预警值:[X]-[X] 个月
- 危险值:< [X] 个月
□ 流动比率:[X]
- 安全值:> [X]
- 预警值:[X]-[X]
- 危险值:< [X]
□ 速动比率:[X]
- 安全值:> [X]
- 预警值:[X]-[X]
- 危险值:< [X]
第三步:评估授信可用性
银行授信情况:
□ 授信总额:[XXX万]
□ 已使用授信:[XXX万]([X%])
□ 可用授信:[XXX万]([X%])
□ 是否有未使用的银行授信?[有/无]
□ 授信是否有多家银行?[是/否(单一银行依赖)]
□ 授信是否即将到期?[是/否]
授信健康度:
□ 授信使用率:[X%](目标 < [X]%)
□ 授信到期日:[YYYY-MM-DD]
□ 续授信难度:[低/中/高]
第四步:评估到期债务
未来 [X] 个月到期债务:
月份 | 到期本金 | 到期利息 | 合计 | 可用授信 | 缺口
-----|----------|----------|------|----------|------
[月1] | [XXX万] | [XXX万] | [XXX万] | [XXX万] | [XXX万]
[月2] | [XXX万] | [XXX万] | [XXX万] | [XXX万] | [XXX万]
[月3] | [XXX万] | [XXX万] | [XXX万] | [XXX万] | [XXX万]
到期风险:
□ 最大单月到期:[XXX万]([月X])
□ 可用授信能否覆盖到期?[能/否]
□ 是否存在再融资压力?[是/否]
□ 到期风险:[✅ 可控 / ⚠️ 偏紧 / 🔴 高风险]
第五步:评估风险等级
流动性风险等级:
风险等级:[低/中/高/极高]
低风险(正常):
□ 可用月数 > [X] 个月
□ 流动比率 > [X]
□ 授信使用率 < [X]%
□ 到期债务可由授信覆盖
→ 无需特殊应对,保持监控
中风险(关注):
□ 可用月数 [X]-[X] 个月
□ 流动比率 [X]-[X]
□ 授信使用率 [X]-[X]%
□ 到期债务基本可覆盖
→ 加强监控,提前准备应对方案
高风险(预警):
□ 可用月数 < [X] 个月
□ 流动比率 < [X]
□ 授信使用率 > [X]%
□ 到期债务存在缺口
→ 立即启动应对方案,减少非必要支出
极高风险(危机):
□ 可用月数 < [X] 个月
□ 现金即将耗尽
□ 授信即将用尽
□ 即将技术性违约
→ 立即启动危机应对,引入外部资源
第六步:制定应对方案
中风险应对方案:
□ 加强应收账款催收
→ 目标:回款 [XXX万]
→ 时间:[X] 周
→ 责任人:[X]
□ 提前与银行沟通续授信
→ 沟通时间:[YYYY-MM-DD]
→ 预期结果:[描述]
→ 责任人:[X]
□ 减少非必要支出
→ 预算冻结范围:[描述]
→ 节约金额:[XXX万]/月
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 · 314 lines · 102 tokens per session scan A b94ac9708ae8
liquidity-assessment is a skill published in the GitHub repository vivy-yi/finance-skills (29 stars, last pushed 3mo ago), licensed MIT. It adds 102 tokens to every session and 2,441 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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