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 cash-flow-forecastinggit 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/cash-flow-forecasting)<a href="https://agentmods.dev/skills/vivy-yi/finance-skills/cash-flow-forecasting"><img src="https://agentmods.dev/badge/skills/vivy-yi/finance-skills/cash-flow-forecasting/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/cash-flow-forecasting"><img src="https://agentmods.dev/badge/skills/vivy-yi/finance-skills/cash-flow-forecasting.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 | $0.00117 | $0.02670 |
| Opus 5 | $0.00059 | $0.01335 |
| Sonnet 5 | $0.00023 | $0.00534 |
| Haiku 4.5 | $0.00012 | $0.00267 |
Grade A, and why
cash-flow-forecasting 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 11d 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.
This is a copy
89% identical to kim-orchestrator — 321 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 287 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（资金计划周期/融资配置/银行授信）。
/cash-flow-forecasting — 现金流预测
Examples
→ 示例：用户说"帮我预测一下未来 3 个月的现金流，看有没有资金缺口"，系统应调用本技能，执行 3 个月现金流预测。
→ 示例：用户说"下个月有大笔债务到期，帮我看看账户里的钱够不够还"，系统应调用本技能，评估到期债务的资金覆盖能力。
→ 示例：用户说"供应商说我们付款越来越慢，帮我们预测一下改善现金流的时间点"，系统应调用本技能，结合付款政策变化预测现金流改善。
预测方法说明
滚动预测：每月更新，滚动预测未来 3 个月
情景分析：乐观/基准/悲观三情景
数据来源：历史数据 + 当月实际 + 下月计划 + 已知大额进出
第一步：收集基础数据
从 [ERP] 获取历史数据（过去 3 个月）：
□ 月均收入：[XXX万]
□ 月均支出：[XXX万]
□ 月均净流量：[XXX万]
□ 收入波动性：[X%]（标准差/均值）
□ 支出波动性：[X%]
从 [ERP]/[OA] 获取已知大额进出：
□ 已确定大额支出（未来 3 个月）：
- 银行贷款到期：[XXX万] — [月份]
- 供应商大额付款：[XXX万] — [月份]
- 税款缴纳：[XXX万] — [月份]
□ 已确定大额收入（未来 3 个月）：
- 大客户回款：[XXX万] — [月份]
- 融资到账：[XXX万] — [月份]
- 其他确定收入：[XXX万] — [月份]
从 [BK] 获取预算数据：
□ 下月预算支出：[XXX万]
□ 下月预算收入：[XXX万]
□ 下月预算净流量：[XXX万]
第二步：构建预测模型
基准情景（最可能发生）：
| 月份 | 期初余额 | 预期流入 | 预期流出 | 净流量 | 期末余额 | |------|-------|---------|---------|--------|--------|---------| | 月1 | [XXX万] | [XXX万] | [XXX万] | [XXX万] | [XXX万] | | 月2 | [接上月] | [XXX万] | [XXX万] | [XXX万] | [XXX万] | | 月3 | [接上月] | [XXX万] | [XXX万] | [XXX万] | [XXX万] |
乐观情景（收入高于预期/支出低于预期）：
| 月份 | 期初余额 | 乐观流入 | 乐观流出 | 净流量 | 期末余额 | |------|-------|---------|---------|--------|--------|---------| | 月1 | [XXX万] | [XXX万] | [XXX万] | [XXX万] | [XXX万] | | 月2 | [接上月] | [XXX万] | [XXX万] | [XXX万] | [XXX万] | | 月3 | [接上月] | [XXX万] | [XXX万] | [XXX万] | [XXX万] |
悲观情景（收入低于预期/支出高于预期）：
| 月份 | 期初余额 | 悲观流入 | 悲观流出 | 净流量 | 期末余额 | |------|-------|---------|---------|--------|--------|---------| | 月1 | [XXX万] | [XXX万] | [XXX万] | [XXX万] | [XXX万] | | 月2 | [接上月] | [XXX万] | [XXX万] | [XXX万] | [XXX万] | | 月3 | [接上月] | [XXX万] | [XXX万] | [XXX万] | [XXX万] |
第三步：识别资金缺口
缺口时间点分析：
□ 基准情景：
第一个缺口月份：[月份]
缺口金额：[XXX万]
持续时间：[X] 个月
累计最大缺口：[XXX万]
□ 悲观情景：
第一个缺口月份：[月份]
缺口金额：[XXX万]
持续时间：[X] 个月
累计最大缺口：[XXX万]
□ 乐观情景：
是否出现缺口：[是/否]
→ 如有，描述：[...]
缺口原因分析：
□ 季节性因素：
- [描述，如：春节前付款集中]
□ 大额固定支出：
- 银行贷款到期：[月份] — [XXX万]
- 税款缴纳：[月份] — [XXX万]
- [其他大额支出]
□ 收入延迟风险：
- 大客户回款可能延迟：[客户名称]
- 可能延迟金额：[XXX万]
- 延迟概率：[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.
- 11d ago First seen · 287 lines · 117 tokens per session scan A 046a59e74cfe
cash-flow-forecasting is a skill published in the GitHub repository vivy-yi/finance-skills (28 stars, last pushed 2mo ago), licensed MIT. It adds 117 tokens to every session and 2,670 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. It is 89% identical to kim-orchestrator, differing in 321 lines, and is treated as a copy.
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