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 yuping322/financial-services-plugins-new --skill model-updategit clone --depth 1 https://github.com/yuping322/financial-services-plugins-newWrote 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/yuping322/financial-services-plugins-new/model-update)<a href="https://agentmods.dev/skills/yuping322/financial-services-plugins-new/model-update"><img src="https://agentmods.dev/badge/skills/yuping322/financial-services-plugins-new/model-update.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.00932 |
| Opus 5 | $0.00000 | $0.00466 |
| Sonnet 5 | $0.00000 | $0.00186 |
| Haiku 4.5 | $0.00000 | $0.00093 |
Grade A, and why
model-update 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 8d 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.
What it actually says
模型更新
描述：使用新数据更新财务模型 — 季度盈利、管理指导、宏观变化或修订假设。调整估计、重新计算估值并标记重大变化。盈利后、指导更新后或需要刷新假设时使用。触发条件："更新模型"、"插入盈利"、"刷新估计"、"[公司]的更新数字"、"新指导"或"修订估计"。
工作流程
第 1 步：识别发生的变化
确定更新触发因素：
- 盈利发布：新季度实际数据要插入
- 指导变化：公司更新了前向展望
- 估计修订：分析师根据新数据更改假设
- 宏观更新：利率、外汇、商品价格变化
- 事件驱动：M&A、重组、新产品、管理层变化
第 2 步：插入新数据
盈利后
使用报告的实际数据更新模型：
| 行项目 | 先前估计 | 实际 | 差异 | 备注 |
|---|---|---|---|---|
| 收入 | ||||
| 毛利率 | ||||
| 运营费用 | ||||
| EBITDA | ||||
| 每股收益 | ||||
| [关键指标 1] | ||||
| [关键指标 2] |
细分详情（如适用）：
- 更新每个细分的收入和利润率
- 注明任何细分混合变化
资产负债表/现金流更新：
- 现金和债务余额
- 股份数（回购、稀释）
- 资本支出实际vs估计
- 营运资本变化
第 3 步：修订前向估计
根据新数据调整前向估计：
| 旧财年估计 | 新财年估计 | 变化 | 旧次财年 | 新次财年 | 变化 | |
|---|---|---|---|---|---|---|
| 收入 | ||||||
| EBITDA | ||||||
| 每股收益 |
关键假设变化：
- 您改变了哪些假设及其原因？
- 收入增长率：旧 → 新（原因）
- 利润率假设：旧 → 新（原因）
- 任何新项目（重组费用、一次性收益等）
第 4 步：估值影响
使用更新的估计重新计算估值：
| 估值方法 | 先前 | 更新 | 变化 |
|---|---|---|---|
| DCF 公允价值 | |||
| P/E (NTM 每股收益 × 目标倍数) | |||
| EV/EBITDA (NTM EBITDA × 目标倍数) | |||
| 目标价格 |
第 5 步：总结和行动
估计变化总结：
- 一段：发生了什么变化、为什么以及对股票意味着什么
- 这是改变论文的事件还是噪音？
评级/目标价格：
- 维持或改变评级？
- 新目标价格（如改变）及方法
- 相对于当前价格的上升/下降空间
第 6 步：输出
- 更新的 Excel 模型（如用户提供现有模型）
- 估计变化摘要（Markdown 或 Word）
- 更新的目标价格推导
重要说明
- 始终将估计与公司报告的数字对账，然后再向前预测
- 注明您的估计是 GAAP 还是调整后的，以及任何非经常性项目
- 跟踪估计修订历史 — 这显示了您的分析进展
- 如果季度有噪音，在估计变化中将信号与噪音分离
- 更新后检查一致预期 — 您修订的估计与华尔街相比如何？
- 股份数很重要 — 股票补偿、转换或回购的稀释会显著影响每股收益
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.
- 8d ago First seen · 93 lines · 0 tokens per session scan A fc388bbf532c
model-update is a skill published in the GitHub repository yuping322/financial-services-plugins-new (17 stars, last pushed 6mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 932 tokens. 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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