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 claude-office-skills/claude-office-plugin --skill equity-valuationgit clone --depth 1 https://github.com/claude-office-skills/claude-office-pluginWrote 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/claude-office-skills/claude-office-plugin/equity-valuation)<a href="https://agentmods.dev/skills/claude-office-skills/claude-office-plugin/equity-valuation"><img src="https://agentmods.dev/badge/skills/claude-office-skills/claude-office-plugin/equity-valuation/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/claude-office-skills/claude-office-plugin/equity-valuation"><img src="https://agentmods.dev/badge/skills/claude-office-skills/claude-office-plugin/equity-valuation.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 | $0.00044 | $0.02596 |
| Opus 5 | $0.00022 | $0.01298 |
| Sonnet 5 | $0.00009 | $0.00519 |
| Haiku 4.5 | $0.00004 | $0.00260 |
Grade A, and why
equity-valuation 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.
How it starts
The opening of the file, as written. The whole thing — 206 lines — stays where its author put it; the contents beside it link to each section on GitHub.
股票估值报告引擎(决策级完整工作簿)
当用户要求"给这只股票估值"/"值不值得买"/"对比 A 和 B"/"写投资备忘录"时,你生成的是包含完整估值逻辑链的多 Sheet Excel 工作簿 — 从数据验证到最终投资结论,每步可审计、可调参。
本 Skill 与 financial-modeling 配合使用:financial-modeling 负责 DCF/P&L 的具体公式实现,本 Skill 负责估值决策框架和报告结构。
工作簿结构(7 个 Sheet)
| # | Sheet 名称 | 核心内容 |
|---|---|---|
| 1 | 数据总览 | 数据源/日期/质量评分/置信度等级 |
| 2 | 核心假设 | Bull/Base/Bear 三情景参数面板 |
| 3 | 相对估值 | P/E / P/B / EV/EBITDA 同行对比表 |
| 4 | DCF 模型 | FCF预测 + 折现 + 终端价值(调用 financial-modeling 规范) |
| 5 | 质量评估 | 6维企业质量打分矩阵 |
| 6 | 风险矩阵 | 风险事件 × 概率 × 影响 × 监控触发器 |
| 7 | 估值结论 | 三角验证 + 安全边际 + 投资结论仪表盘 |
Sheet 1:数据总览与质量门控
这是模型的"入口检查"——先验证数据质量再做估值:
// 数据质量评分(公式驱动)
// 完整性得分 = 已填字段数 / 总必填字段数
ws.Range("C8").Formula = "=COUNTA(C12:C25)/14";
ws.Range("C8").NumberFormat = "0%";
// 时效性标记
ws.Range("C9").Value2 = "2024-12-31"; // 最新财报期(蓝色可编辑)
ws.Range("D9").Formula = '=IF(TODAY()-DATEVALUE(C9)>180,"⚠ 超过6个月","✓ 近期")';
// 置信度等级(自动判断)
ws.Range("C10").Formula = '=IF(C8>=0.85,"High",IF(C8>=0.6,"Medium","Low"))';
// High = 可做完整估值三角验证
// Medium = 可估值但需加宽区间
// Low = 仅定性方向判断,跳过精确 DCF
// 必填数据清单(缺失项红色标记)
var fields = ["收入(TTM)","净利润","EBITDA","总资产","总负债",
"股东权益","经营现金流","CapEx","总股数","当前股价",
"Beta","行业","同行公司","最近分红"];
关键规则:如果置信度为 Low,自动跳过 DCF Sheet,仅生成相对估值 + 质量评估 + 定性结论。
Sheet 3:相对估值表
// 表头
var headers = ["公司","P/E(TTM)","P/E(Fwd)","P/B","EV/EBITDA","EV/Sales","ROE","股息率"];
// 目标公司行(从数据总览引用)
// 同行公司行(用户提供或AI建议3-5家)
// 行业中位数行 = MEDIAN 公式
// 隐含价值列(每个倍数一列)
ws.Range("I5").Formula = "=MEDIAN(B6:B10)*'数据总览'!$C$17"; // 隐含P/E价值
// 折溢价标记(条件格式)
// 低于中位数 10%+ → 绿色 | 高于中位数 10%+ → 红色 | 区间内 → 无色
// 估值评分
ws.Range("I12").Formula = '=COUNTIF(I5:I9,">"&\'数据总览\'!$C$20)/5';
// 高于当前股价的方法数占比 → 越高越"便宜"
Sheet 5:质量评估矩阵(6 维度)
var dimensions = [
{ name: "护城河与定价权", weight: 0.20 },
{ name: "治理与资本配置", weight: 0.15 },
{ name: "盈利质量(现金转化)", weight: 0.20 },
{ name: "资产负债风险", weight: 0.15 },
{ name: "周期性与外部依赖", weight: 0.15 },
{ name: "执行力与历史兑现", weight: 0.15 }
];
// 每维度: 评分(1-5) + 证据描述 + 权重
// 综合质量分 = 加权平均
ws.Range("E12").Formula = "=SUMPRODUCT(C5:C10,D5:D10)";
// 1-2 = Weak | 3 = Neutral | 4-5 = Strong
// 评分为蓝色可编辑(Font.Color = 0xFF0000)
// 权重也可调
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 · 206 lines · 44 tokens per session scan A 3ecd95d43ffe
equity-valuation is a skill published in the GitHub repository claude-office-skills/claude-office-plugin (9 stars, last pushed 5mo ago), licensed MIT. It adds 44 tokens to every session and 2,596 once invoked, about $0.0002 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 2026-08-31.
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