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 guoliang1114-boop/AriaAI --skill valuation-and-pricinggit clone --depth 1 https://github.com/guoliang1114-boop/AriaAIWrote 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/guoliang1114-boop/ariaai/valuation-and-pricing)<a href="https://agentmods.dev/skills/guoliang1114-boop/ariaai/valuation-and-pricing"><img src="https://agentmods.dev/badge/skills/guoliang1114-boop/ariaai/valuation-and-pricing/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/guoliang1114-boop/ariaai/valuation-and-pricing"><img src="https://agentmods.dev/badge/skills/guoliang1114-boop/ariaai/valuation-and-pricing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00038 | $0.02788 |
| Opus 5 | $0.00019 | $0.01394 |
| Sonnet 5 | $0.00008 | $0.00558 |
| Haiku 4.5 | $0.00004 | $0.00279 |
Grade A, and why
valuation-and-pricing 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 12d 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 — 302 lines — stays where its author put it; the contents beside it link to each section on GitHub.
估值与定价分析
When To Use
- 并购交易的标的估值和定价建议
- 股权融资的企业价值评估
- 财务报告目的的公允价值评估
- 投资决策的回报分析
- 争议解决中的价值评估
Tools
- 财务数据库（Bloomberg、Capital IQ、Wind）
- WACC计算器
- DCF估值模型
- 可比公司/可比交易分析模板
- 敏感性分析矩阵
Framework
估值方法论
Method 1: Discounted Cash Flow (DCF)
- 自由现金流预测（FCFF / FCFE）
- 折现率计算（WACC）
- 终值计算（永续增长法 / 退出倍数法）
- 企业价值 = PV(显性期FCF) + PV(终值) - 净债务
WACC计算：
WACC = E/(D+E) × Ke + D/(D+E) × Kd × (1-T)
Ke = Rf + β × ERP + α（公司特定风险溢价）
- Rf: 无风险利率（10年期国债收益率）
- β: 权益贝塔（行业可比公司去杠杆β的中位数）
- ERP: 股权风险溢价（通常4-6%）
- α: 公司特定风险溢价（0-5%）
- Kd: 债务成本（税前）
- T: 企业所得税率
终值计算：
- 永续增长法：TV = FCF_n × (1+g) / (WACC - g)
- 退出倍数法：TV = EBITDA_n × Exit Multiple
Method 2: Comparable Company Analysis (Comps)
- 选择可比公司（行业、规模、增长、盈利能力）
- 关键倍数：EV/EBITDA、EV/Revenue、P/E、P/B
- 调整因素：流动性折价、控制溢价、规模差异
Method 3: Comparable Transaction Analysis (Precedents)
- 选择同行业近期并购交易
- 关键倍数：EV/EBITDA、EV/Revenue、P/E
- 调整因素：交易时间、交易条件、协同效应
Method 4: Leveraged Buyout (LBO)
- 目标回报：IRR ≥ 20%，MOIC ≥ 2.5x
- 资本结构设计（优先级债务/次级债/夹层/股权）
- 退出估值假设
- 反推可支付价格（Pricing-to-Return）
中国资产评估准则
- 《资产评估基本准则》（财政部令第83号）
- 《资产评估执业准则——企业价值》
- 收益法、市场法、资产基础法三种基本方法
Workflow
1. 基础数据收集
├─ 历史财务数据（3-5年）
├─ 管理层预测/商业计划
├─ 行业研究报告
└─ 可比公司/交易数据
2. 财务分析
├─ 收入增长趋势分析
├─ 盈利能力分析（毛利率、EBITDA利润率）
├─ 资本支出和营运资本分析
├─ 资本结构分析
└─ 可持续EBITDA调整
3. DCF估值
├─ 自由现金流预测
├─ WACC计算
├─ 终值计算
├─ 敏感性分析（WACC ± 0.5%，g ± 0.5%）
└─ 估值区间确定
4. 相对估值
├─ 可比公司选择及倍数计算
├─ 可比交易选择及倍数计算
├─ 异常值剔除及中位数/均值
└─ 估值区间确定
5. 综合估值
├─ 各方法估值权重设定
├─ Football Field图绘制
├─ 估值区间综合
└─ 定价建议
Output Format
# 估值与定价分析报告
## 一、标的概况
| 项目 | 内容 |
|------|------|
| 公司名称 | |
| 所属行业 | |
| 收入规模 | |
| EBITDA | |
| 净利润 | |
| 交易类型 | |
## 二、财务分析
| 指标 | Year-2 | Year-1 | Year 0 | Year 1E | Year 2E | Year 3E |
|------|--------|--------|--------|---------|---------|---------|
| 收入 | | | | | | |
| 增长率 | | | | | | |
| EBITDA | | | | | | |
| EBITDA利润率 | | | | | | |
| 净利润 | | | | | | |
| CapEx | | | | | | |
## 三、DCF估值
### 关键假设
| 假设 | 数值 | 来源/依据 |
|------|------|-----------|
| 无风险利率 | | |
| Beta | | |
| ERP | | |
| 债务成本 | | |
| WACC | | |
| 永续增长率 | | |
### 估值结果
| 年份 | FCF | 折现因子 | PV(FCF) |
|------|-----|----------|---------|
| Year 1 | | | |
| Year 2 | | | |
| Year 3 | | | |
| Year 4 | | | |
| Year 5 | | | |
| 终值 | | | |
| **企业价值** | | | |
### 敏感性分析
| | WACC 8% | WACC 8.5% | WACC 9% | WACC 9.5% | WACC 10% |
|---|---------|-----------|---------|-----------|----------|
| g=1.5% | | | | | |
| g=2.0% | | | | | |
| g=2.5% | | | | | |
| g=3.0% | | | | | |
## 四、可比公司估值
| 公司 | EV/EBITDA | EV/Revenue | P/E | PEG |
|------|-----------|------------|-----|-----|
| | | | | |
| 中位数 | | | | |
| 均值 | | | | |
## 五、可比交易估值
| 交易 | 日期 | EV/EBITDA | EV/Revenue | P/E | 备注 |
|------|------|-----------|------------|-----|------|
| | | | | | |
| 中位数 | | | | | |
## 六、综合估值（Football Field）
| 方法 | 低值 | 中值 | 高值 | 权重 |
|------|------|------|------|------|
| DCF | | | | 50% |
| 可比公司 | | | | 25% |
| 可比交易 | | | | 25% |
| **综合估值** | | | | |
## 七、定价建议
- 建议交易价格区间：____
- 对应EV/EBITDA倍数：____
- 关键价值驱动因素：____
- 主要价值风险因素：____
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.
- 12d ago First seen · 302 lines · 38 tokens per session scan A 4f8892107f87
valuation-and-pricing is a skill published in the GitHub repository guoliang1114-boop/AriaAI (37 stars, last pushed today), licensed MIT. It adds 38 tokens to every session and 2,788 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 2026-08-30.
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