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 valuation-integrationgit 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/valuation-integration)<a href="https://agentmods.dev/skills/vivy-yi/finance-skills/valuation-integration"><img src="https://agentmods.dev/badge/skills/vivy-yi/finance-skills/valuation-integration/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/valuation-integration"><img src="https://agentmods.dev/badge/skills/vivy-yi/finance-skills/valuation-integration.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 | $0.00087 | $0.02032 |
| Opus 5 | $0.00044 | $0.01016 |
| Sonnet 5 | $0.00017 | $0.00406 |
| Haiku 4.5 | $0.00009 | $0.00203 |
Grade A, and why
valuation-integration 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 — 223 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(估值方法权重/行业特点/谈判策略)。
/valuation-integration — 估值综合分析
Examples
→ 示例:用户说"三种估值方法结果不一样,最终交易价格怎么定,帮我综合分析一下",系统应调用本技能,整合多种估值方法并给出定价建议。
→ 示例:用户说"管理层对估值区间有争议,需要一个中立角度的分析",系统应调用本技能,生成中立估值综合报告。
→ 示例:用户说"交易估值确定了,帮我评估一下协同效应能不能支撑这个价格",系统应调用本技能,评估协同效应支撑的交易价格合理性。
第一步:各估值方法汇总
DCF 估值结果:
□ 估值区间:[X-X] 万(中值 [X] 万)
□ 核心假设:WACC [X]%,永续增长 [X]%
□ 置信度:[✅ 高 / ⚠️ 中 / 🔴 低]
□ 方法适用性:[✅ 适合 / ⚠️ 基本适合 / 🔴 不确定]
可比公司法估值结果:
□ EV/EBITDA 倍数法:
→ 可比公司:[列表]
→ 中位数倍数:[X]x
→ 调整后倍数:[X]x(流动性折价/控股权溢价)
→ 估值结果:[X] 万
□ P/E 倍数法(如适用):
→ 可比公司:[列表]
→ 中位数倍数:[X]x
→ 调整后倍数:[X]x
→ 估值结果:[X] 万
□ P/S 倍数法(如适用):
→ 可比公司:[列表]
→ 中位数倍数:[X]x
→ 估值结果:[X] 万
□ 可比公司法估值区间:[X-X] 万(中值 [X] 万)
□ 置信度:[✅ 高 / ⚠️ 中 / 🔴 低]
交易法估值结果(Precedent Transactions):
□ 近期交易:[交易列表]
□ 交易倍数中位数:[X]x(EV/EBITDA)
□ 控股权溢价中位数:[X]%
□ 交易法估值:[X] 万
□ 置信度:[✅ 高 / ⚠️ 中 / 🔴 低]
第二步:估值结果对比分析
各方法估值对比:
| 估值方法 | 低值 | 中值 | 高值 | 置信度 |
|---------|------|------|------|--------|
| DCF | [X]万 | [X]万 | [X]万 | [高/中/低] |
| 可比公司 EV/EBITDA | [X]万 | [X]万 | [X]万 | [高/中/低] |
| 可比公司法 P/E | [X]万 | [X]万 | [X]万 | [高/中/低] |
| 交易法 | [X]万 | [X]万 | [X]万 | [高/中/低] |
□ 各方法估值中值范围:[X-X] 万
□ 差异分析:
→ 最高 vs 最低中值差异:[+/-X]%([X] 万)
→ 差异原因:[分析]
方法可靠性评估:
□ DCF:适合 [高成长/稳定增长] 公司,但 [WACC/永续增长] 假设敏感
□ 可比公司法:市场情绪影响大, [流动性/控制权] 调整复杂
□ 交易法:历史交易可能不反映当前市场
第三步:权重分配与综合估值
权重分配依据:
□ 权重分配逻辑:
→ 根据 [方法适用性/数据可靠性/市场环境] 综合判断
□ 各方法权重:
| 估值方法 | 权重 | 权重依据 |
|---------|------|---------|
| DCF | [X]% | [描述] |
| 可比公司法 | [X]% | [描述] |
| 交易法 | [X]% | [描述] |
□ 加权估值:
= [X]% × [X]万 + [X]% × [X]万 + [X]% × [X]万
= [X] 万
综合估值区间:
□ 综合估值区间:[X-X] 万
□ 综合估值中值:[X] 万
□ 每股价值(如适用):[X] 元
□ 区间合理性评估:
→ 上限合理性:[描述]
→ 下限合理性:[描述]
第四步:与报价/谈判区间对比
对比分析:
□ 当前报价(如有):[X] 万
□ 报价 vs 综合估值中值:[+/-X]%(溢价/折价)
□ 报价 vs 估值区间:[在区间内/超出区间]
□ 谈判空间分析:
→ 可接受价格区间:[X-X] 万
→ 理想价格:[X] 万
→ 报价上限:[X] 万
第五步:投资建议
风险调整后建议:
□ 估值敏感性:
→ 对 [关键假设] 的敏感度较高
→ 主要风险:[描述]
□ 风险调整:
→ 协同效应价值:[X] 万(已计入/未计入)
→ 控制权溢价:[X]%([X] 万)
→ 流动性折价:[X]%([X] 万)
□ 投资建议:
→ [建议:买入/持有/观望/放弃]
→ 理由:[描述]
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 · 223 lines · 87 tokens per session scan A d9c2ab887b16
valuation-integration is a skill published in the GitHub repository vivy-yi/finance-skills (29 stars, last pushed 3mo ago), licensed MIT. It adds 87 tokens to every session and 2,032 once invoked, about $0.0004 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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