dcf-modeling

dcf-modeling is a skill for Claude Code from vivy-yi/finance-skills. It costs 97 tokens per session (2,284 once invoked), scanned A, original, MIT.

A discounted cash flow valuation model that estimates what a company is worth from its expected future cash. It includes forecasts, a discount rate, a terminal value, and sensitivity or scenario analysis.

In plain words
What is it for?
Use it to value a company during an acquisition or investment decision. It can also compare alternative assumptions, such as different discount rates or growth forecasts.
Why use it?
It shows how assumptions about growth, profit, taxes, investment, and risk affect an estimated value. This helps reveal which assumptions matter most.

Skill for Claude Code

Written for Claude Code: argument-hint in frontmatter. Also seen: mentions CLAUDE.md.

Good fit Use it to value a company during an acquisition or investment decision. It can also compare alternative assumptions, such as different discount rates or growth forecasts.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/vivy-yi/finance-skills/dcf-modeling
Install

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.

Any agent
npx skills add vivy-yi/finance-skills --skill dcf-modeling
Clone the repo
git clone --depth 1 https://github.com/vivy-yi/finance-skills

Made for: Claude Code.

Wrote 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.

agentmods badge for dcf-modeling

README.md
[![agentmods](https://agentmods.dev/badge/skills/vivy-yi/finance-skills/dcf-modeling/github.svg)](https://agentmods.dev/skills/vivy-yi/finance-skills/dcf-modeling)
Your own site
<a href="https://agentmods.dev/skills/vivy-yi/finance-skills/dcf-modeling"><img src="https://agentmods.dev/badge/skills/vivy-yi/finance-skills/dcf-modeling/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.

agentmods 80×15 button for dcf-modeling

Your own site · 80×15
<a href="https://agentmods.dev/skills/vivy-yi/finance-skills/dcf-modeling"><img src="https://agentmods.dev/badge/skills/vivy-yi/finance-skills/dcf-modeling.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 97 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,284 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00097 $0.02284
Opus 5 $0.00048 $0.01142
Sonnet 5 $0.00019 $0.00457
Haiku 4.5 $0.00010 $0.00228

Measured 9d ago against content hash f2e58c30ae5b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

dcf-modeling 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.

finance-skills/skills/m-and-a/skills/dcf-modeling/SKILL.md · 253 lines

How it starts

The opening of the file, as written. The whole thing — 253 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(WACC 假设/行业 Beta/终值方法)。


/dcf-modeling — DCF 估值建模

Examples

→ 示例:用户说"帮我对目标公司做个 DCF 估值,预测期 5 年,终值用 Gordon 增长模型",系统应调用本技能,执行 DCF 估值建模。

→ 示例:用户说"DCF 模型建好了,但 WACC 假设不确定,帮我做个敏感性分析",系统应调用本技能,执行 WACC 敏感性分析。

→ 示例:用户说"这个 DCF 的结果和可比公司法差了很多,帮我分析差异原因",系统应调用本技能,对比 DCF 和可比公司法结果并分析差异。

第一步:历史财务分析

历史财务数据([最近 3-5 年]):

□ 收入及增速:
| 年份 | 收入(万) | 增速 |
|------|----------|------|
| [YYYY] | [X] | [X]% |
| [YYYY] | [X] | [X]% |
| [最近一年] | [X] | [X]% |

□ EBITDA 及利润率:
| 年份 | EBITDA | 率 |
|------|--------|---|
| [最近一年] | [X]万 | [X]% |

□ 折旧摊销(D&A):[X] 万
□ 资本支出(Capex):[X] 万
□ 营运资本变动:[X] 万
□ 实际税率:[X]%

历史财务特征总结:

□ 收入增长特征:[稳定增长/波动/高成长]
□ EBITDA 率趋势:[上升/稳定/下降]
□ Capex 强度:[X]%(Capex/收入)

第二步:盈利预测

预测假设输入:

□ 收入预测:
  → 预测期:[X] 年([YYYY] - [YYYY])
  → 预测方法:[历史均值/行业增速/执行能力]
  → 假设收入增速:
| 年份 | 增速 | 收入(万) |
|------|------|----------|
| [YYYY] | [X]% | [X] |
| [YYYY] | [X]% | [X] |
| [稳定期首年] | [X]% | [X] |

□ EBITDA 率假设:
  → [采用历史均值/逐步改善/维持稳定]
  → 假设 EBITDA 率:[X]%([YYYY])→ [X]%([YYYY])

□ D&A 假设:[X] 万(维持历史水平/收入比例 [X]%)
□ Capex 假设:[X] 万(维持 [X] 万/收入 [X]%)
□ 营运资本假设:[按历史占收比]
□ 税率假设:[X]%(维持/逐步调整)

预测利润表:

| 年份 | 收入 | EBITDA | D&A | EBIT | 税率 | NOPAT |
|------|------|--------|-----|------|------|-------|
| [YYYY] | [X] | [X] | [X] | [X] | [X]% | [X] |

第三步:自由现金流计算

FCF 计算:

□ NOPAT:[X] 万
□ + 折旧摊销:[X] 万
□ - Capex:[X] 万
□ - 营运资本变动:[X] 万
□ = 自由现金流(FCF):[X] 万

□ 预测期 FCF:
| 年份 | FCF(万) |
|------|---------|
| [YYYY] | [X] |
| [YYYY] | [X] |
| [YYYY] | [X] |
| [YYYY] | [X] |
| [YYYY] | [X] |

第四步:WACC 计算

WACC 输入:

□ 股权成本(CAPM):
  → 无风险利率 Rf:[X]%(10 年国债)
  → 市场风险溢价 ERP:[X]%
  → Beta:[X]([行业/可比公司均值])
  → 股权成本 = Rf + β × ERP = [X]%

□ 债务成本:
  → 税前债务成本:[X]%
  → 税率:[X]%
  → 税后债务成本 = [X]%

□ 资本结构:
  → 股权权重 E/V:[X]%
  → 债务权重 D/V:[X]%

□ WACC = E/V × Ke + D/V × Kd × (1-t)
     = [X]% × [X]% + [X]% × [X]% × [1-X]%
     = [X]%

第五步:终值(Terminal Value)计算

终值方法对比:

□ Gordon Growth Model(永续增长法):
  → 永续增长率 g:[X]%(假设)
  → 终值 FCF:[X] 万([稳定期首年])
  → TV = FCF / (WACC - g) = [X] / ([X]% - [X]%) = [X] 万

□ Exit Multiple(退出倍数法):
  → 假设退出 EBITDA 倍数:[X]x(行业均值)
  → 终值 = EBITDA × Multiple = [X] × [X]x = [X] 万

Read the full file on GitHub · 253 lines

Changes

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.

  1. 9d ago First seen · 253 lines · 97 tokens per session scan A f2e58c30ae5b

Subscribe to this mod's changes

dcf-modeling is a skill published in the GitHub repository vivy-yi/finance-skills (29 stars, last pushed 3mo ago), licensed MIT. It adds 97 tokens to every session and 2,284 once invoked, about $0.0005 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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