Agent skill

Reverse Dcf

by OpenMinis in OpenMinis/MinisSkills

Reverse DCF (reverse discounted cash flow) valuation tool. An agent skill from OpenMinis/MinisSkills.

MITAuto-check passedBusiness, Finance & HR

Install Reverse Dcf

skills CLI
$ npx skills add OpenMinis/MinisSkills --skill reverse-dcf -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install OpenMinis/MinisSkills reverse-dcf --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/OpenMinis/MinisSkills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/reverse-dcf .claude/skills/reverse-dcf && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
reverse-dcf
GitHub stars
440
Token cost
~2.7k tokens
SKILL.md length
1,208 words
Files
1
Skills in repo
49
Repo updated
First seen
Licence
MIT

At a glance

Reverse DCF (reverse discounted cash flow) valuation tool. An agent skill from OpenMinis/MinisSkills.

  • Works in 7 steps: Determine Enterprise Value (EV) → Calculate Base-Year FCFF (the core step… → Build the WACC → …
  • The user says reverse DCF
  • SKILL.md covers Core Idea, Applicability, Practical Steps and Handling Special Cases, plus 2 more sections
  • Reaches emweb.securities.eastmoney.com

What it does

Reverse Dcf is an agent skill from OpenMinis/MinisSkills. Reverse DCF (reverse discounted cash flow) valuation tool. Uses the market price to back-solve the market's implied growth rate expectations, replacing the common forward DCF routine of "tweaking parameters to fit the conclusion." Suitable for mature companies with positive FCFF (A-shares, Hong Kong-listed stocks, and U.S.-listed stocks). Trigger when the user says "reverse DCF," "Reverse DCF," "implied growth rate," "market-implied expectations," "price in," "valuation back-solve," "reverse valuation," "run a…

Its SKILL.md is about 2.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Business, Finance & HR, covering Financial modeling. The repository describes itself as: Skills collection for Minis. The licence is MIT.

When your agent uses it

  • The user says reverse DCF
  • Implied growth rate
  • Market-implied expectations
  • Valuation back-solve

Example prompts

  • “tweaking parameters to fit the conclusion.”
  • “reverse DCF,”
  • “Reverse DCF,”
  • “/reverse-dcf”

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Determine Enterprise Value (EV)
  2. Calculate Base-Year FCFF (the core step and the easiest place to make mistakes)
  3. Build the WACC
  4. Two-Stage DCF Model
  5. Build a Sensitivity Table
  6. Translate CAGR into Plain English
  7. Be Honest About Limitations

What it can do on your machine

Read from SKILL.md and the folder at commit cb72d91. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • emweb.securities.eastmoney.com

    Also links to:

    • zhuanlan.zhihu.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Reverse Dcf loads about 2.7k tokens when it runs. Until then it costs about 174 tokens; SKILL.md has 1,208 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~174
When it runs · the whole SKILL.md, loaded when a task matches
~2.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from OpenMinis/MinisSkills at commit cb72d91, republished under its MIT licence (© OpenMinis). 1,208 words, ~2,682 tokens.

Download SKILL.mdSave it as .claude/skills/reverse-dcf/SKILL.md (or your agent's skills folder).
name
reverse-dcf
description
Reverse DCF (reverse discounted cash flow) valuation tool. Uses the market price to back-solve the market's implied growth rate expectations, replacing the common forward DCF routine of "tweaking parameters to fit the conclusion." Suitable for mature companies with positive FCFF (A-shares, Hong Kong-listed stocks, and U.S.-listed stocks). Trigger when the user says "reverse DCF," "Reverse DCF," "implied growth rate," "market-implied expectations," "price in," "valuation back-solve," "reverse valuation," "run a DCF," or asks to "calculate what the market is betting on." Not suitable for companies with negative FCFF (in that case, use a PS-implied revenue back-solve instead).
version
1.0.0

Reverse DCF: Deriving Market-Implied Expectations

Core Idea

Forward DCF: given assumptions, calculate a target price. The parameters can be adjusted arbitrarily and end up "serving the conclusion."

Reverse DCF: given the market price, back-solve the implied growth rate and translate "expensive" or "cheap" into a verifiable proposition.

The essential difference:

  • Forward DCF outputs "fair value." It is abstract, and you can always be right, but your wallet will not get any thicker.
  • Reverse DCF outputs "market expectations": specific, verifiable numbers that can be compared with reality.

Applicability

Necessary condition: base-year FCFF must be positive.

Applying a standard two-stage DCF to companies with negative FCFF, such as early-stage high-growth companies or companies in an asset-heavy expansion phase, produces meaningless results.

Alternative: use PS-implied revenue back-solving (see "Handling Special Cases" below).

Data requirements:

  • Latest complete annual report (income statement, balance sheet, and cash flow statement)
  • Current stock price/market capitalization
  • Details of interest-bearing debt (short-term borrowings, long-term borrowings, lease liabilities, etc.)
  • Risk-free rate (10-year government bond yield)
  • Industry β and ERP (Damodaran data recommended)

Practical Steps

Step 1: Determine Enterprise Value (EV)
EV = Market Capitalization + Net Debt
Net Debt = Interest-Bearing Debt - Cash and Cash Equivalents - Financial Assets Held for Trading

Notes:

  • For companies like SK Hynix that are in a "net cash" position (cash > interest-bearing debt), EV will be lower than market capitalization.
  • For A-share companies, check whether financial assets held for trading include wealth management products, which are treated as cash equivalents.
  • STAR Market companies often have large amounts of IPO or financing proceeds sitting on the balance sheet, so EV may be far lower than market capitalization.
Step 2: Calculate Base-Year FCFF (the core step and the easiest place to make mistakes)

Recommended Method A: Back-solve from CFO (most reliable in practice)

FCFF = CFO - Capex + After-Tax Interest Expense
  • CFO = net cash flow from operating activities (audited real cash).
  • Capex = cash paid to acquire and construct fixed assets and intangible assets.
  • Net-cash companies: after-tax interest ≈ 0.

Verification Method B: Bottom-up from NOPAT

NOPAT = Operating Profit × (1 - Effective Tax Rate)
FCFF = NOPAT + D&A - Capex - ΔWC
  • Effective tax rate ≠ statutory tax rate (for example, South Korea's statutory rate is 24%, while SK Hynix's effective rate is only 14.9%).
  • D&A = depreciation and amortization.
  • ΔWC = increase in working capital (changes in inventory + accounts receivable + prepayments - accounts payable - contract liabilities).
  • Cross-check the two methods and take the average.

Important: the base year determines everything

  • Using FCFF at the top of the cycle → implied CAGR is understated.
  • Using cycle-median FCFF → implied CAGR is on the high side.
  • This is a judgment, not a calculation.
Step 3: Build the WACC
Re = Rf + β × ERP
WACC = Re × We + Rd×(1-t) × Wd

Suggested parameter sources:

ParameterSource
Risk-free rate Rf10-year government bond yield in the company's home country
Equity risk premium ERPDamodaran annual data (varies by country)
βDamodaran industry unlevered β → re-lever based on D/E (more robust than a single-stock regression β)
Pre-tax cost of debt RdAverage level of investment-grade corporate bonds in the company's home country
Effective tax rateCompany's actual effective tax rate (calculated from financial statements, not the statutory rate)
Step 4: Two-Stage DCF Model
EV = Σ [FCFF₀ × (1+g₁)ᵗ / (1+WACC)ᵗ] + [FCFF₁₀ × (1+g₂) / (WACC-g₂)] / (1+WACC)¹⁰

Where:

  • g₁ = annualized FCFF growth rate during the explicit forecast period (10 years) ← the target to back-solve
  • g₂ = perpetual growth rate (usually 2.5-3%, approximately nominal GDP growth)
  • FCFF₁₀ = FCFF₀ × (1+g₁)¹⁰ × (1+g₂)

Forward DCF: given g₁ and g₂, solve for EV.

Reverse DCF: given EV and g₂, solve for g₁.

Step 5: Build a Sensitivity Table
              Perpetual growth g₂
            1.5%  2.0%  2.5%  3.0%  3.5%
     18%     xxx   xxx   xxx   xxx   xxx
CAGR 20%     xxx   xxx   xxx   xxx   xxx
g₁   22%     xxx   xxx   xxx   xxx   xxx
     25%     xxx   xxx   xxx  [1189] xxx  ← Target EV
     28%     xxx   xxx   xxx   xxx   xxx
  1. Each cell = the EV under the corresponding (CAGR, g₂) combination.
  2. Find the cell closest to the actual EV.
  3. The g₁ corresponding to that cell is the market-implied explicit-period CAGR expectation.

Key observations:

  • Valuation sensitivity to explicit-period CAGR >> sensitivity to perpetual g.
  • Valuation differences are not large within the same row (same CAGR), while valuations can differ by a factor of two within the same column (same perpetual g).
  • Therefore, the key valuation question is whether the "10-year CAGR can be achieved," not whether "3% perpetual growth is too aggressive."
Step 6: Translate CAGR into Plain English

After calculating the implied CAGR, make three translations:

Translation 1: Company size in 10 years

FCFF₁₀ = FCFF₀ × (1+g₁)¹⁰
Corresponding revenue ≈ FCFF₁₀ / (current FCFF/revenue conversion rate)

Translation 2: What needs to happen at the industry level

Current TAM → required revenue in 10 years → implied market share change
Or: how many times TAM must grow to support it

Translation 3: Compare with history

Company's actual CAGR over the past 10 years vs implied CAGR
Historical CAGR comparison with industry peers/global tech giants
(TSMC's CAGR over the past 20 years was approximately 18%, already an industry miracle)
Step 7: Be Honest About Limitations
  1. Terminal value (TV) accounts for a high proportion of EV: this is especially dangerous for cyclical stocks. TV accounting for >50% is a red flag.
    • Alternative: Exit Multiple method (use the industry median EV/EBITDA in year 10 for the exit).
  2. The choice of base-year FCFF determines everything: the top and bottom of the cycle can differ by several times.
  3. D&A and Capex are estimates: accuracy is limited by the granularity of public disclosures.
  4. Reverse DCF tells you what the market expects, not whether the market is right or wrong.
    • A 25% CAGR may or may not be reasonable and requires independent judgment.
    • It is not a conclusion. It is the starting point for discussion.
Show full SKILL.md (425 more words)Show less

Handling Special Cases

Companies with Negative FCFF (such as Cambricon)

A standard two-stage DCF cannot be used for the back-solve. Use PS-implied revenue back-solving instead:

  1. Assume a reasonable terminal PE, such as 30x in the mature phase.
  2. Back-solve the required net profit 10 years from now.
  3. Then assume a reasonable net margin and back-solve the required revenue 10 years from now.
  4. Calculate the implied revenue CAGR.
Implied Revenue₁₀ = Market Capitalization / Terminal PE / Net Profit Margin
Implied CAGR = (Implied Revenue₁₀ / Current Revenue)^(1/10) - 1
Cyclical Stocks

Use cycle-median FCFF instead of a single year's FCFF as the base-year data.

You can also use the Exit Multiple method instead of the Gordon Growth Model to calculate terminal value.

DataRecommended acquisition method
Stock price/market capitalizationbrowser_use navigate to Sina Finance or Xueqiu individual stock pages, then use get_text to extract
Financial statement dataUse browser_use navigate to open https://emweb.securities.eastmoney.com/PC_HSF10/NewFinanceAnalysis/Index?type=web&code=<stock-code>; the income statement, balance sheet, and cash flow statement tabs provide the complete data.
Details of interest-bearing debtSame as above, balance sheet tab: short-term borrowings, long-term borrowings, lease liabilities, and bonds payable
CFO/CapexSame as above, cash flow statement tab: net cash flow from operating activities and cash paid to acquire and construct fixed assets
Industry β/ERPDamodaran Online (pages.stern.nyu.edu/~adamodar/)
10-year government bond yieldTradingView or official central bank websites, retrieved with browser_use navigate
Historical revenue/CAGREast Money PC_HSF10 income statement tab, pull 5-10 years of revenue data and calculate manually

Note: All data should be retrieved in real time through browser_use; do not rely on training data. A-share stock codes in emweb format are SH600519 (Shanghai) or SZ000651 (Shenzhen), and Hong Kong stocks use HK00700.

Practical Case References

Series of articles (author: monokuro, Manager on the valuation team at a Big Four accounting firm in Tokyo):

  1. Core case: "What Expectations Is the Market Pricing In for SK Hynix? Reverse DCF Gives You a Startling Number": uses Reverse DCF to calculate that SK Hynix's current stock price implies 25% annualized FCFF growth over the next 10 years. FCFF would need to reach 208 trillion won in 10 years, nine times 2025 revenue and twice the actual growth rate over the past 10 years (13%).
  2. Method correction: "Three Corrections to the Previous Reverse DCF for the Five AI Chip Giants": points out practical pitfalls such as using Exit Multiple instead of GGM, replacing single-year FCFF with cycle-median FCFF, and correcting data sources. It can be used as supplemental reference for the limitations section of Reverse DCF.

The core methodological reference is Aswath Damodaran's valuation framework (Investment Valuation and the country risk premium data updated each year).

© OpenMinis, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in reverse-dcf of OpenMinis/MinisSkills.

Open the folder on GitHubat commit cb72d91

Compare with similar skills

Reverse Dcf next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Reverse Dcf compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Reverse Dcf this skillOpenMinis/MinisSkills440—~2.7kAutomated safety check: PassMIT
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Equity Researcherlzwme/finance-quant-skills4321 repos~4.9kAutomated safety check: PassNone
Equity ResearchrollingSirius/equity-research-skill452—~1.5kAutomated safety check: PassMIT
SaaS Metrics Coachrongxinzy/RongxinAI1542 repos~1.3kAutomated safety check: PassMIT
Startup Financial Modelingnicepkg/auto-company19210 repos~2.8kAutomated safety check: PassNone

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Questions about Reverse Dcf

What does Reverse Dcf do?

Reverse DCF (reverse discounted cash flow) valuation tool. An agent skill from OpenMinis/MinisSkills. Reverse Dcf is an agent skill from OpenMinis/MinisSkills. Reverse DCF (reverse discounted cash flow) valuation tool.

When should I use Reverse Dcf?

Reverse Dcf fits situations like: the user says reverse DCF; implied growth rate; market-implied expectations; valuation back-solve.

How do I install Reverse Dcf in Claude Code?

Run `npx skills add OpenMinis/MinisSkills --skill reverse-dcf -a claude-code`. Or copy the skill folder (reverse-dcf in OpenMinis/MinisSkills) into .claude/skills/reverse-dcf in your project. Claude Code loads it when a task matches its description.

How do I install Reverse Dcf in Codex?

Run `npx skills add OpenMinis/MinisSkills --skill reverse-dcf -a codex`. Or copy the skill folder (reverse-dcf in OpenMinis/MinisSkills) into .agents/skills/reverse-dcf in your project. Codex loads it when a task matches its description.

Can I use Reverse Dcf in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add OpenMinis/MinisSkills --skill reverse-dcf -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/reverse-dcf, .gemini/skills/reverse-dcf, .github/skills/reverse-dcf and .opencode/skills/reverse-dcf in your project.

What does Reverse Dcf need to run?

SKILL.md names no scripts, command-line tools or credentials: Reverse Dcf is instructions for the agent only.

Does Reverse Dcf access the network?

SKILL.md names 2 domains. In commands or code: emweb.securities.eastmoney.com; the agent is likely to contact it when it follows the instructions. As links in the text: zhuanlan.zhihu.com. This is read from the text; nothing was executed.

Is Reverse Dcf safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Reverse Dcf use?

Reverse Dcf is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Reverse Dcf use?

About 2.7k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Reverse Dcf?

Skills that share tags, products or a category with Reverse Dcf: Creating Financial Models (Chen-zexi/open-ptc-agent, 730 stars), Equity Researcher (lzwme/finance-quant-skills, 432 stars), Equity Research (rollingSirius/equity-research-skill, 452 stars) and SaaS Metrics Coach (rongxinzy/RongxinAI, 154 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Reverse Dcf?

OpenMinis (a GitHub organization) maintains it in OpenMinis/MinisSkills, which has 440 GitHub stars. The repository holds 49 skills in this directory. The repository was last updated on October 5, 2026.

Source: OpenMinis/MinisSkills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.