Dcf Valuation
edinetdb/dexter-jp
Performs discounted cash flow (DCF) valuation analysis to estimate intrinsic value per share for Japanese listed companies.
This skill provides an advanced financial modeling suite with DCF analysis, sensitivity testing, Monte Carlo simulations, and scenario planning for investment decisions
Install Creating Financial Models
$ npx skills add Chen-zexi/open-ptc-agent --skill creating-financial-models -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Chen-zexi/open-ptc-agent creating-financial-models --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/Chen-zexi/open-ptc-agent.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/creating-financial-models .claude/skills/creating-financial-models && rm -rf skills-srcUse ~/.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/
Install the "creating-financial-models" agent skill from https://github.com/Chen-zexi/open-ptc-agent/tree/main/skills/creating-financial-models into .claude/skills/creating-financial-models/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "creating-financial-models", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/Chen-zexi/open-ptc-agent/tree/main/skills/creating-financial-modelsType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add Chen-zexi/open-ptc-agent --skill creating-financial-models -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Chen-zexi/open-ptc-agent creating-financial-models --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Chen-zexi/open-ptc-agent.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/creating-financial-models .agents/skills/creating-financial-models && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "creating-financial-models" agent skill from https://github.com/Chen-zexi/open-ptc-agent/tree/main/skills/creating-financial-models into .agents/skills/creating-financial-models/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "creating-financial-models", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Chen-zexi/open-ptc-agent --skill creating-financial-models -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Chen-zexi/open-ptc-agent creating-financial-models --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Chen-zexi/open-ptc-agent.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/creating-financial-models .cursor/skills/creating-financial-models && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "creating-financial-models" agent skill from https://github.com/Chen-zexi/open-ptc-agent/tree/main/skills/creating-financial-models into .cursor/skills/creating-financial-models/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "creating-financial-models", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/Chen-zexi/open-ptc-agent.git --path skills/creating-financial-models--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add Chen-zexi/open-ptc-agent --skill creating-financial-models -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Chen-zexi/open-ptc-agent creating-financial-models --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Chen-zexi/open-ptc-agent.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/creating-financial-models .gemini/skills/creating-financial-models && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "creating-financial-models" agent skill from https://github.com/Chen-zexi/open-ptc-agent/tree/main/skills/creating-financial-models into .gemini/skills/creating-financial-models/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "creating-financial-models", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install Chen-zexi/open-ptc-agent creating-financial-modelsInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add Chen-zexi/open-ptc-agent --skill creating-financial-models -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Chen-zexi/open-ptc-agent.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/creating-financial-models .github/skills/creating-financial-models && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "creating-financial-models" agent skill from https://github.com/Chen-zexi/open-ptc-agent/tree/main/skills/creating-financial-models into .github/skills/creating-financial-models/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "creating-financial-models", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Chen-zexi/open-ptc-agent --skill creating-financial-models -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Chen-zexi/open-ptc-agent creating-financial-models --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Chen-zexi/open-ptc-agent.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/creating-financial-models .opencode/skills/creating-financial-models && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "creating-financial-models" agent skill from https://github.com/Chen-zexi/open-ptc-agent/tree/main/skills/creating-financial-models into .opencode/skills/creating-financial-models/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "creating-financial-models", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
creating-financial-models- GitHub stars
- 729
- Used in
- 3 other repos
- Token cost
- ~1.3k tokens
- SKILL.md length
- 568 words
- Files
- 3
- Skills in repo
- 1
- Repo updated
- First seen
- Licence
- MIT
At a glance
This skill provides an advanced financial modeling suite with DCF analysis, sensitivity testing, Monte Carlo simulations, and scenario planning for investment decisions
- Works in 4 steps: Discounted Cash Flow (DCF) Analysis → Sensitivity Analysis → Monte Carlo Simulation → …
- Tasks that involve Financial modeling
- SKILL.md covers Core Capabilities, Input Requirements, Output Formats and Model Types Supported, plus 6 more sections
- Runs Python scripts from its folder
What it does
Creating Financial Models is an agent skill from Chen-zexi/open-ptc-agent. This skill provides an advanced financial modeling suite with DCF analysis, sensitivity testing, Monte Carlo simulations, and scenario planning for investment decisions
Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `dcf_model.py` and `sensitivity_analysis.py`).
It sits in Business, Finance & HR, covering Financial modeling. It works with LangChain and Model Context Protocol. The repository describes itself as: An open source implementation of code execution with MCP (Programatic Tool Calling). The licence is MIT.
When your agent uses it
- Tasks that involve Financial modeling
Example prompts
- “/creating-financial-models”
Requirements
- Python 3
Workflow steps
4 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 425b957. 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
Ships script files (Python), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
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
Creating Financial Models loads about 1.3k tokens when it runs. Until then it costs about 49 tokens; SKILL.md has 568 words of instructions outside code blocks.
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 Chen-zexi/open-ptc-agent at commit 425b957, republished under its MIT licence (© Chen-zexi). 568 words, ~1,277 tokens.
Download SKILL.mdSave it as
.claude/skills/creating-financial-models/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.- name
- creating-financial-models
- description
- This skill provides an advanced financial modeling suite with DCF analysis, sensitivity testing, Monte Carlo simulations, and scenario planning for investment decisions
Financial Modeling Suite
A comprehensive financial modeling toolkit for investment analysis, valuation, and risk assessment using industry-standard methodologies.
Core Capabilities
1. Discounted Cash Flow (DCF) Analysis
- Build complete DCF models with multiple growth scenarios
- Calculate terminal values using perpetuity growth and exit multiple methods
- Determine weighted average cost of capital (WACC)
- Generate enterprise and equity valuations
2. Sensitivity Analysis
- Test key assumptions impact on valuation
- Create data tables for multiple variables
- Generate tornado charts for sensitivity ranking
- Identify critical value drivers
3. Monte Carlo Simulation
- Run thousands of scenarios with probability distributions
- Model uncertainty in key inputs
- Generate confidence intervals for valuations
- Calculate probability of achieving targets
4. Scenario Planning
- Build best/base/worst case scenarios
- Model different economic environments
- Test strategic alternatives
- Compare outcome probabilities
Input Requirements
For DCF Analysis
- Historical financial statements (3-5 years)
- Revenue growth assumptions
- Operating margin projections
- Capital expenditure forecasts
- Working capital requirements
- Terminal growth rate or exit multiple
- Discount rate components (risk-free rate, beta, market premium)
For Sensitivity Analysis
- Base case model
- Variable ranges to test
- Key metrics to track
For Monte Carlo Simulation
- Probability distributions for uncertain variables
- Correlation assumptions between variables
- Number of iterations (typically 1,000-10,000)
For Scenario Planning
- Scenario definitions and assumptions
- Probability weights for scenarios
- Key performance indicators to track
Output Formats
DCF Model Output
- Complete financial projections
- Free cash flow calculations
- Terminal value computation
- Enterprise and equity value summary
- Valuation multiples implied
- Excel workbook with full model
Sensitivity Analysis Output
- Sensitivity tables showing value ranges
- Tornado chart of key drivers
- Break-even analysis
- Charts showing relationships
Monte Carlo Output
- Probability distribution of valuations
- Confidence intervals (e.g., 90%, 95%)
- Statistical summary (mean, median, std dev)
- Risk metrics (VaR, probability of loss)
Scenario Planning Output
- Scenario comparison table
- Probability-weighted expected values
- Decision tree visualization
- Risk-return profiles
Model Types Supported
Corporate Valuation
- Mature companies with stable cash flows
- Growth companies with J-curve projections
- Turnaround situations
Project Finance
- Infrastructure projects
- Real estate developments
- Energy projects
M&A Analysis
- Acquisition valuations
- Synergy modeling
- Accretion/dilution analysis
LBO Models
- Leveraged buyout analysis
- Returns analysis (IRR, MOIC)
- Debt capacity assessment
Show full SKILL.md (225 more words)Show less
Best Practices Applied
Modeling Standards
- Consistent formatting and structure
- Clear assumption documentation
- Separation of inputs, calculations, outputs
- Error checking and validation
- Version control and change tracking
Valuation Principles
- Use multiple valuation methods for triangulation
- Apply appropriate risk adjustments
- Consider market comparables
- Validate against trading multiples
- Document key assumptions clearly
Risk Management
- Identify and quantify key risks
- Use probability-weighted scenarios
- Stress test extreme cases
- Consider correlation effects
- Provide confidence intervals
Example Usage
"Build a DCF model for this technology company using the attached financials"
"Run a Monte Carlo simulation on this acquisition model with 5,000 iterations"
"Create sensitivity analysis showing impact of growth rate and WACC on valuation"
"Develop three scenarios for this expansion project with probability weights"
Scripts Included
dcf_model.py: Complete DCF valuation enginesensitivity_analysis.py: Sensitivity testing framework
Limitations and Disclaimers
- Models are only as good as their assumptions
- Past performance doesn't guarantee future results
- Market conditions can change rapidly
- Regulatory and tax changes may impact results
- Professional judgment required for interpretation
- Not a substitute for professional financial advice
Quality Checks
The model automatically performs:
- Balance sheet balancing checks
- Cash flow reconciliation
- Circular reference resolution
- Sensitivity bound checking
- Statistical validation of Monte Carlo results
Updates and Maintenance
- Models use latest financial theory and practices
- Regular updates for market parameter defaults
- Incorporation of regulatory changes
- Continuous improvement based on usage patterns
© Chen-zexi, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 2 other files in skills/creating-financial-models of Chen-zexi/open-ptc-agent.
- SKILL.md
- dcf_model.py
- sensitivity_analysis.py
Open the folder on GitHubat commit 425b957
Used in 3 other repositories
We found 9 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 3 other GitHub owners. This page covers the copy in Chen-zexi/open-ptc-agent, which our catalogue first saw on October 7, 2026.
Compare with similar skills
Creating Financial Models 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Creating Financial Models this skillChen-zexi/open-ptc-agent | 729 | 3 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Dcf Valuationedinetdb/dexter-jp | 312 | — | ~1.1k | Automated safety check: Pass | MIT | |
| Dcf ModelWind-Alice/AliceMarket | 134 | 2 repos | ~12k | Automated safety check: Pass | None | |
| Analyst EstimatesOctagonAI/skills | 127 | — | ~1.1k | Automated safety check: Pass | MIT | |
| Historical Financial RatingsOctagonAI/skills | 127 | — | ~1k | Automated safety check: Pass | MIT | |
| Ratings SnapshotOctagonAI/skills | 127 | — | ~1.1k | Automated safety check: Pass | MIT |
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Related
Works with
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Questions about Creating Financial Models
What does Creating Financial Models do?
This skill provides an advanced financial modeling suite with DCF analysis, sensitivity testing, Monte Carlo simulations, and scenario planning for investment decisions. Creating Financial Models is an agent skill from Chen-zexi/open-ptc-agent.
When should I use Creating Financial Models?
Creating Financial Models fits situations like: tasks that involve Financial modeling.
How do I install Creating Financial Models in Claude Code?
Run `npx skills add Chen-zexi/open-ptc-agent --skill creating-financial-models -a claude-code`. Or copy the skill folder (skills/creating-financial-models in Chen-zexi/open-ptc-agent) into .claude/skills/creating-financial-models in your project. Claude Code loads it when a task matches its description.
How do I install Creating Financial Models in Codex?
Run `npx skills add Chen-zexi/open-ptc-agent --skill creating-financial-models -a codex`. Or copy the skill folder (skills/creating-financial-models in Chen-zexi/open-ptc-agent) into .agents/skills/creating-financial-models in your project. Codex loads it when a task matches its description.
Can I use Creating Financial Models 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 Chen-zexi/open-ptc-agent --skill creating-financial-models -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/creating-financial-models, .gemini/skills/creating-financial-models, .github/skills/creating-financial-models and .opencode/skills/creating-financial-models in your project.
What does Creating Financial Models need to run?
Going by SKILL.md and its folder, Creating Financial Models needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Creating Financial Models access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Creating Financial Models 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 Creating Financial Models use?
Creating Financial Models 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 Creating Financial Models use?
About 1.3k tokens (SKILL.md is roughly 5.1k 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 Creating Financial Models?
Skills that share tags, products or a category with Creating Financial Models: Dcf Valuation (edinetdb/dexter-jp, 312 stars), Dcf Model (Wind-Alice/AliceMarket, 134 stars), Analyst Estimates (OctagonAI/skills, 127 stars) and Historical Financial Ratings (OctagonAI/skills, 127 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Creating Financial Models?
Chen-zexi (a GitHub user) maintains it in Chen-zexi/open-ptc-agent, which has 729 GitHub stars. The repository was last updated on January 21, 2026.
Source: Chen-zexi/open-ptc-agent on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.