Creating Financial Models
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
Discounted cash flow valuation with sensitivity analysis. An agent skill from daloopa/investing.
$ npx skills add daloopa/investing --skill dcf -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install daloopa/investing dcf --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/daloopa/investing.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/dcf .claude/skills/dcf && 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 "dcf" agent skill from https://github.com/daloopa/investing/tree/main/.claude/skills/dcf into .claude/skills/dcf/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dcf", 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/daloopa/investing/tree/main/.claude/skills/dcfType 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 daloopa/investing --skill dcf -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install daloopa/investing dcf --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/daloopa/investing.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/dcf .agents/skills/dcf && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "dcf" agent skill from https://github.com/daloopa/investing/tree/main/.claude/skills/dcf into .agents/skills/dcf/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dcf", 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 daloopa/investing --skill dcf -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install daloopa/investing dcf --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/daloopa/investing.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/dcf .cursor/skills/dcf && 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 "dcf" agent skill from https://github.com/daloopa/investing/tree/main/.claude/skills/dcf into .cursor/skills/dcf/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dcf", 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/daloopa/investing.git --path .claude/skills/dcf--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 daloopa/investing --skill dcf -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install daloopa/investing dcf --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/daloopa/investing.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/dcf .gemini/skills/dcf && 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 "dcf" agent skill from https://github.com/daloopa/investing/tree/main/.claude/skills/dcf into .gemini/skills/dcf/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dcf", 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 daloopa/investing dcfInstalls 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 daloopa/investing --skill dcf -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/daloopa/investing.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/dcf .github/skills/dcf && 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 "dcf" agent skill from https://github.com/daloopa/investing/tree/main/.claude/skills/dcf into .github/skills/dcf/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dcf", 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 daloopa/investing --skill dcf -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install daloopa/investing dcf --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/daloopa/investing.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/dcf .opencode/skills/dcf && 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 "dcf" agent skill from https://github.com/daloopa/investing/tree/main/.claude/skills/dcf into .opencode/skills/dcf/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dcf", 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.
dcfDiscounted cash flow valuation with sensitivity analysis. An agent skill from daloopa/investing.
Dcf is an agent skill from daloopa/investing. Discounted cash flow valuation with sensitivity analysis
Its SKILL.md is about 2.5k 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 licence is Apache-2.0.
10 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit e2dd01d. It shows what the files ask for, not the result of running them.
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.
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.
Hosts in commands or code, which the agent is likely to contact:
daloopa.comFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Dcf loads about 2.5k tokens when it runs. Until then it costs about 15 tokens; SKILL.md has 1,096 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.
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.
The full file from daloopa/investing at commit e2dd01d, republished under its Apache-2.0 licence (© daloopa). 1,096 words, ~2,453 tokens.
.claude/skills/dcf/SKILL.md (or your agent's skills folder).Build a discounted cash flow (DCF) valuation for the company specified by the user: $ARGUMENTS
Before starting, read ../data-access.md for data access methods and ../design-system.md for formatting conventions. Follow the data access detection logic and design system throughout this skill.
Follow these steps:
Look up the company by ticker using discover_companies. Capture:
company_idlatest_calendar_quarter — anchor for all period calculations below (see ../data-access.md Section 1.5)latest_fiscal_quarter../data-access.md Section 4.5Get market-side inputs for {TICKER} (see ../data-access.md Section 2 for how to source market data in your environment):
If market data is unavailable, use reasonable defaults: beta=1.0, risk-free rate=4.5%, and note the assumptions.
Calculate 8 quarters backward from latest_calendar_quarter. Pull:
Also pull segment revenue and any available guidance series.
Cost of Equity (CAPM):
Cost of Debt:
Capital Structure:
Show all inputs and the resulting WACC clearly.
Before projecting top-down, attempt a bottoms-up revenue build using operational KPIs. This produces a significantly more defensible DCF — a top-down trend decay is a guess; a bottoms-up KPI build is analysis.
Discover segment and KPI data: Pull segment revenue breakdown + segment-specific KPIs for the target company. Use the sector taxonomy to know what to search for:
Build bottoms-up projections per segment: For each segment with KPI data, project revenue using unit economics:
Sum segment projections to get total revenue for each of 5 years. Show the build clearly so the reader can challenge individual segment assumptions.
Fall back to top-down if KPIs aren't available. If segment KPIs are sparse or unavailable, use the top-down approach in Section 5b instead, but note explicitly that the model is less reliable without bottoms-up drivers.
Build 5-year FCF projections. If a projection engine is available (see ../data-access.md Section 5), use it. Otherwise, project manually:
Show all assumptions clearly — this is the most judgment-intensive part. If using this fallback instead of the KPI-driven build (Section 5a), note the limitation.
Calculate terminal value using perpetuity growth method:
Also compute:
Build a sensitivity table varying two key inputs:
WACC (rows): Base WACC ± 2% in 0.5% increments (7 rows) Terminal Growth Rate (columns): 1.5% to 4.0% in 0.5% increments (6 columns)
Each cell = implied share price at that WACC/growth combination. Highlight the base case cell and the current market price for reference.
Also show a secondary sensitivity: Revenue Growth vs FCF Margin if data supports it.
If consensus estimates are available (see ../data-access.md Section 3):
If consensus data is not available, skip this check.
Flag any issues:
Challenge your own assumptions — don't anchor to the current price:
Save to reports/{TICKER}_dcf.html using the HTML report template from ../design-system.md. Write the full analysis as styled HTML with the design system CSS inlined. This is the final deliverable — no intermediate markdown step needed.
Structure the report with these sections:
<h1>{Company Name} ({TICKER}) — DCF Valuation</h1>
<p>Generated: {date}</p>
<h2>Summary</h2>
<table>
| Metric | Value |
| Current Price | $XXX |
| Implied Share Price | $XXX |
| Upside / Downside | +X.X% / -X.X% |
| WACC | X.X% |
| Terminal Growth | X.X% |
| Terminal Value % of Total | XX% |
</table>
<h2>WACC Calculation</h2>
<table>
| Component | Value | Source |
| Risk-Free Rate | X.X% | FRED 10Y Treasury |
| Equity Risk Premium | 5.5% | Standard assumption |
| Beta | X.XX | Market data |
| Cost of Equity | X.X% | CAPM |
| Cost of Debt (after-tax) | X.X% | Interest/Debt × (1-t) |
| Equity Weight | XX% | Market cap |
| Debt Weight | XX% | Total debt |
| **WACC** | **X.X%** | |
</table>
<h2>Historical Free Cash Flow (8 Quarters)</h2>
<table>
| Metric | Q1 | Q2 | ... | Q8 |
{OCF, CapEx, FCF, FCF Margin — with Daloopa citations}
</table>
<h2>FCF Projections (5 Years)</h2>
<table>
| Metric | Year 1 | Year 2 | Year 3 | Year 4 | Year 5 |
{Revenue, FCF Margin, FCF — with assumptions noted}
</table>
<h2>Valuation Bridge</h2>
<table>
| Component | Value |
| PV of Projected FCFs | $XXX |
| PV of Terminal Value | $XXX |
| Enterprise Value | $XXX |
| Less: Net Debt | ($XXX) |
| Equity Value | $XXX |
| Shares Outstanding | XXX |
| **Implied Share Price** | **$XXX** |
</table>
<h2>Sensitivity Table: WACC vs Terminal Growth</h2>
<table>
| WACC \ Growth | 1.5% | 2.0% | 2.5% | 3.0% | 3.5% | 4.0% |
{matrix of implied share prices, base case bolded}
</table>
<p>Current market price: $XXX for reference.</p>
<h2>Key Assumptions & Risks</h2>
<ul>{List all key assumptions and what could invalidate them}</ul>
<h2>Sanity Checks</h2>
<ul>{Implied multiples vs historical, terminal value concentration, etc.}</ul>All financial figures must use Daloopa citation format: <a href="https://daloopa.com/src/{fundamental_id}">$X.XX million</a>
Tell the user where the HTML report was saved.
Summarize: implied price vs current price, key upside/downside drivers, and the biggest sensitivity.
© daloopa, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in .claude/skills/dcf of daloopa/investing.
Open the folder on GitHubat commit e2dd01d
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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Dcf this skilldaloopa/investing | 489 | — | ~2.5k | Automated safety check: Pass | Apache-2.0 | |
| Creating Financial ModelsChen-zexi/open-ptc-agent | 729 | 4 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Equity Researcherlzwme/finance-quant-skills | 435 | 1 repos | ~4.9k | Automated safety check: Pass | None | |
| Equity ResearchrollingSirius/equity-research-skill | 452 | — | ~1.5k | Automated safety check: Pass | MIT | |
| SaaS Metrics Coachrongxinzy/RongxinAI | 154 | 2 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Startup Financial Modelingnicepkg/auto-company | 192 | 12 repos | ~2.8k | Automated safety check: Pass | None |
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
lzwme/finance-quant-skills
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rollingSirius/equity-research-skill
撰写机构级个股投资研究报告(二级市场深度研究)。Use whenever the user wants to research, analyze, or value a specific publicly-traded stock — e.g.
rongxinzy/RongxinAI
SaaS financial health advisor. An agent skill from rongxinzy/RongxinAI.
nicepkg/auto-company
This skill should be used when the user asks to "create financial projections", "build a financial model", "forecast revenue", "calculate burn rate", "estimate runway", "model cash flow", or…
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Categories
Discounted cash flow valuation with sensitivity analysis. An agent skill from daloopa/investing. Dcf is an agent skill from daloopa/investing.
Dcf fits situations like: tasks that involve Financial modeling.
Run `npx skills add daloopa/investing --skill dcf -a claude-code`. Or copy the skill folder (.claude/skills/dcf in daloopa/investing) into .claude/skills/dcf in your project. Claude Code loads it when a task matches its description.
Run `npx skills add daloopa/investing --skill dcf -a codex`. Or copy the skill folder (.claude/skills/dcf in daloopa/investing) into .agents/skills/dcf in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add daloopa/investing --skill 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/dcf, .gemini/skills/dcf, .github/skills/dcf and .opencode/skills/dcf in your project.
SKILL.md names no scripts, command-line tools or credentials: Dcf is instructions for the agent only.
SKILL.md names 1 domain. In commands or code: daloopa.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.
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.
Dcf is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.5k tokens (SKILL.md is roughly 9.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Dcf: Creating Financial Models (Chen-zexi/open-ptc-agent, 729 stars), Equity Researcher (lzwme/finance-quant-skills, 435 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.
daloopa (a GitHub organization) maintains it in daloopa/investing, which has 489 GitHub stars. The repository holds 22 skills in this directory. The repository was last updated on October 7, 2026.
Source: daloopa/investing on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.