fsi-fa-cmd-dcf
Build a DCF valuation model with comps-informed terminal multiples — usage: /dcf [company name or ticker]
Skill by d-wwei
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/d-wwei-fsi-fa-cmd-dcf
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
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Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/fsi-fa-cmd-dcf
What's inside
- Skill name
fsi-fa-cmd-dcf- Description
- Build a DCF valuation model with comps-informed terminal multiples — usage: /dcf [company name or ticker]
- License
- Apache-2.0
- Instructions
- 99 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# DCF Valuation Command Build an institutional-quality DCF model that uses comparable company analysis to inform valuation ranges. ## Workflow ### Step 1: Gather Company Information If a company name or ticker is provided, use it. Otherwise ask: - "What company would you like to value?" ### Step 2: Run Comparable Company Analysis **First, load the comps-analysis skill** to build trading comps: Use `skill: "comps-analysis"` to: 1. Identify 4-6 comparable public companies 2. Pull operating metrics (Revenue, EBITDA, margins, growth) 3. Pull valuation multiples (EV/Revenue, EV/EBITDA, P/E) 4. Calculate statistical summary (median, 25th/75th percentiles) **Key outputs to capture from comps:** - Median EV/EBITDA multiple → informs terminal value exit multiple - Median EV/Revenue multiple → sanity check on DCF output - Peer growth rates → benchmark for revenue projections - Peer margins → benchmark for margin assumptions ### Step 3: Build DCF Model **Load the dcf-model skill** to construct the valuation: Use `skill: "dcf-model"` to: 1. Gather historical financials and market data 2. Build revenue projections (Bear/Base/Bull cases) 3. Model operating expenses and FCF 4. Calculate WACC using CAPM 5. Discount cash flows and calculate terminal value 6. Bridge to equity value and implied share price **Use comps to inform DCF assumptions:** | Comps Output | DCF Input | |--------------|-----------| | Peer median EV/EBITDA | Terminal exit multiple range | | Peer 25th-75th EV/EBITDA | Sensitivity analysis range | | Peer median growth rate | Benchmark for revenue assumptions | | Peer median EBITDA margin | Target margin in terminal year | | Peer median P/E | Cross-check implied P/E from DCF | ### Step 4: Cross-Check Valuation After DCF is complete, validate: 1. **Implied EV/EBITDA** from DCF vs peer median - If DCF implies 25x but peers trade at 12x, investigate why 2. **Implied P/E** from DCF vs peer median 3. **Terminal value as % of EV** (should be 50-70%) 4. **Implied growth** embedded in valuation vs peer growth rates ### Step 5: Deliver Output Provide: 1. **Comps analysis spreadsheet** (.xlsx) with peer trading multiples 2. **DCF model** (.xlsx) with: - Bear/Base/Bull scenarios - Sensitivity tables (WACC vs Terminal Growth, etc.) - Valuation summary with implied upside/downside 3. **Summary** explaining: - Key valuation drivers - How comps informed the analysis - Risks and sensitivities to watch ## Example Output Summary ``` VALUATION SUMMARY: [Company] ([Ticker]) Comparable Companies Analysis: - Peer Group: [List of 4-6 comps] - Median EV/EBITDA: 12.5x (range: 10.2x - 15.8x) - Median EV/Revenue: 3.2x (range: 2.1x - 4.5x) DCF Valuation (Base Case): - Implied Share Price: $XX.XX - Current Price: $YY.YY - Implied Upside: +XX% Valuation Cross-Check: - DCF Implied EV/EBITDA: 13.2x (vs peer median 12.5x) - DCF Implied P/E: 22.4x (vs peer median 20.1x) - Terminal Value: 62% of EV (within normal range) Key Assumptions: - Revenue CAGR: X% (vs peer median X%) - Terminal EBITDA Margin: X% (vs peer median X%) - WACC: X.X% - Terminal Growth: X.X% ```
From d-wwei/openclaw-financial-services, Apache-2.0.
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Signals
- Stars
- 17
- Forks
- 4
- Open issues
- 0
- Last commit (this folder)
- Feb 25, 2026 (8 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- Apache-2.0
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
fsi-fa-cmd-dcf skill. Agent Mart. https://agentmart.dev/skills/d-wwei-fsi-fa-cmd-dcf (last updated 2026-10-24)