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Us Value Investing Framework

US stock valuation model skill (English-first + 中文) based on financial report data. Use when you need to apply explicit rules: ROE > 15% for 3+ years, debt ratio < 50%, free cash flow > 80% of net income, moat assessment (brand/network effect/cost advantage), then output investment rating (A/B/C/D) with reasons.

dvcrn Updated 32 repo stars
AI & ML

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US Stock Valuation Model - Value Investing Framework (EN + 中文)

This skill is an explicit rule-based value model focused on US stocks.

Input

Company financial report data (structured JSON), including:

  • 3+ years of ROE
  • Debt ratio
  • Free cash flow and net income
  • Moat assessment: brand / network effect / cost advantage

Use the bundled template: references/input-template.json.

Decision Rules (strict)

  1. ROE rule: ROE > 15% for at least 3 consecutive years
  2. Leverage rule: Debt ratio < 50%
  3. Cash conversion rule: Free cash flow > 80% of net income
  4. Moat rule: evaluate brand/network effect/cost advantage

Output

  • Investment rating: A / B / C / D
  • Reasons (pass/fail explanation per rule)
  • Bilingual summary (EN main + 中文摘要)

Run

python3 scripts/evaluate_company.py \
  --input references/input-template.json \
  --out .state/eval.json \
  --markdown .state/eval.md

Rating policy

  • A: all 4 rules pass
  • B: 3 rules pass
  • C: 2 rules pass
  • D: 0-1 rule pass

Resources

  • scripts/evaluate_company.py: deterministic evaluator
  • references/input-template.json: input schema example

dvcrn/openclaw-skills-marketplace/tree/main/plugins/spyfree--us-value-investing-framework/skills/us-value-investing-framework commit 777f8a11ae

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npx skillmds@latest add dvcrn/us-value-investing-framework