Li Xin

US Stock Valuation Model - Value Investing Framework / 美股估值模型-价值投资框架

Professionalv1.1.0
By Li XinUpdated 2026-05-112 versions · latest released 2026-02-22us-value-investing-framework@clawhub_spyfree/us-value-investing-framework
Finance#Investment#Financial#Stock

According to AlphaMoat, as of 2026-09, US Stock Valuation Model - Value Investing Framework / 美股估值模型-价值投资框架 has 4,208 downloads and 2 stars — ranked #2,373 of 5,078 AI skills overall, and #195 of 465 in Professional.

Installs
204
Downloads
4.2K
Stars
2
Overall Rank
#2,373
Top 47% overall · Top 42% in Professional
PlatformInstallsDownloadsStarsComments
ClawHub ↗1334.2K2-
SkillHub ↗2044.2K2—

Platforms count differently. AlphaMoat’s totals use the higher figure across platforms, not the sum.

What this skill does

Reads structured financial data and checks ROE, leverage, cash flow and moat conditions. It explains each pass or failure and returns a rating with a bilingual summary.

Profile published 2026-10-26

What you can do with it

  • Apply a consistent financial-report evaluation framework

When to use it

  • When structured financial data needs traceable scoring

Example prompts

Generated from the skill’s documentation as examples; not results of actual runs.

Explain the model’s rule-by-rule rating for this financial report

Requirements

Compiled from what the skill’s documentation declares; not verified by installing or running it.

Required command-line tools
python3

Monthly Trend

Installs204
121166210Current methodLegacy method2026-03 · Installs 180 (Legacy method)2026-05 · Installs 204 (Legacy method)2026-06 · Installs 127 (Legacy method)2026-07 · Installs 204 (Legacy method)2026-08 · Installs 133 (Legacy method)2026-09 · Installs 20426-0326-09
Downloads4.2K
2.3K3.3K4.4KCurrent methodLegacy method2026-03 · Downloads 2.4K (Legacy method)2026-05 · Downloads 3.1K (Legacy method)2026-06 · Downloads 3.4K (Legacy method)2026-07 · Downloads 3.8K (Legacy method)2026-08 · Downloads 4.0K (Legacy method)2026-09 · Downloads 4.2K26-0326-09
Stars2
122Current methodLegacy method2026-03 · Stars 1 (Legacy method)2026-05 · Stars 2 (Legacy method)2026-06 · Stars 2 (Legacy method)2026-07 · Stars 2 (Legacy method)2026-08 · Stars 2 (Legacy method)2026-09 · Stars 226-0326-09

From 2026-09 the figures use the current method (full catalog). Earlier months use the legacy method (only skills with installs, same-name skills merged). The two are not directly comparable, so the chart does not connect them or compute growth across them.

MonthDownloadsMoMStarsInstalls
2026-094.2K—2204
2026-08Legacy method4.0K+5.5%2133
2026-07Legacy method3.8K+11.4%2204
2026-06Legacy method3.4K+7.8%2127
2026-05Legacy method3.1K—2204
2026-03Legacy method2.4K—1180

SKILL.md (original)

The author’s original file, shown as plain text without edits or review by AlphaMoat. Links are not clickable; check commands before running them. Fetched 2026-10-23.

Show original (1.5 KB · ClawHub v1.1.0)
---
name: us-value-investing-framework
description: 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.
---

# 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

```bash
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
Other files archived by AlphaMoat (fetched selectively, may be incomplete)
  • references/input-template.json · 644 B
  • skill-card.md · 2.3 KB

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Data month: 2026-09 · Downloads, stars and installs are aggregated monthly from public skill registries (ClawHub, SkillHub). See methodology.