Agent Skills › staskh/trading_skills › fundamentals

fundamentals

GitHub

获取Yahoo Finance基本面数据，包括财务、收益和关键指标。支持计算Piotroski F-Score以评估公司财务健康度，涵盖9项标准及评分解读，辅助价值投资和财务强度分析。

.claude/skills/fundamentals/SKILL.md staskh/trading_skills

触发场景

查询财务数据获取收益信息查看关键指标计算Piotroski F-Score 评估财务健康度

安装

npx skills add staskh/trading_skills --skill fundamentals -g -y

更多选项

非标准路径

npx skills add https://github.com/staskh/trading_skills/tree/main/.claude/skills/fundamentals -g -y

不安装直接使用

npx skills use staskh/trading_skills@fundamentals

指定 Agent (Claude Code)

npx skills add staskh/trading_skills --skill fundamentals -a claude-code -g -y

安装 repo 全部 skill

npx skills add staskh/trading_skills --all -g -y

预览 repo 内 skill

npx skills add staskh/trading_skills --list

SKILL.md

Frontmatter

{
    "name": "fundamentals",
    "description": "Get fundamental financial data including financials, earnings, and key metrics. Use when user asks about financials, earnings, revenue, profit, balance sheet, income statement, or company fundamentals.",
    "dependencies": [
        "trading-skills"
    ]
}

Fundamentals

Fetch fundamental financial data from Yahoo Finance.

Instructions

Note: If uv is not installed or pyproject.toml is not found, replace uv run python with python in all commands below.

uv run python scripts/fundamentals.py SYMBOL [--type TYPE]

Arguments

SYMBOL - Ticker symbol
--type - Data type: all, financials, earnings, info (default: all)

Output

Returns JSON with:

info - Key metrics (market cap, PE, EPS, dividend, etc.)
financials - Recent quarterly/annual income statement data
earnings - Historical and estimated earnings

Present key metrics clearly. Compare actual vs estimated earnings if relevant.

Piotroski F-Score

Calculate Piotroski's F-Score to evaluate a company's financial strength using 9 fundamental criteria.

Instructions

uv run python scripts/piotroski.py SYMBOL

What is Piotroski F-Score?

Piotroski's F-Score is a fundamental analysis tool developed by Joseph Piotroski that evaluates a company's financial strength using 9 criteria. Each criterion scores 1 point if passed, 0 if failed, for a maximum score of 9.

The 9 Criteria

Positive Net Income - Company is profitable
Positive ROA - Assets are generating returns
Positive Operating Cash Flow - Company generates cash from operations
Cash Flow > Net Income - High-quality earnings (cash exceeds accounting profit)
Lower Long-Term Debt - Decreasing leverage (improving financial position)
Higher Current Ratio - Improving liquidity
No New Shares Issued - No dilution (or share buybacks)
Higher Gross Margin - Improving profitability efficiency
Higher Asset Turnover - More efficient use of assets

Score Interpretation

8-9: Excellent - Very strong financial health
6-7: Good - Strong financial health
4-5: Fair - Moderate financial health
0-3: Poor - Weak financial health

Output

Returns JSON with:

score - F-Score (0-9)
max_score - Maximum possible score (9)
criteria - Detailed breakdown of each criterion with pass/fail status and values
interpretation - Text description of financial health level
data_available - Boolean indicating if year-over-year comparison data is available for criteria 5-9

Implementation Details

Criteria 1-4 use quarterly financial data (most recent year)
Criteria 5-9 use annual financial data for year-over-year comparisons
Compares most recent fiscal year vs previous fiscal year

Use Cases

Use Piotroski F-Score when:

Evaluating fundamental financial strength
Screening for value stocks with improving fundamentals
Assessing financial health trends
Comparing financial strength across companies
Identifying companies with strong fundamentals but undervalued prices

Dependencies

pandas
yfinance

Timezone

All timestamps and time-based calculations must use the America/New_York timezone. All JSON output must include generated_at (NY time string) and data_delay fields.