/fundamentals

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.

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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

1. **Positive Net Income** - Company is profitable 2. **Positive ROA** - Assets are generating returns 3. **Positive Operating Cash Flow** - Company generates cash from operations 4. **Cash Flow > Net Income** - High-quality earnings (cash exceeds accounting profit) 5. **Lower Long-Term Debt** - Decreasing leverage (improving financial position) 6. **Higher Current Ratio** - Improving liquidity 7. **No New Shares Issued** - No dilution (or share buybacks) 8. **Higher Gross Margin** - Improving profitability efficiency 9. **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.