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.
Install via CLI
openskills install staskh/trading_skills---
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.
```bash
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
```bash
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.No comments yet. Be the first to comment!