# Fundamentals

> 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.

- Skill: `staskh/fundamentals` (Agent Skill, multi-file: 3 files)
- Install (CLI): `npx skillmds@latest add staskh/fundamentals`
- Raw SKILL.md: https://api.skillmd.com/api/skills/staskh/fundamentals/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Finance & Business
- Author: staskh (https://skillmd.com/u/staskh)
- Updated: 2026-09-10
- Page: https://skillmd.com/skills/staskh/fundamentals

---


# 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.