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Filter and screen stocks by financial metrics like P/E ratio, market cap, dividend yield, and growth rates. Analyze and compare stocks from CSV data.
Passed 23 of 23 test cases with the skill, and 7 of 23 without it.
and 18 more in the full report
16 fixed7 passed either way0 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 16 test cases the skill fixed. Same model, same prompt, with and without the skill.
Write a shell command to screen stocks in `market_data.csv` using the stock screening CLI script for maximum P/E ratio of 20 and minimum dividend yield of 2.0. Rather than custom python, use the direct command line interface flags.
| Checked | Without skill | With skill |
|---|---|---|
| Includes --input market_data.csv in the CLI command | Passed | Passed |
| Uses --pe-max 20 | Missed | Passed |
| Includes min dividend threshold of 2.0 via CLI options | Passed | Passed |
The instructions your model reads when the skill loads.
Filter stocks by financial metrics and perform comparative analysis.
from stock_screener import StockScreener
screener = StockScreener()
# Load stock data
screener.load_csv("stocks.csv")
# Apply filters
results = screener.filter(
pe_ratio=(0, 20),
market_cap_min=1e9,
dividend_yield_min=2.0
)
print(results)
# Basic screening
python stock_screener.py --input stocks.csv --pe-max 20 --div-min 2.0
# Multiple filters
test cases passed, vs 7 / 23 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.