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金融数据清洗与异常检测工具，提供缺失值处理、去重、异常值检测、数据标准化等功能。当用户需要对原始金融数据进行预处理时使用。
Passed 22 of 22 test cases with the skill, and 21 of 22 without it.
1 fixed21 passed either way0 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
A test case the skill fixed. Same model, same prompt, with and without the skill.
In a cross-sectional snapshot of 1000 stocks at a single point in time, 5 stocks are missing market cap data. The sector distribution is verified uniform and stationary across the universe. What static central tendency metric imputes missing values based on average cross-sectional level?
| Checked | Without skill | With skill |
|---|---|---|
| Recommends mean or sector-median imputation | Missed | Passed |
The instructions your model reads when the skill loads.
数据清洗与异常检测 Skill。
test cases passed, vs 21 / 22 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.