Security audit
Security checks for vulnerabilities and agentic risk
This is a static reference skill for data trimming, and its executable script only prints guidance text.
Review the examples before applying them to real files or databases, because some displayed SQL and sed examples would modify data if copied and run. The skill itself does not perform those modifications automatically.
The description says 'Use when cleaning text data, removing noise, or preparing datasets by trimming unwanted elements,' which is a wide natural-language trigger covering many common requests. It does not define clear boundaries or exclusion conditions, so the skill may be invoked for general data-cleaning tasks rather than specifically trimming-focused ones.
Output size or generation rate is not bounded. Unbounded output enables denial-of-service through resource exhaustion, log flooding, or context-window stuffing.
Best Practices:
1. Visualize before trimming (histogram, box plot)
2. Document trimming criteria and how many removed
3. Compare results with and without trimming
4. Consider: Are "outliers" actually valid data?
5. Domain knowledge > statistical rules
EOF
The 'When to Use' bullets enumerate several broad cleanup contexts, including text normalization, database cleanup, and signal noise removal, without stating when the skill should not be used. For markdown skill descriptions, missing specificity on trigger scope can cause unintended invocation overlap with more specialized cleaning or preprocessing skills.
No suspicious patterns detected.