Create publication-quality visualizations from CSV/TSV/Excel data using Python
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
The workflow reads and processes user-provided/tabular data files via qsv commands like `mcp__qsv__qsv_stats`, `mcp__qsv__qsv_frequency`, and `mcp__qsv__qsv_slice`, so outsider-authored free text in the uploaded dataset is ingested directly at runtime.
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If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.