Search and progressively read open-access academic papers through DeepXiv. Use when the user wants layered paper access, section-level reading, trending papers, or DeepXiv-backed literature retrieval.
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Low
Low-risk findings worth noting
Low
Low-risk findings.
1 low severity finding. Worth noting, but not necessarily harmful.
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.
Outsider free text can enter the LLM context via DeepXiv’s runtime retrieval of paper content/sections from external sources (e.g., arXiv/Semantic Scholar/web) when the skill runs `python3 "$DEEPXIV_FETCHER" paper-brief/paper-head/paper-section/trending/wsearch/sc`, which then feeds the fetched text into the agent for summarization.
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