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.
51
55%
Does it follow best practices?
Impact
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No eval scenarios have been run
Advisory
Suggest reviewing before use
Optimize this skill with Tessl
npx tessl skill review --optimize ./skills/skills-codex/deepxiv/SKILL.mdSecurity
1 medium severity finding. This skill can be installed but you should review these findings before use.
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.
Third-party content exposure detected (high risk: 0.85). 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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