Use when identifying seminal papers in a research field, mapping research lineage and intellectual heritage, discovering related work through reference tracking, or finding potential collaborators through co-citation analysis. Maps citation networks to trace research evolution, identify influential papers, and discover hidden connections in scientific literature. Supports systematic reviews, bibliometric analysis, and research planning through comprehensive citation tracking.
83
78%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Advisory
Suggest reviewing before use
Optimize this skill with Tessl
npx tessl skill review --optimize ./scientific-skills/Evidence insights/citation-chasing-mapping/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: 0.80). The skill clearly fetches and ingests external content from the public Semantic Scholar API (see scripts/main.py: SemanticScholarClient.BASE_URL = "https://api.semanticscholar.org/graph/v1" and calls like search_paper/get_citations/get_references), and that untrusted third‑party content (paper metadata and citations) is read and used to drive multi‑hop traversal and subsequent analysis, so it can materially influence the agent's actions.
ca9aaa4
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