Trace citation neighborhoods around a focal paper into interpretable buckets.
npx skills add https://github.com/XWIlluDelu/agent-share --skill trace-citations
Please help me install this Agent Skill. Skill: trace-citations Source: https://github.com/XWIlluDelu/agent-share/tree/main/lib/trace-citations Command: npx skills add https://github.com/XWIlluDelu/agent-share --skill trace-citations
You need a structured view of how a specific research paper connects to prior work and later work, including which citations look influential, which are merely contextual, and which edges are weak signals.
Run: the AI assistant executes the trace-citations workflow for the paper title you specify and returns a JSON report with the citation buckets.
High-intent search queries and answers about installing and using this skill.
Citation tracing maps a research paper's lineage by fetching first-hop references and citations via Semantic Scholar, then bucketing them into foundations, direct descendants, and bridge nodes to reveal academic influence.
You categorize citations by scoring edges using influence, context, and intent signals, which separates strong foundations and direct descendants from mid-confidence bridge nodes and weak edges.
Yes, Semantic Scholar resolves the focal paper query and fetches bounded citations and references, enabling follow-up literature discovery through an optional second-hop expansion for stronger anchors.
Citation context and intent metadata improve influence analysis by providing interpretable signals that explain why specific edges are categorized as foundations, bridge nodes, or weak connections.
The literature mapping workflow fetches first-hop references and citations with bounded maxima, outputting a stable JSON envelope with workflow metadata and specific examined counts for the focal paper.
The best way to identify weak citation signals is to score edges using impact and context signals, grouping low-confidence connections into a distinct weak edges bucket within the output JSON envelope.
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