Agent skill

bibliometrix-guide

Perform science mapping and bibliometric analysis with R bibliometrix

brycew6m4,252★ · +31/wk · 3 repos on radarProfile →
claude-codeNOASSERTION
Install
npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill bibliometrix-guide --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 5 KB
Bundled scripts: none
Path: skills/43-wentorai-research-plugins/skills/literature/metadata/bibliometrix-guide/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 3,244
Language: Stata
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Bibliometrix Guide ## Overview Bibliometrix is an R package for comprehensive science mapping and bibliometric analysis. It imports data from Scopus, Web of Science, PubMed, and other databases, then performs co-citation analysis, keyword co-occurrence mapping, collaboration networks, thematic evolution tracking, and more. Includes Biblioshiny — a Shiny-based web interface for no-code analysis.

More from Auto-Empirical-Research-Skills
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About this skill
What does the bibliometrix-guide skill do?

Perform science mapping and bibliometric analysis with R bibliometrix

How do I install it?

Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill bibliometrix-guide --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From brycewang-stanford/Auto-Empirical-Research-Skills, a repository with 3,244 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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