Agent skill

baidu-scholar-guide

Using Baidu Scholar for Chinese and English academic literature search

brycew6m4,252★ · +31/wk · 3 repos on radarProfile →
claude-codeNOASSERTION
Install
npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill baidu-scholar-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: 6 KB
Bundled scripts: none
Path: skills/43-wentorai-research-plugins/skills/literature/search/baidu-scholar-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

# Baidu Scholar Guide ## Overview Baidu Scholar (百度学术, xueshu.baidu.com) is one of the largest academic search engines with particular strength in indexing Chinese-language scholarly publications. For researchers working with Chinese academic literature—or conducting bilingual research that spans both English and Chinese sources—Baidu Scholar provides access to content that is often underrepresent

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

Using Baidu Scholar for Chinese and English academic literature search

How do I install it?

Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill baidu-scholar-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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