An AI-powered academic search tool that enables researchers to discover papers, filter by author or date, and extract detailed scholarly metadata.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install google-scholar-search-skill
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install google-scholar-search-skill using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Google Scholar Search?
Google Scholar Search is a specialized tool designed to bridge the gap between AI agents and the world's largest repository of scholarly literature. By utilizing this component of Openclaw Skills, developers and researchers can programmatically query academic databases to find peer-reviewed papers, patents, and citations without the need for manual searching.
This skill is particularly valuable for users who require a high-fidelity feed of academic data for literature reviews, competitive analysis, or automated research pipelines. It provides a structured interface to Google Scholar, transforming web-based search results into actionable data points like abstracts, author affiliations, and citation counts.
Google Scholar Search Use Cases
- Automating the discovery of new research papers in specific scientific domains.
- Performing comprehensive literature reviews for academic projects or industry R&D.
- Tracking the publication history and citation metrics of specific researchers.
- Building datasets of academic abstracts for natural language processing and data analysis tasks.
How Google Scholar Search Works
- The user triggers the skill using the /google-scholar-search command followed by search parameters.
- The skill parses the query to determine whether to perform a keyword search, an advanced filter search, or an author profile lookup.
- It executes a targeted web scraping process to retrieve data directly from the Google Scholar interface.
- The raw data is parsed to extract metadata such as titles, authors, publication years, and direct document links.
- The final output is delivered to the user in a clean console format or saved as a structured JSON file for further use within Openclaw Skills workflows.
Google Scholar Search Setup
To integrate this skill into your environment, use the standard installation command for your agent:
/skill-install google-scholar-search
Once installed, verify the connection by running a basic search query:
/google-scholar-search --query "neural networks" --results 3
Google Scholar Search Data Schema & Taxonomy
The skill organizes its output into a consistent format, whether viewing in the console or exporting to JSON. The following table describes the primary data points captured:
| Attribute | Description | Data Type |
|---|---|---|
| title | The full title of the academic paper | String |
| authors | A list of contributing researchers | String |
| abstract | A summary snippet of the paper's content | String |
| link | Direct URL to the paper's landing page or PDF | URL |
| citations | Total number of citations listed on Google Scholar | Integer |
| year | The year the research was published | Integer |
Google Scholar Search Advanced Features
- Advanced Filtering: Narrow down search results by specifying both the author and a precise year range (e.g., 2018 to 2023).
- Author Intelligence: Retrieve deep-dive profiles including a researcher's interests, institutional affiliation, and their most cited works.
- JSON Interoperability: Seamlessly export any search result or author profile into JSON format for integration with data visualization or analysis tools.
- Multi-Skill Synergy: Works in tandem with other Openclaw Skills like PubMed or Sci-Hub to create a complete academic research ecosystem.
SKILL.md
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