A comprehensive research tool for searching millions of academic papers and generating automated literature reviews without an API key.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install academic-research
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 academic-research 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 Academic Research?
The Academic Research skill provides a robust interface for interacting with the OpenAlex API, granting access to a massive database of over 250 million scholarly works. This skill is a vital addition to Openclaw Skills, enabling researchers and developers to perform complex academic queries, fetch detailed metadata, and locate open-access full-text documents instantly without the need for authentication or API keys.
Designed for technical users, this skill excels at synthesizing vast amounts of academic data into actionable insights. It bridges the gap between raw scholarly data and structured knowledge, allowing AI agents to perform high-level research tasks such as citation analysis and thematic synthesis with minimal overhead.
Academic Research Use Cases
- Automating the literature review process for new academic or technical projects.
- Tracking the citation impact and influence of specific researchers or papers.
- Gathering verified scholarly references to support technical documentation.
- Identifying emerging trends through thematic clustering of recent publications.
- Programmatically extracting paper metadata for data analysis and visualization.
How Academic Research Works
- The skill receives a query through specific Python scripts for either search or literature review tasks.
- It interfaces with the OpenAlex API to retrieve metadata for relevant academic works based on topic, author, or DOI.
- The system applies filters for publication year, relevance, or citation count as specified by the user.
- For literature reviews, the skill performs deduplication and thematic analysis to group related papers.
- The final output is generated in structured Markdown or JSON, providing a clear summary of findings.
Academic Research Setup
To integrate this capability into your environment, ensure Python 3 is available. This Openclaw Skills component requires no external API keys for standard operation.
# Search for papers by topic
python3 scripts/scholar-search.py search "transformer architectures" --limit 10
# Run a full literature review synthesis
python3 scripts/literature-review.py "query topic" --papers 20 --output review.md
Academic Research Data Schema & Taxonomy
The skill organizes academic data into a structured format for easy parsing. Each paper entry includes the following metadata taxonomy:
| Property | Detail |
|---|---|
| Title | Full title and publication year |
| Authors | Primary contributors (up to 5 listed) |
| Abstract | Text summary of the research (when available) |
| Citations | Total citation count for impact assessment |
| DOI | Unique Digital Object Identifier |
| OA URL | Direct link to Open Access versions |
| Source | Original journal, conference, or venue |
Academic Research Advanced Features
- Bi-directional citation analysis to explore both references and future citations.
- Deep Read mode for simultaneous fetching of abstracts and available full-text URLs.
- Automated thematic clustering to identify core research themes in literature reviews.
- Local caching mechanism in
/tmp/litreview_cache/to optimize performance and minimize API calls. - Native JSON output support for seamless data piping between different Openclaw Skills.
SKILL.md
Loading
Related Openclaw Skills
Dutch News Interlinear Translator
A specialized linguistic tool that translates Dutch news articles into English using a sentence-by-sentence interlinear format.
Budget Tracker
A financial management and safety net skill for autonomous agents to track expenses, set spending limits, and prevent overspending.
Semantic Paper Radar
An AI-powered research discovery engine that synthesizes academic literature into structured reading lists and research maps.
Multi-Source Intel Radar
A high-signal information filtering system that transforms noisy social feeds from YouTube, X, Reddit, and WeChat into actionable founder-grade intelligence.
AI Income Agent
An autonomous system designed to transform OpenClaw agents into compounding revenue engines through skill sales, bounties, and affiliate marketing.
AI Productivity Audit
A professional-grade analyzer that audits your AI software subscriptions to calculate ROI, identify redundancies, and surface critical workflow gaps.
Featured*
