An AI-powered research discovery engine that synthesizes academic literature into structured reading lists and research maps.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install semantic-paper-radar
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 semantic-paper-radar 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 Semantic Paper Radar?
Semantic Paper Radar is a sophisticated literature discovery tool designed to streamline academic research across multiple repositories including arXiv, OpenAlex, and PubMed. By leveraging semantic search capabilities within Openclaw Skills, it helps researchers and developers identify foundational papers, track frontier developments, and map the evolution of specific technical or scientific domains.
This skill goes beyond simple keyword matching to understand natural-language intent. It allows users to categorize findings into foundational research, methodological shifts, and recent breakthroughs, providing a holistic view of the academic landscape in fields like AI, medicine, and engineering.
Semantic Paper Radar Use Cases
- Identifying foundational must-read papers for a new research domain.
- Mapping the lineage and evolution of specific technologies or scientific concepts.
- Generating curated, stratified reading lists for interdisciplinary topics.
- Tracking high-momentum preprints on arXiv to stay ahead of formal publications.
- Conducting deep-dive research into biomedical and clinical literature with specialized filters.
How Semantic Paper Radar Works
- Clarify query intent by defining topic, scope, time window, and discovery priority (foundational, frontier, or balanced).
- Run aggregated retrieval across OpenAlex (for peer-reviewed data) and arXiv (for preprints) using optimized Python scripts.
- Generate a synthesis report that stratifies findings based on citation momentum and publication date.
- Present results through a research map that includes academic timelines and recommended reading orders.
Semantic Paper Radar Setup
To integrate this capability into your Openclaw Skills workflow, ensure your environment has Python 3 and the necessary script dependencies. Use the following commands for literature retrieval:
# General domain search
python3 scripts/paper_radar.py search --query "YOUR_TOPIC" --max 40 --years 8
# Generate a balanced synthesis report
python3 scripts/paper_radar.py report --query "YOUR_TOPIC" --max 40 --years 8 --top 12 --mode balanced
# Export research map to clickable HTML
python3 scripts/paper_radar.py report --query "YOUR_TOPIC" --export-html
Semantic Paper Radar Data Schema & Taxonomy
The skill organizes research data into the following structure:
| Data Point | Description |
|---|---|
| Core Metadata | Title, DOI, Authors, and Publication Venue. |
| Tiered Classification | Stratification into 'Classic/Foundational', 'Evolutionary', and 'Recent Frontier'. |
| Academic Lineage | A chronological timeline of how the research topic has evolved. |
| Reading Priority | A 3-step recommended reading sequence for rapid domain onboarding. |
| Preprint Alerts | Explicit warnings for unreviewed biomedical preprints. |
Semantic Paper Radar Advanced Features
- Multi-source aggregation combining the authority of OpenAlex/PubMed with the speed of arXiv.
- Specialized biomedical mode for clinical research workflows.
- Interactive HTML export for visual exploration of research maps.
- Optional Google Scholar integration for secondary citation cross-checks and author authority verification.
- Natural language intent parsing to adjust the retrieval strategy between foundational theory and cutting-edge application.
SKILL.md
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