An advanced research tool that compares up to five academic papers side-by-side using DOIs, URLs, or PDF files to identify research gaps and methodology differences.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install paper-compare
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 paper-compare 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 Paper Compare?
Paper Compare is a specialized utility designed for academic rigor, enabling AI agents to perform deep comparative analysis of research documents. It synthesizes complex information into actionable insights by evaluating papers across ten critical dimensions, including methodology, results, and limitations. This capability within the ecosystem of Openclaw Skills allows researchers and developers to quickly grasp the nuances between competing approaches or track the evolution of a specific technology over time.
By leveraging APIs like Semantic Scholar and Crossref, Paper Compare provides more than just summaries; it offers a quality-scored assessment of each paper's impact and reliability. Whether you are conducting a literature review or selecting the best algorithm for a project, this skill provides the structured framework necessary for high-level technical decision-making.
Paper Compare Use Cases
- Comparing different methodologies used to solve the same research problem.
- Tracking the evolution of State-of-the-Art (SOTA) performance across multiple years.
- Identifying research gaps and unexplored directions in a specific scientific niche.
- Evaluating the trade-offs between competing approaches to choose the best implementation strategy.
- Summarizing a single complex paper into a structured format for quick ingestion.
How Paper Compare Works
- Interpret: The agent identifies the specific papers provided via DOIs, URLs, or file uploads and clarifies the user's research goal.
- Retrieve: It fetches metadata, abstracts, and full texts from sources like arXiv, IEEE, and PubMed using integrated web search and fetch tools.
- Analyze: The skill extracts data for 10 specific dimensions, including the research question, dataset used, and key findings.
- Synthesize: It builds a narrative comparison and a structured table, scoring each paper based on venue prestige and citation counts.
- Validate: The agent delivers a final verdict with a decision matrix to help the user choose the most relevant paper for their specific objective.
Paper Compare Setup
To integrate this functionality into your environment, ensure that your agent has access to the required dependency skills. This skill for Openclaw Skills utilizes the existing PDF extraction and web retrieval protocols to process paper data.
# Ensure the following dependencies are active in your Openclaw Skills configuration:
# - pdf (for local file extraction)
# - web_search (for finding papers by query)
# - web_fetch (for retrieving metadata from URLs)
Paper Compare Data Schema & Taxonomy
Paper Compare organizes research data into a strictly defined schema to ensure consistency across different analysis sessions. Findings are often persisted in a local history file for future reference.
| Component | Details |
|---|---|
| Core Dimensions | 10 fields: Title, Authors, Year, Venue, Research Question, Methodology, Dataset, Results, Limitations, Code/Data. |
| Quality Score | A weighted star rating based on Venue Quality, Citation Count, and Artifact (Code/Data) availability. |
| Verdict Matrix | A logical mapping of user needs to specific paper recommendations. |
| History Log | JSON-formatted storage located at memory/paper-compare-history.json containing past comparison goals and results. |
Paper Compare Advanced Features
- Multi-Source Mixed Input: Simultaneously compare papers provided via different formats, such as one DOI, one arXiv URL, and one uploaded PDF.
- Quality Assessment Framework: Automatically ranks papers using a 3-tier venue quality system and real-time citation data from Semantic Scholar.
- Automated Research Gap Analysis: Specifically identifies what is missing across a cluster of papers to suggest original research opportunities.
- Structured Decision Matrix: Generates a 'If You Need X, Choose Paper Y' table to expedite implementation decisions.
- Persistence and Memory: Saves user goals and comparison outcomes to JSON to enable context-aware research sessions in the future.
SKILL.md
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