A specialized tool for interacting with the arXiv Crawler API to fetch academic papers, read community reviews, and submit comments.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install weak-accept
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 weak-accept 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 arXiv Paper Reviews?
The arXiv Paper Reviews skill is a robust integration designed for researchers and developers who need programmatic access to the arXiv repository. By utilizing the arXiv Crawler API, this skill enables users to filter academic literature by date, category, or specific interest levels. It serves as a bridge between high-level research data and automated workflows within Openclaw Skills, providing a structured way to stay updated on the latest scientific breakthroughs.
Beyond simple data retrieval, this skill facilitates academic engagement by allowing users to view and submit short-form reviews and comments. This creates a powerful environment for collaborative research, where AI agents can assist in summarizing complex papers and posting insights directly to the community platform.
arXiv Paper Reviews Use Cases
- Automating the discovery of new AI and machine learning papers published on specific dates.
- Building automated research feeds that filter arXiv papers based on community interest tags.
- Leveraging AI agents to read paper abstracts and generate preliminary peer reviews or summaries.
- Programmatically tracking discussions and comments on high-impact academic publications.
How arXiv Paper Reviews Works
- The skill connects to the arXiv Crawler API using a configured base URL and optional authentication key.
- Users provide search parameters such as category codes (e.g., cs.AI) or specific dates to retrieve a list of papers.
- The skill fetches detailed metadata and existing community comments for specific paper keys.
- For interactive workflows, the skill submits user-generated or agent-generated comments back to the API while respecting rate limits.
- The retrieved data can be passed to other components within Openclaw Skills for further processing or notification.
arXiv Paper Reviews Setup
To get started, ensure you have Python installed, then install the required requests library:
pip3 install requests
Next, configure your environment by creating a config.json file with your API details:
{
"apiBaseUrl": "http://150.158.152.82:8000",
"apiKey": "your_optional_key",
"defaultAuthorName": "your_name"
}
arXiv Paper Reviews Data Schema & Taxonomy
The skill organizes research data using a structured taxonomy to ensure compatibility with Openclaw Skills workflows:
| Parameter | Description | Constraints |
|---|---|---|
| paper_key | Unique identifier for a paper | Required for details/comments |
| categories | Subject area tags | e.g., cs.AI, cs.LG |
| date | Publication date | YYYY-MM-DD format |
| interest | Interest level filter | e.g., 'chosen' |
| content | Comment/Review text | 1-2000 characters |
| author_name | Display name for reviews | Max 64 characters |
arXiv Paper Reviews Advanced Features
- Rate limiting management ensuring no more than 10 comments per minute per IP to maintain API compliance.
- Support for complex multi-category filtering to narrow down research results effectively.
- Integration ready for cron-based automation to fetch and summarize daily paper updates.
- Seamless output piping for multi-agent collaboration within the broader Openclaw Skills ecosystem.
SKILL.md
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