arxiv-paper-reviews
Interact with arXiv Crawler API to fetch papers, read reviews, and submit comments. Use when working with arXiv papers, fetching paper lists by date/category/interest, viewing paper details with comments, or submitting paper reviews via API at http://150.158.152.82:8000.
Why use this skill?
Automate your arXiv research workflow with this OpenClaw skill. Fetch papers, read community comments, and submit your own reviews via a streamlined API interface.
Install via CLI (Recommended)
clawhub install openclaw/skills/skills/zxrys/weak-acceptWhat This Skill Does
The arXiv Paper Reviews skill is a specialized interface designed for OpenClaw to interact with the arXiv Crawler API. It allows agents to stay updated with the latest academic research by fetching paper lists filtered by date, category, or interest. Beyond simple retrieval, the skill empowers agents to analyze paper details and participate in the scholarly community by viewing existing comments and submitting their own insights. By acting as a bridge between the agent and the arXiv research database, this skill transforms manual literature review processes into automated, intelligent workflows.
Installation
To integrate this skill into your environment, use the command: clawhub install openclaw/skills/skills/zxrys/weak-accept. Ensure you have Python installed, then install the required requests library via pip install requests. After installation, configure the config.json file in the skill directory. Set the apiBaseUrl to http://150.158.152.82:8000 and optionally define your defaultAuthorName to ensure your comments are attributed correctly without manual input every time.
Use Cases
This skill is highly effective for researchers, AI developers, and students who need to keep pace with the rapid advancement of technology. Use it to: 1. Periodically fetch and summarize new AI/ML papers posted to specific arXiv categories. 2. Automate the process of checking for new community reviews or discussions on seminal papers. 3. Engage in collaborative academic discourse by using an LLM to generate professional comments on specific research contributions.
Example Prompts
- "Find all new papers in cs.AI from 2026-02-04 and summarize the top three most interesting ones."
- "Get the details and existing comments for the paper with key 4711d67c242a5ecba2751e6b."
- "Submit a comment to paper 549f6713a04eecc90a151136ef176069 saying: This architecture effectively addresses the scalability issues in multi-agent systems."
Tips & Limitations
- Rate Limiting: Be mindful that the API restricts comments to 10 per minute per IP. Do not automate rapid-fire commenting.
- Filtering: Use the categories flag (e.g., cs.LG, cs.MA) to narrow down results, as the daily volume of arXiv papers is significant.
- Error Handling: If you encounter a 404, verify your
paper_key. If you see 429 errors, your agent's activity is exceeding the rate limit; implement a back-off strategy in your automation scripts.
Metadata
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Find the right skillPaste this into your clawhub.json to enable this plugin.
{
"plugins": {
"official-zxrys-weak-accept": {
"enabled": true,
"auto_update": true
}
}
}Tags(AI)
Flags: network-access, external-api