> guhaohao0991/PaperClaw
an OpenClaw skill that can generate paper search-review-critque expert-agent relevant to specific topics (we use Scientific ML and 3D geometry surrogate modeling as a demo).
curl "https://skillshub.wtf/guhaohao0991/PaperClaw/arxiv-search?format=md"> about
an OpenClaw skill that can generate paper search-review-critque expert-agent relevant to specific topics (we use Scientific ML and 3D geometry surrogate modeling as a demo).
> skills (6)
> arxiv-search
arxiv-search skill from guhaohao0991/PaperClaw
> daily-search
daily-search skill from guhaohao0991/PaperClaw
> paper-expert-generator
Generate a specialized domain-expert research agent modeled on PaperClaw architecture. Use this skill when a user wants to create an AI agent that can automatically search, filter, summarize, and evaluate academic papers in a specific research field. Trigger phrases include help me create a paper tracking agent for my field, I want an agent to monitor latest papers in bioinformatics, build me a paper review agent for computer vision, create a PaperClaw-style agent for my domain, generate a domai
> paper-review
paper-review skill from guhaohao0991/PaperClaw
> semantic-scholar
semantic-scholar skill from guhaohao0991/PaperClaw
> weekly-report
# Weekly Report Generation Skill ## 功能描述 基于本周评估的论文，生成每周精选报告，为精选论文创建独立知识库文档，并通过如流消息发送给指定用户。 ## 核心流程 ### 步骤1: 读取已评估论文数据 从 `evaluated_papers.json` 读取本周评估的论文： ```bash # 读取已评估论文列表 cat workspace/papers/evaluated_papers.json ``` ### 步骤2: 筛选本周论文并排序 ```python import json from datetime import datetime, timedelta # 读取已评估论文 with open('workspace/papers/evaluated_papers.json', 'r') as f: data = json.load(f) # 筛选本周论文（最近7天） week_start = datetime.now() - timedelta(days=7) week_papers = [ paper f