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paper-search
Primary skill for searching, retrieving, and reading academic papers from arXiv.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
菜单
Primary skill for searching, retrieving, and reading academic papers from arXiv.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Use only when the user explicitly requests comprehensive multi-source research, such as "research X", "deep dive into X", "comprehensive review of X", "systematic comparison between X and Y", "investigate the landscape of X", or Chinese equivalents like "调研一下X", "深入研究X", "全面对比X与Y", "X的详细综述", "深度调查X". Do NOT trigger for simple questions, how-to guidance, ordinary recommendations, or content creation merely because research could improve the answer. Follow the source priorities supplied by the system and the user.
Use this skill when the user requests to review, analyze, critique, or summarize a SINGLE academic paper, general document, internal report, proposal, or web article. Supports comprehensive structured reviews covering methodology/logic assessment, strengths, weaknesses, and constructive feedback. Retrieves content using native tools (`url_fetch`, `kb_search`, `arxiv_search`) and outputs the analysis directly in the chat.
Use this skill when the user wants a systematic review, thematic synthesis, or cross-document analysis across multiple academic papers OR provided general documents (reports, internal memos, web articles). Retrieves sources via arXiv, internal Knowledge Base (KB), or direct URLs. Analyzes the content within the current context and outputs a fully structured synthesis report directly in the chat.
Use this skill for scientific literature search, evidence retrieval, paper metadata screening, and cited research synthesis with Sciverse. This LazyLLM-adapted version supports SciverseSearch search, meta_search, meta_catalog, and get_content only; it does not assume full Sciverse MCP resource or attachment APIs are available.
Build and review UI components for robust accessibility and runtime resilience, including semantic structure, keyboard support, loading and error states, retry flows, and predictable async behavior.
Implement or refactor UI forms with defense-in-depth validation, safe input handling, reliable submission behavior, and privacy-aware error handling. Use when building login, registration, profile, payment, admin, or file-upload forms.
| name | paper-search |
| description | Primary skill for searching, retrieving, and reading academic papers from arXiv. |
This skill provides a streamlined workflow for searching and reading academic papers from arXiv. You must default to using the system's native tools for searching and reading. Use local scripts only for specific formatting tasks (like BibTeX) or as a fallback mechanism.
arxiv_search (Primary): Use this first for querying papers by keyword, author, or ID.url_fetch (Primary): Use this to read abstracts and full-text HTML papers.run_script (Optional/Fallback): Use this only to generate BibTeX citations OR if arxiv_search fails to return valid results. This tool returns a dictionary.Primary Method:
When the user asks for papers on a topic, immediately call the native arxiv_search tool with appropriate keywords.
arxiv_search(query="large language models")Fallback Method (If arxiv_search fails or returns empty/errors):
If the native tool malfunctions, use run_script to execute the fallback Python search script.
{
"name": "paper-search",
"rel_path": "scripts/search_arxiv.py",
"args": ["<your_search_query>"]
}
Once you have identified target arXiv IDs, retrieve their content using url_fetch.
https://arxiv.org/abs/<arxiv_id>url_fetch(url="https://arxiv.org/abs/2402.03300")https://ar5iv.labs.arxiv.org/html/<arxiv_id>url_fetch(url="https://ar5iv.labs.arxiv.org/html/2402.03300")If the user specifically asks for BibTeX citations, the native tools might not format it correctly. Use run_script to execute the BibTeX generator.
{
"name": "paper-search",
"rel_path": "scripts/get_bibtex.py",
"args": ["<arxiv_id>"]
}
Example <arxiv_id>: 2402.03300
arxiv_search before resorting to scripts/search_arxiv.py.run_script, the args parameter MUST be a List of strings (List[str]).2402.03300 resolves to the latest version. Use unversioned IDs for lookups unless the user specifically requests an older version.