NSFC申请书文献检索与引用生成。使用OpenAlex API免费搜索学术文献,使用wenxian生成标准引用格式。
npx skills add https://github.com/njzjz/nsfc-agent-skills --skill nsfc-literature
脚本:scripts/search_literature.py
基本用法:
# 搜索关键词,按引用数排序
uv run scripts/search_literature.py "machine learning potential" --limit 20 --sort cited_by_count
# 搜索近3年的文献
uv run scripts/search_literature.py "deep learning molecular dynamics" --year-from 2023
# 按发表日期排序(找最新文献)
uv run scripts/search_literature.py "neural network force field" --sort publication_date
# 紧凑输出(每篇一行)
uv run scripts/search_literature.py "density functional theory" --compact
返回信息:标题、作者、期刊、年份、DOI、引用数、摘要
搜索策略建议:
wenxian 是一个学术引用生成工具,支持从 DOI、PMID、arXiv ID 等标识符生成标准引用格式。
脚本:scripts/generate_references.py
用法:
# 从DOI列表文件生成BibTeX引用
uv run scripts/generate_references.py refs.txt --format bibtex
# 生成纯文本引用
uv run scripts/generate_references.py refs.txt --format text
# 输出到文件
uv run scripts/generate_references.py refs.txt --format bibtex --output refs.bib
refs.txt 格式(每行一个标识符):
10.1103/PhysRevLett.120.143001
10.1038/s41586-020-2242-8
arXiv:2304.09423
NSFC申请书通常使用编号引用格式 [1], [2], ...
格式示例:
[1] 作者1, 作者2, 等. 标题. 期刊, 卷(期): 起始页-结束页, 年份.
[2] Author1, Author2, et al. Title. Journal, Volume(Issue): Pages, Year.
注意:
1. 确定研究方向和关键词
↓
2. 用 search_literature.py 搜索相关文献
↓
3. 筛选 ~30 条最相关的文献
- 高引经典 + 近年前沿 + 自己的工作
↓
4. 收集所有 DOI,写入 refs.txt
↓
5. 用 generate_references.py 生成标准引用
↓
6. 检查格式统一性
↓
7. 确认没有遗漏关键文献
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Take njzjz/nsfc-literature from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.