据 AlphaMoat 统计,截至 2026-09,Academic Research Conflict 累计下载 1,227 次、获 0 个星标,在全部 5,078 个 AI 技能中排名第 4,923 位,在「专业领域」分类(465 个)中排名第 450 位。

累计安装

143

累计下载

1,227

星标

全站排名

#4,923

全站前 97% · 「专业领域」前 97%

平台	累计安装	累计下载	星标	评论
ClawHub ↗	22	932	-	-
SkillHub ↗	143	1,227	-	—

各平台的计数口径不同,统计时间不一致。

这个技能是做什么的

可返回论文标题、作者、摘要、引用数、DOI 和开放获取链接，并在可用时获取全文。综述由自动化流程综合生成，引用、摘要和综合结论必须对照原论文人工核验后再用于学术或专业交付。调用会向 OpenAlex/Unpaywall 等服务发送请求，可能附带写入的联系邮箱；结果会缓存到临时目录，也可能写入用户指定路径。Markdown 报告默认带有 Topanga 署名，分发前应检查署名与披露要求。文档所列命令需要 Python。

资料发布于 2026-10-29

可以用来做什么

按主题、作者或 DOI 查找学术论文
查看论文引用链和开放获取全文链接
生成按主题聚类并综合论文信息的综述草稿

什么时候用

需要学术论文发现或文献综述初稿时
可以核对论文来源、引用和结论时
允许相关 API 外联、缓存行为和指定路径文件写入时

示例提示词

以下是根据技能文档生成的示例,不代表实际运行结果。

为这个研究主题规划检索词和综述核验清单，要求逐条检查原论文与引用；不要调用学术 API 或写入文件。

月度数据趋势

累计下载1,227

星标-

2026-09 起统计方法调整:同名技能按作者分别统计,并覆盖全部技能。图中虚线为调整前的月份,与之后的数据不直接比较,也不计算跨越调整的增长。

月份	累计下载	环比	星标
2026-09	1,227	—	-
2026-08	1,005	+16.9%	-
2026-07	860	+37.8%	-
2026-06	624	+22.8%	-
2026-05	508	—	-
2026-03	282	—	-

SKILL.md 原文

以下是作者发布的原始文件,按纯文本显示,本站未做修改或审核;其中的链接不可点击,命令请核实后再运行。抓取于 2026-10-23。

2.7 KB · ClawHub v1.0.0

---
name: academic-research
version: 1.0.0
description: Search academic papers and conduct literature reviews using OpenAlex API (free, no key needed). Use when the user needs to find scholarly papers by topic/author/DOI, explore citation chains, get structured paper metadata (title, authors, abstract, citations, DOI, open access URL), fetch full text of open access papers, or conduct automated literature reviews with theme identification and synthesis. Triggers on requests involving academic search, paper lookup, citation analysis, literature review, research synthesis, or scholarly reference gathering.
---

# Academic Research

Search 250M+ academic works via OpenAlex. No API key required.

展开全部(共 82 行)

Built by [Topanga](https://topanga.ludwitt.com) — AI Research Consultant

## Quick Start

### Search papers by topic
```bash
python3 scripts/scholar-search.py search "transformer architectures" --limit 10
```

### Search by author
```bash
python3 scripts/scholar-search.py author "Yann LeCun" --limit 5
```

### Look up by DOI
```bash
python3 scripts/scholar-search.py doi "10.1038/s41586-021-03819-2"
```

### Get citation chain (papers that cite a work)
```bash
python3 scripts/scholar-search.py citations "10.1038/s41586-021-03819-2" --direction both
```

### Deep read (fetch abstract + full text when available)
```bash
python3 scripts/scholar-search.py deep "10.1038/s41586-021-03819-2"
```

### JSON output for programmatic use
```bash
python3 scripts/scholar-search.py search "CRISPR" --json
```

## Literature Review Workflow

Automated multi-step literature review:

```bash
python3 scripts/literature-review.py "algorithmic literacy in education" --papers 30 --output review.md
```

This will:
1. Search for papers across multiple query variations
2. Deduplicate and rank by relevance + citations
3. Identify thematic clusters
4. Generate a structured synthesis in markdown

Options:
- `--papers N` — Target number of papers (default: 20)
- `--output FILE` — Write review to file (default: stdout)
- `--years 2020-2025` — Restrict publication year range
- `--json` — Output structured JSON instead of markdown

## Output Format

All search commands return structured data per paper:
- **Title** and publication year
- **Authors** (up to 5)
- **Abstract** (when available)
- **Citation count**
- **DOI**
- **Open access URL** (when available)
- **Source journal/venue**

## Tips

- OpenAlex sorts by relevance by default; use `--sort citations` for most-cited
- Combine `search` + `deep` for quick triage: search first, deep-read promising hits
- The literature review script caches results in `/tmp/litreview_cache/` to avoid re-fetching
- For full-text PDFs, pipe DOIs to your PDF extraction tool