来源信息
- 仓库
- brycewang-stanford/Auto-Empirical-Research-Skills
- 最近来源活动
- 2026年4月3日 02:07
- 检测到的 SKILL.md 语言
- 英语
- 星标
- 3,291
- 分支
- 432
安装方式
默认使用会先检查来源的 Prompt;你也可以切换为直接命令,或下载本地副本。
检查来源文件
决定是否安装前,请先阅读 SKILL.md,以及 SkillsMP 当前展示的配套文件。
菜单
默认使用会先检查来源的 Prompt;你也可以切换为直接命令,或下载本地副本。
决定是否安装前,请先阅读 SKILL.md,以及 SkillsMP 当前展示的配套文件。
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。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills --skill semantic-scholar-api命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
基于 SOC 职业分类
正在显示 SKILL.md
| name | semantic-scholar-api |
| description | Search papers and analyze citation graphs via OpenAlex and CrossRef APIs |
| metadata | {"openclaw":{"emoji":"🔍","category":"literature","subcategory":"search","keywords":["academic database search","semantic search","AI-powered literature search","citation analysis","citation network"],"source":"https://api.openalex.org/"}} |
OpenAlex is a free, open catalog of the global research system, indexing over 250 million academic works across all fields of science. It provides structured access to papers, authors, institutions, concepts, and citation networks. OpenAlex is the successor to Microsoft Academic Graph and is maintained by OurResearch (the team behind Unpaywall).
CrossRef is the official DOI registration agency for scholarly content, providing metadata for over 150 million DOIs across all publishers and disciplines. Together, OpenAlex and CrossRef provide comprehensive coverage for academic search, citation analysis, and bibliometric research.
Both APIs are free to use without authentication. OpenAlex requests a polite User-Agent header; CrossRef requests a User-Agent with contact email for access to the polite pool (faster rate limits).
No authentication is required for either API.
OpenAlex: Include a User-Agent header for polite access:
User-Agent: ResearchPlugins/1.0 (https://wentor.ai)
CrossRef: Include a User-Agent header with contact email for polite pool:
User-Agent: ResearchPlugins/1.0 (https://wentor.ai; mailto:dev@wentor.ai)
GET https://api.openalex.org/works| Param | Type | Required | Description |
|---|---|---|---|
| search | string | No | Full-text search query |
| filter | string | No | Filter expression (e.g., from_publication_date:2024-01-01) |
| sort | string | No | Sort field (e.g., cited_by_count:desc, publication_date:desc) |
| per_page | integer | No | Results per page (default: 25, max: 200) |
| page | integer | No | Page number (default: 1) |
curl "https://api.openalex.org/works?search=attention+is+all+you+need&per_page=5"
meta (count, page info) and results array containing work objects.GET https://api.openalex.org/works/{id}| Param | Type | Required | Description |
|---|---|---|---|
| id | string | Yes | OpenAlex ID (e.g., W2741809807), DOI URL, or other identifier |
curl "https://api.openalex.org/works/W2741809807"
id, title, abstract_inverted_index, publication_year, cited_by_count, authorships, concepts, referenced_works.GET https://api.openalex.org/authors| Param | Type | Required | Description |
|---|---|---|---|
| search | string | No | Author name search |
| filter | string | No | Filter expression |
| per_page | integer | No | Results per page (max: 200) |
curl "https://api.openalex.org/authors?search=Yoshua+Bengio&per_page=5"
works_count, cited_by_count, summary_stats.h_index, affiliations.GET https://api.crossref.org/works/{doi}| Param | Type | Required | Description |
|---|---|---|---|
| doi | string | Yes | DOI to resolve (e.g., 10.1038/nature12373) |
curl "https://api.crossref.org/works/10.18653/v1/N19-1423"
OpenAlex: No strict rate limit, but use polite User-Agent header. Recommended: max 10 requests per second. The API returns HTTP 429 when limits are exceeded.
CrossRef: Without polite pool: ~50 requests per second. With polite pool (contact email in User-Agent): higher limits. The API returns HTTP 429 when limits are exceeded.
Retrieve a paper and find all works that cite it:
# Get paper details
curl "https://api.openalex.org/works/W2741809807"
# Get works citing this paper, sorted by citation count
curl "https://api.openalex.org/works?filter=cites:W2741809807&sort=cited_by_count:desc&per_page=20"
Search for highly cited works on a topic:
curl "https://api.openalex.org/works?search=graph+neural+networks&sort=cited_by_count:desc&per_page=20"
Search CrossRef for papers matching a query, sorted by citation count:
curl "https://api.crossref.org/works?query=graph+neural+networks&sort=is-referenced-by-count&order=desc&rows=20"