/install aminer-academic-search
AMiner Academic Data Search (学术数据查询)
AMiner is a leading global academic data platform. This skill covers all 28 open APIs organized into 6 practical workflows for comprehensive academic research.
- API Docs: https://open.aminer.cn/open/doc
- Console (Token): https://open.aminer.cn/open/board?tab=control
Getting Started
1. Get API Token
- Visit AMiner Console
- Login and generate an API Token
- Token goes in
Authorizationheader for all requests
2. Quick Usage
# Scholar profile analysis
python scripts/aminer_client.py --token \x3CTOKEN> --action scholar_profile --name "Andrew Ng"
# Paper deep dive (with citation chain)
python scripts/aminer_client.py --token \x3CTOKEN> --action paper_deep_dive --title "Attention is all you need"
# Organization analysis
python scripts/aminer_client.py --token \x3CTOKEN> --action org_analysis --org "清华大学"
# Venue/journal paper monitoring
python scripts/aminer_client.py --token \x3CTOKEN> --action venue_papers --venue "Nature" --year 2024
# Academic Q&A (natural language)
python scripts/aminer_client.py --token \x3CTOKEN> --action paper_qa --query "transformer架构最新进展"
# Patent search
python scripts/aminer_client.py --token \x3CTOKEN> --action patent_search --query "量子计算"
Reliability & Error Handling
Built-in resilience:
- Timeout: 30s default
- Retries: Max 3 with exponential backoff (1s → 2s → 4s) + jitter
- Retryable:
408 / 429 / 500 / 502 / 503 / 504 - Degradation:
paper_deep_diveauto-falls back topaper_search_pro;paper_qadegrades topaper_search_pro - Traceability: Composite workflow output includes
source_api_chain
Paper Search API Selection Guide
| API | Focus | Use Case | Cost |
|---|---|---|---|
paper_search |
Title lookup → paper_id |
Known paper title | Free |
paper_search_pro |
Multi-condition search | Filter by author/org/venue | ¥0.01 |
paper_qa_search |
Natural language Q&A | Semantic search | ¥0.05 |
paper_list_by_search_venue |
Rich paper info | Analysis/reports | ¥0.30 |
paper_list_by_keywords |
Multi-keyword batch | Topic batch retrieval | ¥0.10 |
paper_detail_by_condition |
Year + venue filter | Annual venue monitoring | ¥0.20 |
Recommended routing:
- Known title →
paper_search→paper_detail→paper_relation - Condition filter →
paper_search_pro→paper_detail - Natural language →
paper_qa_search(fallback:paper_search_pro) - Venue analysis →
venue_search→venue_paper_relation→paper_detail_by_condition
6 Composite Workflows
1. Scholar Profile (学者全景分析)
Use: Complete academic profile of a scholar.
Scholar Search (name → person_id)
↓
Parallel:
├── Scholar Detail (bio/education/honors)
├── Scholar Figure (research areas/interests)
├── Scholar Papers (publication list)
├── Scholar Patents (patent list)
└── Scholar Projects (grants/funding)
python scripts/aminer_client.py --token \x3CTOKEN> --action scholar_profile --name "Yann LeCun"
2. Paper Deep Dive (论文深度挖掘)
Use: Full paper info + citation chain.
Paper Search (title → paper_id)
↓
Paper Detail (abstract/authors/DOI/venue/year)
↓
Paper Citations (cited papers → cited_ids)
↓
(Optional) Batch paper info for cited papers
python scripts/aminer_client.py --token \x3CTOKEN> --action paper_deep_dive --title "BERT"
3. Organization Analysis (机构研究力分析)
Use: Analyze an institution's research capabilities.
Org Disambiguation Pro (raw string → org_id)
↓
Parallel:
├── Org Detail (intro/type/founded)
├── Org Scholars (scholar list)
├── Org Papers (paper list)
└── Org Patents (patent list, up to 10k)
python scripts/aminer_client.py --token \x3CTOKEN> --action org_analysis --org "MIT"
4. Venue Papers (期刊论文监控)
Use: Track papers from a specific journal/venue by year.
Venue Search (name → venue_id)
↓
Venue Detail (ISSN/type/abbreviation)
↓
Venue Papers (venue_id + year → paper_ids)
↓
(Optional) Batch paper details
python scripts/aminer_client.py --token \x3CTOKEN> --action venue_papers --venue "NeurIPS" --year 2023
5. Paper Q&A (学术智能问答)
Use: Natural language academic search.
Supports: query (natural language), topic_high/middle/low (keyword weights), sci_flag, force_citation_sort, author_terms, org_terms.
python scripts/aminer_client.py --token \x3CTOKEN> --action paper_qa \
--query "用于蛋白质结构预测的深度学习方法"
6. Patent Analysis (专利链分析)
Use: Search patents by technology domain.
Patent Search (query → patent_id)
↓
Patent Detail (abstract/filing date/assignee/inventor)
python scripts/aminer_client.py --token \x3CTOKEN> --action patent_search --query "量子计算芯片"
Full API Reference
| # | API | Method | Cost | Path |
|---|---|---|---|---|
| 1 | Paper QA Search | POST | ¥0.05 | /api/paper/qa/search |
| 2 | Scholar Search | POST | Free | /api/person/search |
| 3 | Paper Search | GET | Free | /api/paper/search |
| 4 | Paper Search Pro | GET | ¥0.01 | /api/paper/search/pro |
| 5 | Patent Search | POST | Free | /api/patent/search |
| 6 | Org Search | POST | Free | /api/organization/search |
| 7 | Venue Search | POST | Free | /api/venue/search |
| 8 | Scholar Detail | GET | ¥1.00 | /api/person/detail |
| 9 | Scholar Projects | GET | ¥3.00 | /api/project/person/v3/open |
| 10 | Scholar Papers | GET | ¥1.50 | /api/person/paper/relation |
| 11 | Scholar Patents | GET | ¥1.50 | /api/person/patent/relation |
| 12 | Scholar Figure | GET | ¥0.50 | /api/person/figure |
| 13 | Paper Info | POST | Free | /api/paper/info |
| 14 | Paper Detail | GET | ¥0.01 | /api/paper/detail |
| 15 | Paper Citation | GET | ¥0.10 | /api/paper/relation |
| 16 | Patent Info | GET | Free | /api/patent/info |
| 17 | Patent Detail | GET | ¥0.01 | /api/patent/detail |
| 18 | Org Detail | POST | ¥0.01 | /api/organization/detail |
| 19 | Org Patents | GET | ¥0.10 | /api/organization/patent/relation |
| 20 | Org Scholars | GET | ¥0.50 | /api/organization/person/relation |
| 21 | Org Papers | GET | ¥0.10 | /api/organization/paper/relation |
| 22 | Venue Detail | POST | ¥0.20 | /api/venue/detail |
| 23 | Venue Papers | POST | ¥0.10 | /api/venue/paper/relation |
| 24 | Org Disambiguation | POST | ¥0.01 | /api/organization/na |
| 25 | Org Disambiguation Pro | POST | ¥0.05 | /api/organization/na/pro |
| 26 | Paper Search (venue) | GET | ¥0.30 | /api/paper/list/by/search/venue |
| 27 | Paper Batch (keywords) | GET | ¥0.10 | /api/paper/list/citation/by/keywords |
| 28 | Paper Detail (condition) | GET | ¥0.20 | /api/paper/platform/allpubs/more/detail/by/ts/org/venue |
Base URL: https://datacenter.aminer.cn/gateway/open_platform
References
- Official Docs: https://open.aminer.cn/open/doc
- Console: https://open.aminer.cn/open/board?tab=control
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install aminer-academic-search - 安装完成后,直接呼叫该 Skill 的名称或使用
/aminer-academic-search触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
AMiner Academic Search 是什么?
Academic data search and analysis using AMiner Open Platform APIs. Query scholars, papers, institutions, journals, and patents. Includes 6 composite workflow... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 432 次。
如何安装 AMiner Academic Search?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install aminer-academic-search」即可一键安装,无需额外配置。
AMiner Academic Search 是免费的吗?
是的,AMiner Academic Search 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
AMiner Academic Search 支持哪些平台?
AMiner Academic Search 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 AMiner Academic Search?
由 ye4wzp(@ye4wzp)开发并维护,当前版本 v1.0.0。