/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
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install aminer-academic-search - After installation, invoke the skill by name or use
/aminer-academic-search - Provide required inputs per the skill's parameter spec and get structured output
What is AMiner Academic Search?
Academic data search and analysis using AMiner Open Platform APIs. Query scholars, papers, institutions, journals, and patents. Includes 6 composite workflow... It is an AI Agent Skill for Claude Code / OpenClaw, with 432 downloads so far.
How do I install AMiner Academic Search?
Run "/install aminer-academic-search" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is AMiner Academic Search free?
Yes, AMiner Academic Search is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does AMiner Academic Search support?
AMiner Academic Search is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created AMiner Academic Search?
It is built and maintained by ye4wzp (@ye4wzp); the current version is v1.0.0.