name: aminer-data-search version: 1.0.0 description: > Academic data search and analysis using AMiner Open Platform APIs. Query scholars, papers, institutions, journals, and patents. Includes 6 composite workflows (Scholar Profile, Paper Deep Dive, Org Analysis, Venue Papers, Paper QA, Patent Analysis) and 28 individual APIs. Triggers: "AMiner", "学术数据", "查论文", "查学者", "学术搜索", "academic search", "paper search", "scholar lookup", "citation analysis". tags: [academic, research, aminer, scholar, paper, journal, patent, citation, chinese, english] env: AMINER_TOKEN: "AMiner API Token (from https://open.aminer.cn/open/board?tab=control)"

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

1. Visit AMiner Console
2. Login and generate an API Token
3. Token goes in Authorization header for all requests

2. Quick Usage

# Scholar profile analysis
python scripts/aminer_client.py --token <TOKEN> --action scholar_profile --name "Andrew Ng"

# Paper deep dive (with citation chain)
python scripts/aminer_client.py --token <TOKEN> --action paper_deep_dive --title "Attention is all you need"

# Organization analysis
python scripts/aminer_client.py --token <TOKEN> --action org_analysis --org "清华大学"

# Venue/journal paper monitoring
python scripts/aminer_client.py --token <TOKEN> --action venue_papers --venue "Nature" --year 2024

# Academic Q&A (natural language)
python scripts/aminer_client.py --token <TOKEN> --action paper_qa --query "transformer架构最新进展"

# Patent search
python scripts/aminer_client.py --token <TOKEN> --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_dive auto-falls back to paper_search_pro; paper_qa degrades to paper_search_pro - Traceability: Composite workflow output includes source_api_chain

Paper Search API Selection Guide

Recommended routing: 1. Known title → paper_search → paper_detail → paper_relation 2. Condition filter → paper_search_pro → paper_detail 3. Natural language → paper_qa_search (fallback: paper_search_pro) 4. 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 <TOKEN> --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 <TOKEN> --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 <TOKEN> --action org_analysis --org "MIT"

4. Venue Papers (期刊论文监控)

Use: Track papers from a specific journal/venue by year.

7w4.net小葱技能站收录全网优质技能，值得收藏。

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 <TOKEN> --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 <TOKEN> --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 <TOKEN> --action patent_search --query "量子计算芯片"

Full API Reference

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

这个Skill质量中等偏上，文档写得非常详细清楚，工作流设计实用，错误处理考虑周全。但最大的问题是它只提供了说明书，缺少能直接运行的程序代码，所以没法真正使用。如果你需要的是一份学术搜索API的参考手册，它很合适；但如果想要一个能直接调用的工具，目前还做不到。