drchronx/ai-agent-research-starter-kit/academic-research-openalex

Academic Research

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

Built by Topanga — AI Research Consultant

Quick Start

Search papers by topic

python3 scripts/scholar-search.py search "transformer architectures" --limit 10

Search by author

python3 scripts/scholar-search.py author "Yann LeCun" --limit 5

Look up by DOI

python3 scripts/scholar-search.py doi "10.1038/s41586-021-03819-2"

Get citation chain (papers that cite a work)

python3 scripts/scholar-search.py citations "10.1038/s41586-021-03819-2" --direction both

Deep read (fetch abstract + full text when available)

python3 scripts/scholar-search.py deep "10.1038/s41586-021-03819-2"

JSON output for programmatic use

python3 scripts/scholar-search.py search "CRISPR" --json

Literature Review Workflow

Automated multi-step literature review:

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

⏱️ 超时处理与重试机制（v1.0.1 新增）

超时配置：

• 单次检索超时时间：5 分钟
• 最大重试次数：3 次
• 重试间隔：5 秒

重试策略：

第 1 次失败 → 等待 5 秒 → 重试（减少 limit 参数）
第 2 次失败 → 等待 5 秒 → 重试（简化查询词）
第 3 次失败 → 记录失败原因 → 向主人汇报

OpenAlex API 限制：

• 免费 API 无 key，但有速率限制
• 建议单次检索不超过 100 条结果
• 多次检索之间添加延迟

失败后处理：

1. 记录失败原因（API 超时 / 解析失败 / 网络错误）
2. 向主人汇报："OpenAlex 检索失败，原因：XXX，已重试 3 次"
3. 如 CNKI 和 Google Scholar 已完成，可继续撰写综述
4. 在文档中标注缺失的数据源