literature-search-biorxiv

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bioRxiv and medRxiv Literature Search

bioRxiv与medRxiv文献检索

Prerequisites

前提条件

uv
: Read the
```
uv
```
skill and follow its Setup instructions to ensure
```
uv
```
is installed and on PATH.
User Notification: If LICENSE_NOTIFICATION.txt does not already exist in this skill directory then (1) prominently notify the user to check the terms at https://api.biorxiv.org/ and https://www.biorxiv.org/content/about-biorxiv and to always check the license of the papers retrieved by the skill for any restrictions, then (2) create the file recording the notification text and timestamp.

uv
：阅读
```
uv
```
技能文档并遵循其设置说明，确保
```
uv
```
已安装且添加至系统PATH。
用户通知：若此技能目录中不存在LICENSE_NOTIFICATION.txt文件，则需（1）显著通知用户查看https://api.biorxiv.org/和https://www.biorxiv.org/content/about-biorxiv上的条款，并务必检查该技能检索到的论文的许可证是否存在使用限制；（2）创建记录通知文本和时间戳的文件。

Search Strategy Guide (Read First)

检索策略指南（请先阅读）

This skill browses a date-based preprint archive. It is NOT a keyword search engine. Choose your approach based on what you already know:

A DOI (e.g., from a citation): Use
```
search_by_doi.py
```
. Fast and reliable.
Approximate date + category: Use
```
search_by_dates.py
```
with a 1–4 week range and
```
--category
```
.
Only a topic or keywords, no date: Do NOT use this skill for discovery. Use a keyword-capable literature skill first to find relevant DOIs, then return here to fetch metadata.

CRITICAL ANTI-PATTERN — Do NOT do this: Do NOT attempt to search broad date ranges (months or years) with
--keywords
hoping to find a specific paper. The bioRxiv API does not support server-side keyword search. The script must download ALL metadata for the entire date range and filter locally in Python. Broad ranges will result in thousands of API calls, timeouts, and your request being blocked for API abuse. This is the #1 reason this skill fails.

**本技能用于浏览基于日期的预印本文档库，并非关键词搜索引擎。**请根据已知信息选择合适的方法：

已知DOI（例如来自引用）：使用
```
search_by_doi.py
```
，快速且可靠。
大致日期+分类：使用
```
search_by_dates.py
```
，设置1-4周的时间范围并搭配
```
--category
```
参数。
仅知道主题或关键词，无日期信息：请勿使用本技能进行探索性检索。请先使用支持关键词检索的文献技能找到相关DOI，再返回此处获取元数据。

重要反模式——请勿执行此操作：请勿尝试使用
--keywords
参数搜索宽泛的日期范围（数月或数年）以查找特定论文。bioRxiv API不支持服务器端关键词搜索，脚本必须下载整个日期范围内的所有元数据并在Python中本地筛选。宽泛的日期范围会导致数千次API调用、超时，甚至因API滥用导致请求被拦截。这是本技能失效的首要原因。

Core Rules

核心规则

Use the Wrapper: ALWAYS execute the provided helper scripts to query the database rather than accessing the database directly. The scripts automatically enforce the required rate limit gracefully.
Local Filtering (CRITICAL WARNING): Unlike arXiv, the bioRxiv API does not support server-side keyword or author searches. Keyword and author filtering is performed locally by the scripts after downloading all metadata for a specified date range. You MUST use narrow date ranges (e.g., 1-4 weeks) AND the
```
--category
```
filter when searching with
```
--keywords
```
or
```
--author
```
.
Abstracts Excluded By Default: To save context space in the resulting JSON, abstracts are stripped from the output by default. If you are searching by
```
--keywords
```
and want to read the abstracts of the resulting papers to understand their context, you MUST pass the
```
--include_abstracts
```
flag.
Output Redirection: Search commands output JSON arrays to standard output. Always redirect output to a file (e.g.,
```
> results.json
```
) and parse the file separately.
List Sources If this skill is used, ensure this is mentioned in the output AND list the URLs of all papers that were used in producing the output.

使用封装脚本：始终执行提供的辅助脚本查询数据库，而非直接访问数据库。脚本会自动优雅地执行必要的速率限制。
本地筛选（重要警告）：与arXiv不同，bioRxiv API不支持服务器端关键词或作者检索。关键词和作者筛选由脚本在下载指定日期范围内的所有元数据后在本地执行。使用
```
--keywords
```
或
```
--author
```
参数检索时，必须使用较窄的日期范围（例如1-4周）并搭配
```
--category
```
筛选条件。
默认排除摘要：为节省生成的JSON的上下文空间，默认会从输出中移除摘要。若使用
```
--keywords
```
检索并希望查看结果论文的摘要以了解其背景，必须传递
```
--include_abstracts
```
标志。
输出重定向：检索命令会将JSON数组输出至标准输出。请始终将输出重定向至文件（例如
```
> results.json
```
）并单独解析该文件。
列出来源：若使用本技能，请确保在输出中提及这一点，并列出所有用于生成输出的论文的URL。

Utility Scripts

实用脚本

All tools enforce a cross-process rate limits and retry with backoff on failure. To ensure you respect terms-of-service, do NOT write custom

curl

queries.

Pagination: The bioRxiv API returns results in pages of up to 100 papers. The

search_by_dates.py

script automatically fetches all pages and reports pagination progress to stderr (e.g.,

[Page 2] Fetched 200/543 papers...

). The JSON output to stdout contains the complete filtered result set across all pages — no manual pagination is needed.

所有工具都会执行跨进程速率限制，并在失败时自动重试并退避。为确保遵守服务条款，请勿编写自定义

curl

查询。

分页处理：bioRxiv API会以每页最多100篇论文的形式返回结果。

search_by_dates.py

脚本会自动获取所有页面，并向标准错误输出报告分页进度（例如

[Page 2] Fetched 200/543 papers...

）。向标准输出输出的JSON包含所有页面的完整筛选结果集——无需手动分页。

1. Search by Dates (

search_by_dates.py

)

1. 按日期检索（

search_by_dates.py

）

Search for preprints within an explicit date range, optionally filtering by category, keywords, or author.

bash

undefined

在指定日期范围内检索预印本，可选择按分类、关键词或作者筛选。

bash

undefined

Broad category search over a 2-week period

对神经科学分类进行为期2周的宽泛检索

uv run scripts/search_by_dates.py --server biorxiv
--start_date 2024-01-01 --end_date 2024-01-14
--category neuroscience > results.json

Deep keyword filtering using OR logic and including abstracts

使用OR逻辑进行深度关键词筛选并包含摘要

uv run scripts/search_by_dates.py --server medrxiv
--start_date 2023-11-01 --end_date 2023-11-30
--category infectious_diseases
--keywords "covid" "sars-cov-2" --match_logic OR
--include_abstracts > covid_papers.json

Finding papers by a specific author in a narrow window

在窄时间窗口内查找特定作者的论文

uv run scripts/search_by_dates.py
--start_date 2024-05-01 --end_date 2024-05-14
--author "Smith" > smith_papers.json


*Required Arguments:*

-   `--start_date`: YYYY-MM-DD
-   `--end_date`: YYYY-MM-DD

*Optional Arguments:*

-   `--server`: `biorxiv` (default) or `medrxiv`
-   `--category`: A valid subject category (see below). **Highly recommended** —
    dramatically reduces the data the script must download and filter.
-   `--keywords`: List of strings to search in the title/abstract.
-   `--match_logic`: `AND` (default) or `OR` for keywords.
-   `--author`: Author name (case-insensitive string match).
-   `--include_abstracts`: Flag to include full abstracts in the JSON output.

uv run scripts/search_by_dates.py
--start_date 2024-05-01 --end_date 2024-05-14
--author "Smith" > smith_papers.json


*必填参数：*

-   `--start_date`：格式为YYYY-MM-DD
-   `--end_date`：格式为YYYY-MM-DD

*可选参数：*

-   `--server`：`biorxiv`（默认）或`medrxiv`
-   `--category`：有效的主题分类（见下文）。**强烈推荐使用**——可大幅减少脚本需下载和筛选的数据量。
-   `--keywords`：用于在标题/摘要中搜索的字符串列表。
-   `--match_logic`：关键词匹配逻辑，可选`AND`（默认）或`OR`。
-   `--author`：作者姓名（不区分大小写的字符串匹配）。
-   `--include_abstracts`：在JSON输出中包含完整摘要的标志。

2. Fetch Metadata by DOI (

search_by_doi.py

)

2. 通过DOI获取元数据（

search_by_doi.py

）

Retrieve the detailed JSON metadata for a single paper if you already know its DOI. This is the most reliable entry point.

bash

uv run scripts/search_by_doi.py --server biorxiv \
  --doi "10.1101/2023.08.15.551388" \
  --include_abstracts > paper_info.json

若已知论文的DOI，可检索单篇论文的详细JSON元数据。这是最可靠的入口方式。

bash

uv run scripts/search_by_doi.py --server biorxiv \
  --doi "10.1101/2023.08.15.551388" \
  --include_abstracts > paper_info.json

Downloading Full-Text PDFs

下载全文PDF

This skill does NOT support PDF downloads. To download the full-text PDF of a bioRxiv or medRxiv preprint, use the literature-search-europepmc
skill. First, use the paper's DOI to look up its PMCID via EuropePMC, then use EuropePMC's PDF retrieval to download the document.

本技能不支持PDF下载。若要下载bioRxiv或medRxiv预印本的全文PDF，请使用**
literature-search-europepmc
**技能。首先通过EuropePMC使用论文的DOI查找其PMCID，然后使用EuropePMC的PDF检索功能下载文档。

Valid Subject Categories

有效主题分类

You can pass these to the

--category

flag in

search_by_dates.py

. The script will strictly validate them.

可将以下分类传递给

search_by_dates.py

中的

--category

参数，脚本会严格验证这些分类。

bioRxiv Categories:

bioRxiv分类：

animal_behavior_and_cognition

biochemistry

bioengineering

bioinformatics

biophysics

cancer_biology

cell_biology

clinical_trials

developmental_biology

ecology

epidemiology

evolutionary_biology

genetics

genomics

immunology

microbiology

molecular_biology

neuroscience

paleontology

pathology

pharmacology_and_toxicology

physiology

plant_biology

scientific_communication_and_education

synthetic_biology

systems_biology

zoology

animal_behavior_and_cognition

biochemistry

bioengineering

bioinformatics

biophysics

cancer_biology

cell_biology

clinical_trials

developmental_biology

ecology

epidemiology

evolutionary_biology

genetics

genomics

immunology

microbiology

molecular_biology

neuroscience

paleontology

pathology

pharmacology_and_toxicology

physiology

plant_biology

scientific_communication_and_education

synthetic_biology

systems_biology

zoology

medRxiv Categories:

medRxiv分类：

addiction_medicine

allergy_and_immunology

anesthesia

cardiovascular_medicine

dentistry_and_oral_medicine

dermatology

emergency_medicine

endocrinology

epidemiology

forensic_medicine

gastroenterology

genetic_and_genomic_medicine

health_informatics

health_economics_and_outcomes_research

health_policy

health_systems_and_quality_improvement

hematology

hiv_aids

infectious_diseases

intensive_care_and_critical_care_medicine

medical_education

medical_ethics

nephrology

neurology

nursing

nutrition

obstetrics_and_gynecology

occupational_and_environmental_health

oncology

ophthalmology

orthopedics

otolaryngology

pain_medicine

palliative_care

pathology

pediatrics

pharmacology_and_therapeutics

primary_care_research

psychiatry_and_clinical_psychology

public_and_global_health

radiology_and_imaging

rehabilitation_medicine_and_physical_therapy

respiratory_medicine

rheumatology

sexual_and_reproductive_health

sports_medicine

surgery

toxicology

transplantation

urology

addiction_medicine

allergy_and_immunology

anesthesia

cardiovascular_medicine

dentistry_and_oral_medicine

dermatology

emergency_medicine

endocrinology

epidemiology

forensic_medicine

gastroenterology

genetic_and_genomic_medicine

health_informatics

health_economics_and_outcomes_research

health_policy

health_systems_and_quality_improvement

hematology

hiv_aids

infectious_diseases

intensive_care_and_critical_care_medicine

medical_education

medical_ethics

nephrology

neurology

nursing

nutrition

obstetrics_and_gynecology

occupational_and_environmental_health

oncology

ophthalmology

orthopedics

otolaryngology

pain_medicine

palliative_care

pathology

pediatrics

pharmacology_and_therapeutics

primary_care_research

psychiatry_and_clinical_psychology

public_and_global_health

radiology_and_imaging

rehabilitation_medicine_and_physical_therapy

respiratory_medicine

rheumatology

sexual_and_reproductive_health

sports_medicine

surgery

toxicology

transplantation

urology

literature-search-biorxiv

Original

Translation

bioRxiv and medRxiv Literature Search

bioRxiv与medRxiv文献检索

Prerequisites

前提条件

Search Strategy Guide (Read First)

检索策略指南（请先阅读）

Core Rules

核心规则

Utility Scripts

实用脚本

1. Search by Dates (
`search_by_dates.py`
)

1. 按日期检索（
`search_by_dates.py`
）

Broad category search over a 2-week period

对神经科学分类进行为期2周的宽泛检索

Deep keyword filtering using OR logic and including abstracts

使用OR逻辑进行深度关键词筛选并包含摘要

Finding papers by a specific author in a narrow window

在窄时间窗口内查找特定作者的论文

2. Fetch Metadata by DOI (
`search_by_doi.py`
)

2. 通过DOI获取元数据（
`search_by_doi.py`
）

Downloading Full-Text PDFs

下载全文PDF

Valid Subject Categories

有效主题分类

bioRxiv Categories:

bioRxiv分类：

medRxiv Categories:

medRxiv分类：

literature-search-biorxiv

Original

Translation

bioRxiv and medRxiv Literature Search

bioRxiv与medRxiv文献检索

Prerequisites

前提条件

Search Strategy Guide (Read First)

检索策略指南（请先阅读）

Core Rules

核心规则

Utility Scripts

实用脚本

1. Search by Dates (search_by_dates.py)

1. 按日期检索（search_by_dates.py）

Broad category search over a 2-week period

对神经科学分类进行为期2周的宽泛检索

Deep keyword filtering using OR logic and including abstracts

使用OR逻辑进行深度关键词筛选并包含摘要

Finding papers by a specific author in a narrow window

在窄时间窗口内查找特定作者的论文

2. Fetch Metadata by DOI (search_by_doi.py)

2. 通过DOI获取元数据（search_by_doi.py）

Downloading Full-Text PDFs

下载全文PDF

Valid Subject Categories

有效主题分类

bioRxiv Categories:

bioRxiv分类：

medRxiv Categories:

medRxiv分类：

1. Search by Dates (
`search_by_dates.py`
)

1. 按日期检索（
`search_by_dates.py`
）

2. Fetch Metadata by DOI (
`search_by_doi.py`
)

2. 通过DOI获取元数据（
`search_by_doi.py`
）