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Literature Search Biorxiv

Google DeepMindOfficialPublished by Google DeepMind

  • Skill
  • Tool integration
  • Science and research
  • Apache-2.0
  • Low risk
  • Has scripts

From the author

Browse and filter life sciences, biology, and medical preprints from bioRxiv and medRxiv. Supports fetching paper metadata by DOI, and browsing by date range with category and keyword filters. Keyword filtering is local, so date ranges MUST be narrow (1-4 weeks) with a category to prevent timeouts.
— the description by Google DeepMind

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides an interface to query the bioRxiv and medRxiv preprint servers. It allows users to fetch specific paper metadata using a DOI or browse collections within defined date ranges. Because the underlying API does not support server-side keyword searching, the skill performs filtering locally, requiring users to specify narrow date ranges and categories to ensure successful data retrieval.

What it does

  • Fetches detailed metadata for specific preprints using a DOI.
  • Retrieves lists of preprints based on date ranges and subject categories.
  • Filters results locally by keywords or author names.
  • Supports optional inclusion of full paper abstracts in the output.
  • Enforces rate limits and handles pagination automatically.
  • Outputs results in a structured JSON format.

When to use it

  • When you have a specific DOI and need the associated paper metadata.
  • When you need to monitor recent publications within a specific life science or medical category.
  • When you need to gather a list of preprints from a narrow timeframe for further analysis.
  • When you are conducting a literature review and need to verify preprint details.

Advantages

  • Provides direct access to current life science and medical preprint data.
  • Automates the handling of API pagination and rate limiting.
  • Allows for flexible local filtering by keywords and authors.
  • Supports both bioRxiv and medRxiv servers through a unified interface.

Usage examples

“Fetch metadata for the paper with DOI 10.1101/2023.08.15.551388.”
The skill retrieves the full JSON metadata for the specified paper, including the title, authors, and publication date.
“Find all neuroscience papers published between January 1st and January 14th, 2024.”
The skill returns a JSON file containing the metadata for all preprints matching the category and date range.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/google-deepmind/literature-search-biorxiv/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip literature-search-biorxiv.zip -d .agents/skills

Documentation by Google DeepMind

Prerequisites

  1. uv: Read the uv skill and follow its Setup instructions to ensure uv is installed and on PATH.

  2. User Notification: If .licenses/literature_search_biorxiv_LICENSE.txt does not already exist in the workspace root 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.

Search Strategy Guide (Read First)

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.

Core Rules

  • 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.

Utility Scripts

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.

1. Search by Dates (search_by_dates.py)

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

# Broad category search over a 2-week period
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
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
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.

2. Fetch Metadata by DOI (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.

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

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.

Valid Subject Categories

You can pass these to the --category flag in search_by_dates.py. The script will strictly validate them.

bioRxiv Categories:

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:

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

Files

scripts/search_by_dates.py

# Copyright 2026 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

"""Search bioRxiv/medRxiv by date range with local filtering."""

# /// script
# requires-python = ">=3.10"
# dependencies = [
#   "polite-http",
# ]
# ///

import argparse
import json
import sys
from polite_http import http_client

client = http_client.HttpClient(base_url="https://api.biorxiv.org/", qps=1.0)

# ---------------------------------------------------------------------------
# Constants
# ---------------------------------------------------------------------------

BIORXIV_PAGE_SIZE = 30
BIORXIV_CATEGORIES = [
    "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 = [
    "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",
]


def search_biorxiv(args):
  """Searches bioRxiv/medRxiv for preprints in the given date range."""
  # Strict Category Validation
  if args.category:
    if args.server == "biorxiv" and args.category not in BIORXIV_CATEGORIES:
      sys.exit(
          f"Error: Invalid category '{args.category}' for bioRxiv.\n"
          f"Valid categories are: {', '.join(BIORXIV_CATEGORIES)}"
      )
    elif args.server == "medrxiv" and args.category not in MEDRXIV_CATEGORIES:
      sys.exit(
          f"Error: Invalid category '{args.category}' for medRxiv.\n"
          f"Valid categories are: {', '.join(MEDRXIV_CATEGORIES)}"
      )

  base_url = (
      f"https://api.biorxiv.org/details/{args.server}"
      f"/{args.start_date}/{args.end_date}"
  )
  cursor = 0
  all_results = []
  total_fetched = 0
  total_after_category = 0
  page_num = 0

  print(
      f"Fetching metadata for {args.server} from {args.start_date}"
      f" to {args.end_date}...",
      file=sys.stderr,
  )
  if args.category:
    print(f"  Category filter: {args.category}", file=sys.stderr)
  if args.keywords:
    print(
        f"  Keyword filter ({args.match_logic}): {', '.join(args.keywords)}",
        file=sys.stderr,
    )
  if args.author:
    print(f"  Author filter: {args.author}", file=sys.stderr)

  while True:
    url = f"{base_url}/{cursor}"
    page_num += 1
    data = client.fetch_json(url)

    collection = data.get("collection", [])
    if not collection:
      break

    total_fetched += len(collection)

    # Print pagination progress to stderr
    print(
        f"  [Page {page_num}] Fetched {total_fetched} papers...",
        file=sys.stderr,
    )

    for paper in collection:
      # Local Category Filtering
      # The API may ignore the category query parameter, so we always
      # enforce category filtering locally as a reliable fallback.
      if args.category:
        paper_category = paper.get("category", "").lower().replace(" ", "_")
        if paper_category != args.category.lower():
          continue

      total_after_category += 1

      # Local Author Filtering
      if args.author:
        author_list = paper.get("authors", "").lower().split(";")
        if not any(args.author.lower() in a for a in author_list):
          continue

      # Local Keyword Filtering (checks title and abstract)
      if args.keywords:
        title = paper.get("title", "").lower()
        abstract = paper.get("abstract", "").lower()
        text_to_search = f"{title} {abstract}"

        kw_lower = [k.lower() for k in args.keywords]
        if args.match_logic == "AND":
          if not all(kw in text_to_search for kw in kw_lower):
            continue
        else:  # OR logic
          if not any(kw in text_to_search for kw in kw_lower):
            continue

      # Strip abstract if not requested
      if not args.include_abstracts and "abstract" in paper:
        del paper["abstract"]

      all_results.append(paper)

    # The bioRxiv API returns results in pages of up to `BIORXIV_PAGE_SIZE`
    # items. We advance `cursor` by the page size and stop once we get a short
    # page.  NOTE: We intentionally do NOT use `total_count` for
    # termination because the API sometimes reports `BIORXIV_PAGE_SIZE` (the
    # page size) rather than the true total, which causes premature stopping.
    cursor += len(collection)

    if len(collection) < BIORXIV_PAGE_SIZE:
      # A short page is the only reliable signal that we've fetched everything.
      break

  # Print summary to stderr so the agent can assess results
  print("\n--- Search Summary ---", file=sys.stderr)
  print(
      f"  Total papers in date range: {total_fetched}"
      + (f" (across {page_num} page(s))" if page_num > 1 else ""),
      file=sys.stderr,
  )
  if args.category:
    print(
        f"  After category filter ('{args.category}'): {total_after_category}",
        file=sys.stderr,
    )
  print(
      f"  Final results after all filters: {len(all_results)}",
      file=sys.stderr,
  )
  if not all_results:
    print(
        "  Tip: No results found. Try widening the date range, removing keyword"
        " filters, or changing the category. If searching for a specific paper,"
        " consider using search_by_doi.py with the paper's DOI instead.",
        file=sys.stderr,
    )

  print(json.dumps(all_results, indent=2))


def main():
  """Parses arguments and searches bioRxiv/medRxiv."""
  parser = argparse.ArgumentParser(
      description="Search bioRxiv/medRxiv by date range with local filtering."
  )
  parser.add_argument(
      "--server",
      choices=["biorxiv", "medrxiv"],
      default="biorxiv",
      help="The preprint server to query.",
  )
  parser.add_argument(
      "--start_date",
      required=True,
      help="Start date (YYYY-MM-DD)",
  )
  parser.add_argument(
      "--end_date",
      required=True,
      help="End date (YYYY-MM-DD)",
  )
  parser.add_argument("--category", help="Strict server-side category filter")
  parser.add_argument("--author", help="Local author filter (case-insensitive)")
  parser.add_argument(
      "--keywords",
      nargs="+",
      help="Local keyword filters applied to title and abstract",
  )
  parser.add_argument(
      "--match_logic",
      choices=["AND", "OR"],
      default="AND",
      help="Keyword matching logic",
  )
  parser.add_argument(
      "--include_abstracts",
      action="store_true",
      help="Include full abstracts in the JSON output",
  )

  args = parser.parse_args()
  search_biorxiv(args)


if __name__ == "__main__":
  main()

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs Python

Security

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Attribution and licence

Published by
Google DeepMind
Publisher
Google DeepMind (Official)
Source
google-deepmind/science-skills · skills/literature_search_biorxiv · commit 4de6786
Licence
Apache License 2.0 (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

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