Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/agent-skills-hub/agent-skills-hubnpx agentmods add skills/agent-skills-hub/agent-skills-hub/biorxiv-databaseWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/agent-skills-hub/agent-skills-hub/biorxiv-database)<a href="https://agentmods.dev/skills/agent-skills-hub/agent-skills-hub/biorxiv-database"><img src="https://agentmods.dev/badge/skills/agent-skills-hub/agent-skills-hub/biorxiv-database/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/agent-skills-hub/agent-skills-hub/biorxiv-database"><img src="https://agentmods.dev/badge/skills/agent-skills-hub/agent-skills-hub/biorxiv-database.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00052 | $0.03334 |
| Opus 5.5 | $0.00021 | $0.01334 |
| Sonnet 5.5 | $0.00010 | $0.00667 |
| Haiku 4.5 | $0.00005 | $0.00333 |
Grade A, and why
biorxiv-database scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
91% identical to biorxiv-database — 10 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 483 lines — stays where its author put it; the contents beside it link to each section on GitHub.
bioRxiv Database
Overview
This skill provides efficient Python-based tools for searching and retrieving preprints from the bioRxiv database. It enables comprehensive searches by keywords, authors, date ranges, and categories, returning structured JSON metadata that includes titles, abstracts, DOIs, and citation information. The skill also supports PDF downloads for full-text analysis.
When to Use This Skill
Use this skill when:
- Searching for recent preprints in specific research areas
- Tracking publications by particular authors
- Conducting systematic literature reviews
- Analyzing research trends over time periods
- Retrieving metadata for citation management
- Downloading preprint PDFs for analysis
- Filtering papers by bioRxiv subject categories
Core Search Capabilities
1. Keyword Search
Search for preprints containing specific keywords in titles, abstracts, or author lists.
Basic Usage:
python scripts/biorxiv_search.py \
--keywords "CRISPR" "gene editing" \
--start-date 2024-01-01 \
--end-date 2024-12-31 \
--output results.json
With Category Filter:
python scripts/biorxiv_search.py \
--keywords "neural networks" "deep learning" \
--days-back 180 \
--category neuroscience \
--output recent_neuroscience.json
Search Fields:
By default, keywords are searched in both title and abstract. Customize with --search-fields:
python scripts/biorxiv_search.py \
--keywords "AlphaFold" \
--search-fields title \
--days-back 365
2. Author Search
Find all papers by a specific author within a date range.
Basic Usage:
python scripts/biorxiv_search.py \
--author "Smith" \
--start-date 2023-01-01 \
--end-date 2024-12-31 \
--output smith_papers.json
Recent Publications:
# Last year by default if no dates specified
python scripts/biorxiv_search.py \
--author "Johnson" \
--output johnson_recent.json
3. Date Range Search
Retrieve all preprints posted within a specific date range.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 483 lines · 52 tokens per session scan A 75441ec0cff4
biorxiv-database is a skill published in the GitHub repository agent-skills-hub/agent-skills-hub (124 stars, last pushed 25d ago), licensed MIT. It adds 52 tokens to every session and 3,334 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 91% identical to biorxiv-database, differing in 10 lines, and is treated as a copy.
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