synthetic-sciences/openscience is an AI workbench that carries out scientific research by reading papers, forming hypotheses, writing and running code, conducting experiments, analyzing results, and preparing reports. Researchers use it for work in machine learning, biology, physics, and chemistry with remote or local models. Catalogue add-ons extend its scientific workflows through skills and instructions.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add synthetic-sciences/openscience --skill gwas-databasegit clone --depth 1 https://github.com/synthetic-sciences/openscienceWrote 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/synthetic-sciences/openscience/gwas-database)<a href="https://agentmods.dev/skills/synthetic-sciences/openscience/gwas-database"><img src="https://agentmods.dev/badge/skills/synthetic-sciences/openscience/gwas-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/synthetic-sciences/openscience/gwas-database"><img src="https://agentmods.dev/badge/skills/synthetic-sciences/openscience/gwas-database.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00050 | $0.04838 |
| Opus 5.5 | $0.00020 | $0.01935 |
| Sonnet 5.5 | $0.00010 | $0.00968 |
| Haiku 4.5 | $0.00005 | $0.00484 |
Grade A, and why
gwas-database scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
response = requests.get(url, headers={"Content-Type": "application/json"}) Copies of this mod
6 near-identical copies found in the catalogue:
- gwas-database — 97% identical, 7 lines differ
- gwas-database — 97% identical, 7 lines differ
- gwas-database — 97% identical, 13 lines differ
- gwas-database — 92% identical, 10 lines differ
- gwas-database — 92% identical, 10 lines differ
- gwas-database — 92% identical, 10 lines differ
How it starts
The opening of the file, as written. The whole thing — 614 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GWAS Catalog Database
Overview
The GWAS Catalog is a comprehensive repository of published genome-wide association studies maintained by the National Human Genome Research Institute (NHGRI) and the European Bioinformatics Institute (EBI). The catalog contains curated SNP-trait associations from thousands of GWAS publications, including genetic variants, associated traits and diseases, p-values, effect sizes, and full summary statistics for many studies.
When to Use This Skill
This skill should be used when queries involve:
- Genetic variant associations: Finding SNPs associated with diseases or traits
- SNP lookups: Retrieving information about specific genetic variants (rs IDs)
- Trait/disease searches: Discovering genetic associations for phenotypes
- Gene associations: Finding variants in or near specific genes
- GWAS summary statistics: Accessing complete genome-wide association data
- Study metadata: Retrieving publication and cohort information
- Population genetics: Exploring ancestry-specific associations
- Polygenic risk scores: Identifying variants for risk prediction models
- Functional genomics: Understanding variant effects and genomic context
- Systematic reviews: Comprehensive literature synthesis of genetic associations
Core Capabilities
1. Understanding GWAS Catalog Data Structure
The GWAS Catalog is organized around four core entities:
- Studies: GWAS publications with metadata (PMID, author, cohort details)
- Associations: SNP-trait associations with statistical evidence (p ≤ 5×10⁻⁸)
- Variants: Genetic markers (SNPs) with genomic coordinates and alleles
- Traits: Phenotypes and diseases (mapped to EFO ontology terms)
Key Identifiers:
- Study accessions:
GCSTIDs (e.g., GCST001234) - Variant IDs:
rsnumbers (e.g., rs7903146) orvariant_idformat - Trait IDs: EFO terms (e.g., EFO_0001360 for type 2 diabetes)
- Gene symbols: HGNC approved names (e.g., TCF7L2)
What ships with it
1 file 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 Changed · +6 lines ed766ff41111
- 1mo ago First seen · 608 lines · 50 tokens per session scan A 4f45fdc43ad7
gwas-database is a skill published in the GitHub repository synthetic-sciences/openscience (4,266 stars, last pushed yesterday), licensed Apache-2.0. It adds 50 tokens to every session and 4,838 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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