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 AndyZhuang/Opentest --skill tooluniverse-gwas-study-explorergit clone --depth 1 https://github.com/AndyZhuang/OpentestWrote 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/andyzhuang/opentest/tooluniverse-gwas-study-explorer)<a href="https://agentmods.dev/skills/andyzhuang/opentest/tooluniverse-gwas-study-explorer"><img src="https://agentmods.dev/badge/skills/andyzhuang/opentest/tooluniverse-gwas-study-explorer/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/andyzhuang/opentest/tooluniverse-gwas-study-explorer"><img src="https://agentmods.dev/badge/skills/andyzhuang/opentest/tooluniverse-gwas-study-explorer.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 | $0.00088 | $0.02709 |
| Opus 5 | $0.00044 | $0.01354 |
| Sonnet 5 | $0.00018 | $0.00542 |
| Haiku 4.5 | $0.00009 | $0.00271 |
Grade A, and why
tooluniverse-gwas-study-explorer 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 8d 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.
How it starts
The opening of the file, as written. The whole thing — 343 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GWAS Study Deep Dive & Meta-Analysis
Compare GWAS studies, perform meta-analyses, and assess replication across cohorts
Overview
The GWAS Study Deep Dive & Meta-Analysis skill enables comprehensive comparison of genome-wide association studies (GWAS) for the same trait, meta-analysis of genetic loci across studies, and systematic assessment of replication and study quality. It integrates data from the NHGRI-EBI GWAS Catalog and Open Targets Genetics to provide a complete picture of the genetic architecture of complex traits.
Key Capabilities
- Study Comparison: Compare all GWAS studies for a trait, assessing sample sizes, ancestries, and platforms
- Meta-Analysis: Aggregate effect sizes across studies and calculate heterogeneity statistics
- Replication Assessment: Identify replicated vs novel findings across discovery and replication cohorts
- Quality Evaluation: Assess statistical power, ancestry diversity, and data availability
Use Cases
1. Comprehensive Trait Analysis
Scenario: "I want to understand all available GWAS data for type 2 diabetes"
Workflow:
- Search for all T2D studies in GWAS Catalog
- Filter by sample size and ancestry
- Extract top associations from each study
- Identify consistently replicated loci
- Assess ancestry-specific effects
Outcome: Complete landscape of T2D genetics with replicated findings and population-specific signals
2. Locus-Specific Meta-Analysis
Scenario: "Is the TCF7L2 association with T2D consistent across all studies?"
Workflow:
- Retrieve all TCF7L2 (rs7903146) associations for T2D
- Calculate combined effect size and p-value
- Assess heterogeneity (I² statistic)
- Generate forest plot data
- Interpret heterogeneity level
Outcome: Quantitative assessment of effect size consistency with heterogeneity interpretation
3. Replication Analysis
Scenario: "Which findings from the discovery cohort replicated in the independent sample?"
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.
- 8d ago First seen · 343 lines · 88 tokens per session scan A fd47a721fe88
tooluniverse-gwas-study-explorer is a skill published in the GitHub repository AndyZhuang/Opentest (22 stars, last pushed 6mo ago), licensed MIT. It adds 88 tokens to every session and 2,709 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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