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 GPTomics/bioSkills --skill multiplicity-graphicalgit clone --depth 1 https://github.com/GPTomics/bioSkillsWrote 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/gptomics/bioskills/multiplicity-graphical)<a href="https://agentmods.dev/skills/gptomics/bioskills/multiplicity-graphical"><img src="https://agentmods.dev/badge/skills/gptomics/bioskills/multiplicity-graphical/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/gptomics/bioskills/multiplicity-graphical"><img src="https://agentmods.dev/badge/skills/gptomics/bioskills/multiplicity-graphical.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 | $0.00138 | $0.06204 |
| Opus 5 | $0.00069 | $0.03102 |
| Sonnet 5 | $0.00028 | $0.01241 |
| Haiku 4.5 | $0.00014 | $0.00620 |
Grade A, and why
bio-clinical-biostatistics-multiplicity-graphical 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 6d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- bio-clinical-biostatistics-multiplicity-graphical — 97% identical, 12 lines differ
How it starts
The opening of the file, as written. The whole thing — 346 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Version Compatibility
Reference examples tested with: R gMCP 0.8.16+, graphicalMCP 0.2+, gatekeeping, multcomp, multxpert; Python statsmodels 0.14+ for basic FDR/FWER methods.
Before using code patterns, verify installed versions match. If versions differ:
- R:
packageVersion('<pkg>')then?function_name - Python:
pip show <package>thenhelp(module.function)
If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.
Multiplicity Control for Confirmatory Trials
"Design the multiplicity strategy for my trial" -> Specify a closed-testing procedure (graphical, gatekeeping, hierarchical, or step-down Bonferroni-Holm) that controls family-wise error rate at the trial-wide level across primary endpoints, key secondary endpoints, and subgroup analyses, with provable strong FWER control.
The Foundational Theorem -- Closed Testing Is Necessary
Marcus, Peritz & Gabriel 1976 Biometrika 63:655: a hypothesis H_I (I ⊆ {1,...,m}) is rejected iff every intersection hypothesis ∩_{J⊇I} H_J is rejected by a valid α-level local test. Strong FWER control holds for ANY choice of local tests.
Goeman, Hemerik & Solari 2021 Ann Stat 49:1218 tightens this: closed testing is not merely sufficient — it is necessary for admissibility under FDP/FWER/k-FWER. Every admissible multiplicity procedure is equivalent to some closed test. Graphical procedures, gatekeepers, Hommel, fixed-sequence, fallback — all are closed tests in disguise.
FWER vs FDR philosophical divide:
- FWER: P(any false positive among m tests) — regulatory standard for confirmatory inference (agency wants to bound per-trial false-positive rate)
- FDR: Expected proportion of false discoveries among rejections — exploratory standard (genomics, fMRI, biomarker screens) where many true positives expected
Confirmatory clinical trials use FWER essentially universally.
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.
- 6d ago First seen · 346 lines · 138 tokens per session scan A e248437589ae
bio-clinical-biostatistics-multiplicity-graphical is a skill published in the GitHub repository GPTomics/bioSkills (1,199 stars, last pushed 25d ago), licensed MIT. It adds 138 tokens to every session and 6,204 once invoked, about $0.0007 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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