tooluniverse-pharmacogenomics

tooluniverse-pharmacogenomics is a skill for Claude Code from mims-harvard/ToolUniverse. It costs 80 tokens per session (5,371 once invoked), scanned A, original, Apache-2.0.

A pharmacogenomics research workflow that studies how a person's genes can affect drug response or dosing. It combines gene-drug guidance, variant annotations, metabolizer status, allele frequencies, and FDA biomarker information.

In plain words
What is it for?
Use it to research CPIC recommendations, gene-drug pairs, PharmGKB annotations, FDA pharmacogenomic labels, and metabolizer status for specific variants or genes.
Why use it?
The same medicine can work differently or cause different risks depending on genetic variation. This workflow helps connect a genotype to published dosing and treatment guidance.

Skill for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter.

Part of the tooluniverse plugin — 140 skills, 8 commands, 1 agent, 1 hook, 1 MCP server shipped together

Good fit Use it to research CPIC recommendations, gene-drug pairs, PharmGKB annotations, FDA pharmacogenomic labels, and metabolizer status for specific variants or genes.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/mims-harvard/tooluniverse/tooluniverse-pharmacogenomics
About the project

ToolUniverse is a collection of tools, interfaces, and supporting components for building AI systems that perform scientific work. It is for developers creating AI scientist agents that use APIs, databases, machine-learning tools, and domain-specific utilities. The catalogue includes skills, commands, an MCP server, an agent, and a hook for working with the ecosystem.

mims-harvard/ToolUniverse · 1,680 stars · on GitHub · aiscientist.tools

Install

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.

Any agent
npx skills add mims-harvard/ToolUniverse --skill tooluniverse-pharmacogenomics
Clone the repo
git clone --depth 1 https://github.com/mims-harvard/ToolUniverse

Made for: Claude Code.

Or install tooluniverse, the plugin that ships this one along with the rest of its 140 skills, 8 commands, 1 agent, 1 hook, 1 MCP server.

Wrote 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.

agentmods badge for tooluniverse-pharmacogenomics

README.md
[![agentmods](https://agentmods.dev/badge/skills/mims-harvard/tooluniverse/tooluniverse-pharmacogenomics/github.svg)](https://agentmods.dev/skills/mims-harvard/tooluniverse/tooluniverse-pharmacogenomics)
Your own site
<a href="https://agentmods.dev/skills/mims-harvard/tooluniverse/tooluniverse-pharmacogenomics"><img src="https://agentmods.dev/badge/skills/mims-harvard/tooluniverse/tooluniverse-pharmacogenomics/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.

agentmods 80×15 button for tooluniverse-pharmacogenomics

Your own site · 80×15
<a href="https://agentmods.dev/skills/mims-harvard/tooluniverse/tooluniverse-pharmacogenomics"><img src="https://agentmods.dev/badge/skills/mims-harvard/tooluniverse/tooluniverse-pharmacogenomics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 80 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 5,371 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00080 $0.05371
Opus 5 $0.00040 $0.02686
Sonnet 5 $0.00016 $0.01074
Haiku 4.5 $0.00008 $0.00537

Measured 8d ago against content hash fa25cae06e0d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

tooluniverse-pharmacogenomics 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.

plugin/skills/tooluniverse-pharmacogenomics/SKILL.md · 275 lines

How it starts

The opening of the file, as written. The whole thing — 275 lines — stays where its author put it; the contents beside it link to each section on GitHub.

COMPUTE, DON'T DESCRIBE

When analysis requires computation (statistics, data processing, scoring, enrichment), write and run Python code via Bash. Don't describe what you would do — execute it and report actual results. Use ToolUniverse tools to retrieve data, then Python (pandas, scipy, statsmodels, matplotlib) to analyze it.

Pharmacogenomics (PGx) Research Skill

Systematic PGx analysis: resolve gene-drug pairs, retrieve CPIC dosing guidelines, annotate alleles and variants with PharmGKB, check FDA PGx biomarker labeling, and generate evidence-graded clinical recommendations.

When to Use

  • "What CPIC guidelines exist for CYP2D6?"
  • "Get dosing recommendations for codeine based on CYP2D6 poor metabolizer status"
  • "Which drugs have FDA pharmacogenomic biomarkers for CYP2C19?"
  • "Find PharmGKB clinical annotations for rs1799853"
  • "Is this patient's CYP2D6 genotype relevant to tamoxifen dosing?"
  • "What is the functional status of CYP2D6*4?"
  • "List all CPIC level A gene-drug pairs for CYP2D6"

Workflow Overview

Input (gene/drug/variant/phenotype)
  |
  v
Phase 0: Disambiguation (resolve gene symbols, drug names, rsIDs)
  |
  v
Phase 1: Gene-Drug Pair Identification (CPIC pairs + evidence levels)
  |
  v
Phase 2: Guideline & Dosing Retrieval (CPIC recommendations + PharmGKB)
  |
  v
Phase 3: Allele & Variant Annotation (star alleles, function, activity scores)
  |
  v
Phase 4: FDA Biomarker Labeling (regulatory PGx status)
  |
  v
Phase 5: Cross-Database Enrichment (EpiGraphDB, DGIdb, OpenTargets PGx)
  |
  v
Phase 6: Report (evidence-graded clinical summary)

Phase 0: Disambiguation

Resolve user input to canonical identifiers before querying PGx databases.

PharmGKB_search_genes: query (string REQUIRED, e.g., "CYP2D6"). Returns {status, data: [{id, symbol, name}]}.

  • Use to get PharmGKB gene accession ID (e.g., "PA128" for CYP2D6).

PharmGKB_search_drugs: query (string REQUIRED, e.g., "codeine"). Returns {status, data: [{id, name, types}]}.

  • Use to get PharmGKB chemical ID (e.g., "PA449088" for codeine).

Read the full file on GitHub · 275 lines

Changes

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.

  1. 8d ago First seen · 275 lines · 80 tokens per session scan A fa25cae06e0d

Subscribe to this mod's changes

tooluniverse-pharmacogenomics is a skill published in the GitHub repository mims-harvard/ToolUniverse (1,680 stars, last pushed 3d ago), licensed Apache-2.0. It adds 80 tokens to every session and 5,371 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.

Related

Other skills, from other repositories

nanoresearch-writing

Draft a LaTeX research paper from all previous stage outputs.

OpenRaiser/NanoResearch · 17 tokens

construct-toy-examples

Generate and analyze simpler examples that satisfy both the assumptions and the conclusion of a theorem statement or subgoal. Use when you are stuck in reasoning and need simpler examples to regain traction, or when you want to see where the assumptions take effect and gain intuition.

frenzymath/Danus · 57 tokens

obtain-immediate-conclusions

Derive immediate mathematical consequences from a theorem statement or subgoal. Use when starting a new problem, branch, or subgoal, or when cheap progress or a cleaner reformulation is needed before deeper proof search.

frenzymath/Danus · 49 tokens

astro-dso-doc

Generates a complete, polished HTML documentation page, a processing checklist, an AstroBin post JSON, a PixInsight process icon set (XPSM), AND a ready-to-paste PixInsight project Description field for a deep-sky object (DSO) astrophotography project. Use this skill whenever the user mentions astrophotography, a DSO…

jjmartres/ai-coding-agents · 244 tokens

intermediate-outputs

Use this skill when working with circuit discovery in language models, mechanistic interpretability, activation patching, attribution patching, or Layer-wise Relevance Propagation (LRP) for neural network analysis.

zjunlp/Mechanist · 45 tokens

clip-dissect

Use this skill when you need to automatically describe or interpret the functionality of individual neurons in deep neural networks (DNNs) using CLIP-based semantic analysis, perform mechanistic interpretability research on vision models, dissect convolutional or transformer-based image classifiers, identify what…

zjunlp/Mechanist · 76 tokens