Borrowing it
Nothing to install: this file belongs to 45ck/open-genome-agent. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/45ck/open-genome-agent/main/.agents/skills/pharmacogenomics/SKILL.mdgit clone --depth 1 https://github.com/45ck/open-genome-agentWrote 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/45ck/open-genome-agent/pharmacogenomics)<a href="https://agentmods.dev/skills/45ck/open-genome-agent/pharmacogenomics"><img src="https://agentmods.dev/badge/skills/45ck/open-genome-agent/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.
<a href="https://agentmods.dev/skills/45ck/open-genome-agent/pharmacogenomics"><img src="https://agentmods.dev/badge/skills/45ck/open-genome-agent/pharmacogenomics.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 | $0.00032 | $0.00259 |
| Opus 5 | $0.00016 | $0.00130 |
| Sonnet 5 | $0.00006 | $0.00052 |
| Haiku 4.5 | $0.00003 | $0.00026 |
Grade B, and why
pharmacogenomics scanned grade B 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 9d 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.
Subtle steeringmediumPrompt injection
Instructions that bias recommendations or shape behaviour without the user noticing.
- Never tell the user to change medication directly from this output. What it actually says
Pharmacogenomics
Generate a clearly separated pharmacogenomics section with conservative language and explicit human-review flags. Use only when the user requests drug-response analysis.
When to use
- the user explicitly requests drug-response or medication-response clues
Do not use when
- the user only wants ancestry or general variant analysis
Expected outputs
pharmacogenomics.json
Goal
Produce a conservative drug-response section that remains clearly separate from diagnosis.
Procedure
- Start from already validated variant or haplotype inputs.
- Present outputs as medication-response clues, not prescriptions.
- Attach strong caveats and a human-review flag to every entry.
- Keep the output in its own artifact and section.
Guardrails
- Never tell the user to change medication directly from this output.
- Never mix pharmacogenomics entries into the same summary bucket as disease findings.
- If genotype-to-phenotype translation is incomplete, say so.
References
See references/README.md for durable notes and scripts/ for deterministic helpers.
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.
- 9d ago First seen · 40 lines · 32 tokens per session scan B 6081687a55af
pharmacogenomics is a skill published in the GitHub repository 45ck/open-genome-agent (4 stars, last pushed 2mo ago), licensed MIT. It adds 32 tokens to every session and 259 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it B with 1 finding (subtle steering). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
biomcp
Search and retrieve biomedical data - genes, variants, clinical trials, diagnostic tests, articles, drugs, diseases, pathways, proteins, adverse events, pharmacogenomics, and phenotype-disease matching. Use for gene function, variant pathogenicity, trials, diagnostics, drug safety, pathway context, disease workups…
biomcp-research
Do biomedical literature and variant research with the BioMCP CLI, and file what you learn about the tool itself as issues in the biomcp repo.
cellxgene-census-query
Query CZ CELLxGENE Census (61M+ cells). Filter by cell type/tissue/disease, retrieve expression data, and integrate with scanpy/PyTorch for population-scale single-cell analysis. Use this skill when: (1) Querying single-cell expression data by cell type, tissue, or disease, (2) Exploring available single-cell datasets…
biological-expert
Expert-level biology, biotechnology, genetics, bioinformatics, and computational biology. Use when the user mentions biology, biotechnology, genetics, bioinformatics, or genomics, or when the task involves Molecular Biology, Genomics & Bioinformatics, Systems Biology, or Data Analysis.
genomics-alignment
Load when computing alignment QC metrics (mapping rate, MAPQ distribution, insert size, duplicate rate, proper-pair rate) from a SAM or BAM file produced by any short-/long-read aligner (BWA / Bowtie2 / Minimap2). Skip when running the alignment step itself; only FASTQ-level QC is needed (use genomics-qc).
genomics-assembly
Load when computing genome-assembly QC metrics — N50/N90, L50/L90, total length, contig count, GC content, longest-contig — from a FASTA produced by any assembler (SPAdes / Megahit / Flye / Canu). Skip when running the assembly itself; assessing alignment quality (use genomics-alignment).