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-precision-medicine-stratificationgit 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-precision-medicine-stratification)<a href="https://agentmods.dev/skills/andyzhuang/opentest/tooluniverse-precision-medicine-stratification"><img src="https://agentmods.dev/badge/skills/andyzhuang/opentest/tooluniverse-precision-medicine-stratification/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-precision-medicine-stratification"><img src="https://agentmods.dev/badge/skills/andyzhuang/opentest/tooluniverse-precision-medicine-stratification.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 | $0.00193 | $0.13762 |
| Opus 5 | $0.00097 | $0.06881 |
| Sonnet 5 | $0.00039 | $0.02752 |
| Haiku 4.5 | $0.00019 | $0.01376 |
Grade A, and why
tooluniverse-precision-medicine-stratification 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 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.
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 — 1,144 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Precision Medicine Patient Stratification
Transform patient genomic and clinical profiles into actionable risk stratification, treatment recommendations, and personalized therapeutic strategies. Integrates germline genetics, somatic alterations, pharmacogenomics, pathway biology, and clinical evidence to produce a quantitative risk score with tiered management recommendations.
KEY PRINCIPLES:
- Report-first approach - Create report file FIRST, then populate progressively
- Disease-specific logic - Cancer vs metabolic vs rare disease pipelines diverge at Phase 2
- Multi-level integration - Germline + somatic + expression + clinical data layers
- Evidence-graded - Every finding has an evidence tier (T1-T4)
- Quantitative output - Precision Medicine Risk Score (0-100) with transparent components
- Pharmacogenomic guidance - Drug selection AND dosing recommendations
- Guideline-concordant - Reference NCCN, ACC/AHA, ADA, and other guidelines
- Source-referenced - Every statement cites the tool/database source
- Completeness checklist - Mandatory section showing data availability and analysis coverage
- English-first queries - Always use English terms in tool calls. Respond in user's language
When to Use
Apply when user asks:
- "Stratify this breast cancer patient: ER+/HER2-, BRCA1 mutation, stage II"
- "What is the risk profile for this diabetes patient with HbA1c 8.5 and CYP2C19 poor metabolizer?"
- "NSCLC patient with EGFR L858R, stage IV, TMB 25 - treatment strategy?"
- "Predict prognosis and recommend treatment for this cardiovascular patient"
- "Patient has Marfan syndrome with FBN1 mutation - risk stratification"
- "Alzheimer's risk assessment: APOE e4/e4, family history positive"
- "Personalized treatment plan for type 2 diabetes with genetic risk factors"
- "Which therapy is best for this patient's molecular profile?"
NOT for (use other skills instead):
- Single variant interpretation -> Use
tooluniverse-variant-interpretationortooluniverse-cancer-variant-interpretation - Immunotherapy-specific prediction -> Use
tooluniverse-immunotherapy-response-prediction - Drug safety profiling only -> Use
tooluniverse-adverse-event-detection - Target validation -> Use
tooluniverse-drug-target-validation - Clinical trial search only -> Use
tooluniverse-clinical-trial-matching - Drug-drug interaction analysis only -> Use
tooluniverse-drug-drug-interaction - PRS calculation only -> Use
tooluniverse-polygenic-risk-score
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 · 1,144 lines · 193 tokens per session scan A b90211d88655
tooluniverse-precision-medicine-stratification is a skill published in the GitHub repository AndyZhuang/Opentest (22 stars, last pushed 6mo ago), licensed MIT. It adds 193 tokens to every session and 13,762 once invoked, about $0.0010 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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