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-cancer-variant-interpretationgit 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-cancer-variant-interpretation)<a href="https://agentmods.dev/skills/andyzhuang/opentest/tooluniverse-cancer-variant-interpretation"><img src="https://agentmods.dev/badge/skills/andyzhuang/opentest/tooluniverse-cancer-variant-interpretation/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-cancer-variant-interpretation"><img src="https://agentmods.dev/badge/skills/andyzhuang/opentest/tooluniverse-cancer-variant-interpretation.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 | $0.09248 |
| Opus 5 | $0.00069 | $0.04624 |
| Sonnet 5 | $0.00028 | $0.01850 |
| Haiku 4.5 | $0.00014 | $0.00925 |
Grade A, and why
tooluniverse-cancer-variant-interpretation 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 — 972 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cancer Variant Interpretation for Precision Oncology
Comprehensive clinical interpretation of somatic mutations in cancer. Transforms a gene + variant input into an actionable precision oncology report covering clinical evidence, therapeutic options, resistance mechanisms, clinical trials, and prognostic implications.
KEY PRINCIPLES:
- Report-first approach - Create report file FIRST, then populate progressively
- Evidence-graded - Every recommendation has an evidence tier (T1-T4)
- Actionable output - Prioritized treatment options, not data dumps
- Clinical focus - Answer "what should we treat with?" not "what databases exist?"
- Resistance-aware - Always check for known resistance mechanisms
- Cancer-type specific - Tailor all recommendations to the patient's cancer type when provided
- Source-referenced - Every statement must cite the tool/database source
- English-first queries - Always use English terms in tool calls (gene names, drug names, cancer types), even if the user writes in another language. Respond in the user's language
When to Use
Apply when user asks:
- "What treatments exist for EGFR L858R in lung cancer?"
- "Patient has BRAF V600E melanoma - what are the options?"
- "Is KRAS G12C targetable?"
- "Patient progressed on osimertinib - what's next?"
- "What clinical trials are available for PIK3CA E545K?"
- "Interpret this somatic mutation: TP53 R273H"
- "Molecular tumor board: EGFR exon 19 deletion, NSCLC"
Input Parsing
Required: Gene symbol + variant notation Optional: Cancer type (improves specificity)
Accepted Input Formats
| Format | Example | How to Parse |
|---|---|---|
| Gene + amino acid change | EGFR L858R | gene=EGFR, variant=L858R |
| Gene + HGVS protein | BRAF p.V600E | gene=BRAF, variant=V600E |
| Gene + exon notation | EGFR exon 19 deletion | gene=EGFR, variant=exon 19 deletion |
| Gene + fusion | EML4-ALK fusion | gene=ALK, variant=EML4-ALK |
| Gene + amplification | HER2 amplification | gene=ERBB2, variant=amplification |
| Full query with cancer | "EGFR L858R in lung adenocarcinoma" | gene=EGFR, variant=L858R, cancer=lung adenocarcinoma |
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 · 972 lines · 138 tokens per session scan A e1982bcd2a27
tooluniverse-cancer-variant-interpretation is a skill published in the GitHub repository AndyZhuang/Opentest (22 stars, last pushed 6mo ago), licensed MIT. It adds 138 tokens to every session and 9,248 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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