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 zamushwani/biomedical-ai-skills --skill radiotherapy-responsegit clone --depth 1 https://github.com/zamushwani/biomedical-ai-skillsWrote 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/zamushwani/biomedical-ai-skills/radiotherapy-response)<a href="https://agentmods.dev/skills/zamushwani/biomedical-ai-skills/radiotherapy-response"><img src="https://agentmods.dev/badge/skills/zamushwani/biomedical-ai-skills/radiotherapy-response/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/zamushwani/biomedical-ai-skills/radiotherapy-response"><img src="https://agentmods.dev/badge/skills/zamushwani/biomedical-ai-skills/radiotherapy-response.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 | $0.00000 | $0.03262 |
| Opus 5 | $0.00000 | $0.01631 |
| Sonnet 5 | $0.00000 | $0.00652 |
| Haiku 4.5 | $0.00000 | $0.00326 |
Grade A, and why
radiotherapy-response 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 12d 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 — 304 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Radiotherapy Response
Genomic predictors of radiation response: DNA damage repair pathway profiling, the Radiosensitivity Index and the Genomic-Adjusted Radiation Dose built on it, post-irradiation immune activation signatures, and an honest account of what the abscopal effect can and cannot be predicted from.
When to Use This Skill
Activate when the user requests:
- Radiosensitivity Index (RSI) or Genomic-Adjusted Radiation Dose (GARD)
- DNA damage repair gene or pathway profiling
- Predicting response to radiotherapy from expression data
- Immune activation signatures after irradiation
- Abscopal effect biomarkers
- Combining radiotherapy dose with a genomic covariate
Inputs
| Data Type | Form | Note |
|---|---|---|
| Expression | genes x samples | RSI needs ranks, not raw values |
| Dose / fractionation | total dose, dose per fraction | required for GARD, not RSI |
| Somatic variants | VCF or MAF | DDR gene alterations |
| Clinical | local control, PFS, OS, site irradiated | evaluation only |
Environment
Versions verified 2026-08.
BiocManager::install("RadioGx") # 2.16.0 radiation pharmacogenomics
install.packages("msigdbr") # 26.1.1 gene set collections
NO PACKAGE IMPLEMENTS RSI OR GARD.
Checked CRAN, Bioconductor and PyPI: there is no maintained implementation.
You write the model yourself from the publication, which means the gene list,
the coefficients and the rank transform are your responsibility to get right.
That is the main risk in this skill, so the exact model is written out below.
RadioGx (2.16.0) is the sibling of PharmacoGx for radiation response and
holds curated radiogenomic datasets. It is where to get training or
validation data, not an RSI implementation.
msigdbr changed its version scheme. The history runs 10.0.2 -> 24.1.0 ->
25.1.x -> 26.1.1: it is now CALENDAR versioned against the MSigDB release
year, not semantic. A dependency pinned as ">= 7.5.1" or logic that compares
major versions numerically will behave oddly. Pin an exact version and
record which MSigDB release it carries.
What ships with it
4 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.
- 12d ago First seen · 304 lines · 0 tokens per session scan A c553c9b462c3
radiotherapy-response is a skill published in the GitHub repository zamushwani/biomedical-ai-skills (1 stars, last pushed 13d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 3,262 tokens. 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 2026-08-31.
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