radiotherapy-response

radiotherapy-response is a skill for Claude Code, Codex from zamushwani/biomedical-ai-skills. It costs 0 tokens per session (3,262 once invoked), scanned A, original, MIT.

A guide to estimating how a tumour may respond to radiotherapy from gene activity, DNA-repair changes, immune signals, and treatment dose. It covers the Radiosensitivity Index and the related Genomic-Adjusted Radiation Dose model.

In plain words
What is it for?
Use it to profile DNA-damage repair pathways, calculate radiosensitivity measures, combine gene data with dose and fractionation, and study immune activation after irradiation. Clinical outcomes are included for evaluation rather than direct prediction.
Why use it?
Radiotherapy response depends on both the tumour’s biology and how treatment is delivered. This helps organise genomic and dose information while making clear which predictions are possible and which are not.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to profile DNA-damage repair pathways, calculate radiosensitivity measures, combine gene data with dose and fractionation, and study immune activation after irradiation. Clinical outcomes are included for evaluation rather than direct prediction.

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Install with agentmods
npx agentmods add skills/zamushwani/biomedical-ai-skills/radiotherapy-response
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 zamushwani/biomedical-ai-skills --skill radiotherapy-response
Clone the repo
git clone --depth 1 https://github.com/zamushwani/biomedical-ai-skills

Made for: Claude Code, Codex.

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 radiotherapy-response

README.md
[![agentmods](https://agentmods.dev/badge/skills/zamushwani/biomedical-ai-skills/radiotherapy-response/github.svg)](https://agentmods.dev/skills/zamushwani/biomedical-ai-skills/radiotherapy-response)
Your own site
<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.

agentmods 80×15 button for radiotherapy-response

Your own site · 80×15
<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>
Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,262 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.
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 $0.00000 $0.03262
Opus 5 $0.00000 $0.01631
Sonnet 5 $0.00000 $0.00652
Haiku 4.5 $0.00000 $0.00326

Measured 12d ago against content hash c553c9b462c3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

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.

The scan reads SKILL.md. This mod also ships 2 executable files (tests/run_all.py, tests/validate_rsi.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/radiotherapy-response/SKILL.md · 304 lines

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.

Read the full file on GitHub · 304 lines

Files

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.

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. 12d ago First seen · 304 lines · 0 tokens per session scan A c553c9b462c3

Subscribe to this mod's changes

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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