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 romeo111/OpenOnco --skill skillgit clone --depth 1 https://github.com/romeo111/OpenOncoWrote 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/romeo111/openonco/skill)<a href="https://agentmods.dev/skills/romeo111/openonco/skill"><img src="https://agentmods.dev/badge/skills/romeo111/openonco/skill/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/romeo111/openonco/skill"><img src="https://agentmods.dev/badge/skills/romeo111/openonco/skill.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 | $0.00146 | $0.01783 |
| Opus 5.5 | $0.00058 | $0.00713 |
| Sonnet 5.5 | $0.00029 | $0.00357 |
| Haiku 4.5 | $0.00015 | $0.00178 |
Grade A, and why
cancer-research 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 1mo 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 — 171 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cancer Research — Maximum Life Extension Treatment Planner
Purpose
This skill performs deep, systematic research into cancer treatment options for a given cancer type. It produces a comprehensive, evidence-ranked treatment plan that maximizes patient life extension, drawing from established protocols, clinical trials, emerging therapies, and cutting-edge research.
IMPORTANT MEDICAL DISCLAIMER: This skill generates research-grade information summaries. All output must include a prominent disclaimer that this is NOT medical advice and patients must consult their oncology team before making any treatment decisions. This tool is for research and educational purposes only.
Workflow
Step 1: Parse the Input
Extract from the user's query:
- Cancer type (required) — e.g., "pancreatic adenocarcinoma", "NSCLC", "triple-negative breast cancer"
- Stage (if provided) — I through IV, or specific substaging
- Molecular markers (if provided) — e.g., EGFR+, HER2+, BRCA1/2, MSI-H, PD-L1 expression, KRAS G12C
- Patient context (if provided) — age range, prior treatments, comorbidities
- Country/region (if provided) — affects clinical trial availability and drug approvals
If the user provides only a cancer type, proceed with a general overview across all stages. Ask clarifying questions ONLY if the cancer type itself is ambiguous.
Step 2: Research Strategy
Perform web searches across multiple evidence tiers. Use 10–20 searches to build a comprehensive picture. Search categories:
Tier 1 — Standard of Care (SoC)
Search for NCCN guidelines, ESMO guidelines, and current first-line protocols. Example queries:
[cancer type] NCCN guidelines 2025 2026[cancer type] standard of care first line treatment[cancer type] stage [N] treatment protocol
Tier 2 — Approved Targeted & Immunotherapies
Search for FDA/EMA-approved targeted therapies and immunotherapies.
[cancer type] approved targeted therapy 2025 2026[cancer type] immunotherapy checkpoint inhibitor results[cancer type] [known molecular marker] targeted therapy
What ships with it
1 file 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.
- 1mo ago First seen · 171 lines · 146 tokens per session scan A 11cd5565b9cc
cancer-research is a skill published in the GitHub repository romeo111/OpenOnco (2 stars, last pushed today), licensed MIT. It adds 146 tokens to every session and 1,783 once invoked, about $0.0006 per session on Opus 5.5. 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 2026-08-31.
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