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.
git 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/commands/zamushwani/biomedical-ai-skills/fit-dose-response)<a href="https://agentmods.dev/commands/zamushwani/biomedical-ai-skills/fit-dose-response"><img src="https://agentmods.dev/badge/commands/zamushwani/biomedical-ai-skills/fit-dose-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/commands/zamushwani/biomedical-ai-skills/fit-dose-response"><img src="https://agentmods.dev/badge/commands/zamushwani/biomedical-ai-skills/fit-dose-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 | $0.00035 | $0.00323 |
| Opus 5 | $0.00017 | $0.00161 |
| Sonnet 5 | $0.00007 | $0.00065 |
| Haiku 4.5 | $0.00003 | $0.00032 |
Grade A, and why
fit-dose-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.
What it actually says
Fit dose-response curves for $0.
Follow the drug-response skill. The parts that are usually got wrong:
- Report AUC, not IC50, as the primary metric. A drug that plateaus at 60% viability has no IC50 — pipelines substitute the maximum tested concentration, which is not a measurement. AUC is always defined and correlates better with clinical response.
- Check convergence.
drcstores it as a logical infit$fit$convergencewhereTRUEmeans converged — not the optim== 0convention. UseisTRUE(fit$fit$convergence). - Fit on a log concentration scale (
LL2.4), since screens span orders of magnitude. - Constrain the asymptotes. Unconstrained fits produce negative viability or a 130% upper asymptote.
- Flag extrapolated IC50s.
drcwill happily return an ED50 for a curve that never crosses 50% inhibition.
Report per curve: AUC, IC50 with CI (flagged if extrapolated), convergence status, and the fitted asymptotes.
If $0 is empty, ask for the viability data.
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 · 20 lines · 35 tokens per session scan A dfa7ae6ff84b
fit-dose-response is a command published in the GitHub repository zamushwani/biomedical-ai-skills (1 stars, last pushed 13d ago), licensed MIT. It adds 35 tokens to every session and 323 once invoked, about $0.0002 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 2026-08-31.
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