agentmods.dev

fit-dose-response

fit-dose-response is a command for Claude Code from zamushwani/biomedical-ai-skills. It costs 35 tokens per session (323 once invoked), scanned A, original, MIT.

A command for fitting drug dose-response curves from cell-viability measurements and calculating IC50 and AUC. IC50 is the concentration that reduces viability by half; AUC summarizes the whole response curve.

In plain words
What is it for?
Use it to analyze viability across drug concentrations, compare drug sensitivity, and report AUC, IC50 with confidence intervals, convergence status, and fitted limits.
Why use it?
It helps avoid misleading results when a curve never reaches 50% inhibition or when the statistical fit fails to converge. It also checks that fitted viability limits stay realistic.

Command for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: positional $N argument.

not rated 1repo 1mo ago A scan 35 tokens original MIT

Good fit Use it to analyze viability across drug concentrations, compare drug sensitivity, and report AUC, IC50 with confidence intervals, convergence status, and fitted limits.

Compare 6 commands from other repositories ↓
Install with agentmods
npx agentmods add commands/zamushwani/biomedical-ai-skills/fit-dose-response
View source ↗ zamushwani/biomedical-ai-skills
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.

Clone the repo
git clone --depth 1 https://github.com/zamushwani/biomedical-ai-skills

Made for: Claude Code.

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 fit-dose-response

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

agentmods 80×15 button for fit-dose-response

Your own site · 80×15
<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>
Per session 35 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 323 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 $0.00035 $0.00323
Opus 5.5 $0.00014 $0.00129
Sonnet 5.5 $0.00007 $0.00065
Haiku 4.5 $0.00003 $0.00032

Measured 2mo ago against content hash dfa7ae6ff84b, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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 2mo 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.

.claude/commands/fit-dose-response.md · 20 lines

What it actually says

Fit dose-response curves for $0.

Follow the drug-response skill. The parts that are usually got wrong:

  1. 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.
  2. Check convergence. drc stores it as a logical in fit$fit$convergence where TRUE means converged — not the optim == 0 convention. Use isTRUE(fit$fit$convergence).
  3. Fit on a log concentration scale (LL2.4), since screens span orders of magnitude.
  4. Constrain the asymptotes. Unconstrained fits produce negative viability or a 130% upper asymptote.
  5. Flag extrapolated IC50s. drc will 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.

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. 2mo ago First seen · 20 lines · 35 tokens per session scan A dfa7ae6ff84b

Subscribe to this mod's changes

fit-dose-response is a command published in the GitHub repository zamushwani/biomedical-ai-skills (1 stars, last pushed 1mo ago), licensed MIT. It adds 35 tokens to every session and 323 once invoked, about $0.0001 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.

DESeq2Scientificai-agentai-skillsbioinformaticscancer-genomicscancer-research
Related

fit-dose-response compared with commands from other repositories

fit-dose-response next to 6 commands from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
fit-dose-responsezamushwani/biomedical-ai-skillsCommand11mo agoMITA35Claude Code
readaipoch/medical-research-skillsCommand2.0k1mo agoMITA0Claude Code
feedaipoch/medical-research-skillsCommand2.0k1mo agoMITA0Claude Code
annotateHERRY423/CellTypePilotCommand62mo agoMITA16Claude Code
criticHERRY423/CellTypePilotCommand62mo agoMITA14Claude Code
ctp-inspectHERRY423/CellTypePilotCommand62mo agoMITA16Claude Code
faostat-country-profileberba-q/faostat-skillsCommand106mo agoMITA10Claude Code