ginkgo-cloud-lab

ginkgo-cloud-lab is a skill for Claude Code, Codex from K-Dense-AI/scientific-agent-skills. It costs 94 tokens per session (2,709 once invoked), scanned A, original, MIT.

A service for submitting and managing laboratory protocols through Ginkgo Bioworks Cloud Lab, a web-based system for remote robotic experiments.

In plain words
What is it for?
Use it to order or manage supported workflows such as mRNA or circRNA synthesis, protein expression and purification, and laboratory quantification or characterization.
Why use it?
It gives researchers a way to request listed protein-production, purification, measurement, and assay workflows without running every step in their own laboratory.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: positional $N argument.

Good fit Use it to order or manage supported workflows such as mRNA or circRNA synthesis, protein expression and purification, and laboratory quantification or characterization.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/k-dense-ai/scientific-agent-skills/ginkgo-cloud-lab
About the project

Scientific Agent Skills is a collection of reusable procedures that give AI agents capabilities for scientific research across areas such as biology, chemistry, medicine, and drug discovery. It is used by researchers and by people building AI scientist workflows with compatible coding agents. The catalogue contains many of the project's skills and supporting instructions.

K-Dense-AI/scientific-agent-skills · 54,777 stars · on GitHub · arxiv.org

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 K-Dense-AI/scientific-agent-skills --skill ginkgo-cloud-lab
Clone the repo
git clone --depth 1 https://github.com/K-Dense-AI/scientific-agent-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 ginkgo-cloud-lab

README.md
[![agentmods](https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/ginkgo-cloud-lab/github.svg)](https://agentmods.dev/skills/k-dense-ai/scientific-agent-skills/ginkgo-cloud-lab)
Your own site
<a href="https://agentmods.dev/skills/k-dense-ai/scientific-agent-skills/ginkgo-cloud-lab"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/ginkgo-cloud-lab/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 ginkgo-cloud-lab

Your own site · 80×15
<a href="https://agentmods.dev/skills/k-dense-ai/scientific-agent-skills/ginkgo-cloud-lab"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/ginkgo-cloud-lab.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 94 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,709 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. Third-party audits
  • Socket pass 2 Oct 2026
  • Snyk pass 2 Oct 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00094 $0.02709
Opus 5.5 $0.00038 $0.01084
Sonnet 5.5 $0.00019 $0.00542
Haiku 4.5 $0.00009 $0.00271

Measured 25d ago against content hash b3675d3ad360, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

ginkgo-cloud-lab 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 25d 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.

Origin

Copies of this mod

2 near-identical copies found in the catalogue:

skills/ginkgo-cloud-lab/SKILL.md · 156 lines

How it starts

The opening of the file, as written. The whole thing — 156 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Ginkgo Cloud Lab

Overview

Ginkgo Cloud Lab (https://cloud.ginkgo.bio) provides remote access to Ginkgo Bioworks' autonomous lab infrastructure. Protocols use Reconfigurable Automation Carts (RACs), modular units with robotic arms and plate transport, across a catalog-advertised fleet of 70+ integrated instruments.

The platform also includes EstiMate, a compatibility and pricing assistant that accepts protocol descriptions, files, or links and returns preliminary estimates for custom workflows.

The catalog is organized into Expression & Purification (in vitro / cell-free / E. coli / Pichia), Characterization & Assay, Method & Target Onboarding, and Specialty. Pick a protocol below, then read its reference file for inputs, outputs, the automated workflow, and ordering details.

Available Protocols

The following prices, availability labels, and turnaround text are a 2026-09-30 catalog snapshot, not a configured quote. References link to the corresponding service terms. Catalog and terms sometimes disagree on days versus business days, input format, or readout scope; resolve those differences in the service order.

Expression & Purification - In vitro

Protocol Readout Price Turnaround Status
IVT mRNA/circRNA Synthesis qPCR (mRNA or circRNA, 384-well) $99/sample up to 12 business days Certified

Expression & Purification - Cell-free (E. coli CFPS)

Protocol Readout Price Turnaround Status
Validate sequence expression Go/no-go titer + purity (up to 1800 bp) $39/sample up to 10 days Certified
Optimize expression conditions DoE across 24 conditions $199/sample up to 11 days Certified
Express + quantify (HiBiT) Luminescence, no purification $39/sample up to 11 days Certified
Express + purify (A280) Strep-tag, A280 yield $149/sample up to 11 days Certified
Express + purify minibinder Strep-tag, A280; confirm LabChip separately $149/sample up to 11 days Certified
Express + purify (A280 + LabChip) Strep-tag, A280 + purity/size $159/sample up to 12 days Certified

Read the full file on GitHub · 156 lines

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. 25d ago Changed · +23 lines · -41 tokens per session b3675d3ad360
  2. 26d ago Changed · +8 lines 5c8f065d9d87
  3. 1mo ago Changed · +18 lines 88ca5a0f1e2d
  4. 1mo ago First seen · 107 lines · 135 tokens per session scan A a42fd6891cad

Subscribe to this mod's changes

ginkgo-cloud-lab is a skill published in the GitHub repository K-Dense-AI/scientific-agent-skills (54,777 stars, last pushed yesterday), licensed MIT. It adds 94 tokens to every session and 2,709 once invoked, about $0.0004 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 2026-08-30.

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