eightmm/codex-science/kdense-ginkgo-cloud-lab
Claude Code and agent skill by eightmm/codex-science
- community
Checking that the SKILL.md file is still in the repository.
Submit and manage protocols on Ginkgo Bioworks Cloud Lab (cloud.ginkgo.bio), a web-based interface for autonomous lab execution on Reconfigurable Automation Carts (RACs). Use when the user wants to run protein expression and purification (cell-free, E. coli, or Pichia), HiBiT or A280 or LabChip quantification, IVT mRNA/circRNA synthesis, thermal shift / developability assays, Echo-MS enzyme or analyte methods, SPR target onboarding, fluorescent pixel art, or otherwise interact with Ginkgo Cloud…
Install
npx vskill@latest install eightmm/codex-science/kdense-ginkgo-cloud-labSKILL.md
Kdense Ginkgo Cloud Lab
Use this Codex adapter for the pinned upstream scientific skill.
Catalog status
- Status:
active - Source:
kdense - Audit reasons: none
- Upstream license:
MIT license - Inventory:
../../inventory.json - Upstream instructions:
../../../vendor/scientific-agent-skills/skills/ginkgo-cloud-lab/SKILL.md
Procedure
- Resolve the plugin root as three directories above this skill directory.
- Run
"<plugin-root>/scripts/python_runtime.sh" "<plugin-root>/scripts/search_skills.py" --name kdense-ginkgo-cloud-laband verify the record's status, reasons, and source path and the source's pinned commit (empty for first-partycxskills) from its output instead of readinginventory.json. - Read the upstream instructions only after confirming this record is still active in the current inventory.
- Treat upstream frontmatter as source metadata, not as Codex configuration. Follow the instruction body only where it is compatible with available Codex tools and the current user-approved plan.
- Treat tools named for another agent runtime as capability requests. Map them to an available Codex tool only when the behavior is equivalent; otherwise report the unavailable capability.
- Ask before credentials, package installation, new network hosts, remote compute, writes, paid services, destructive actions, or imported executable code.
- Use
$science-provenancefor produced scientific outputs and$science-reviewbefore presenting scientific claims.
Physical-experiment and remote-lab safety (mandatory)
This skill can drive real laboratory hardware or submit paid remote-lab work. Beyond the general gates, before any physical or remote action:
- Get explicit user approval to operate real devices or submit an order; never
actuate hardware or send a job on your own initiative.
- Simulate or dry-run first and show the user the exact planned steps.
- Confirm samples, reagents, and the biosafety/containment level; refuse
out-of-scope, hazardous, or dual-use protocols.
- Verify instrument state and the emergency-stop/abort path before starting, and
stop immediately on any anomaly.
- For cloud/remote labs, surface the cost and get billing approval before
submitting.
Boundaries
- This wrapper does not grant credentials, network access, package installation, or script execution.
- Do not change an inactive record to active from inside a research task.
- Preserve failures, uncertainty, source identifiers, and licensing constraints.
Security
- Security scanPassed, 100 of 100Pattern checks on the skill's files.
- Model reviewNot runA model review is scheduled for the next rescan.
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingcatalog/codex-skills/kdense-ginkgo-cloud-lab/SKILL.md
Popularity
- Repository stars
- 4
- 7-day trend score
- 12
Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.
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