Active learning experiment loops starter
A framework for discovering, compiling, and validating reusable skills for scientific agents.From the repository description
npx -y skills add ma-compbio-lab/SkillFoundry --skill active-learning-experiment-loops-starterAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
SKILL.md
0.8 KB, 163 tokens by cl100k_base, as published. Nobody here has run it
Active-learning experiment loops Starter
Use this starter when a task lands in the Active-learning experiment loops frontier leaf and the repository has curated resources but no dedicated runtime implementation yet.
What this starter does
- Summarizes the local resource anchors for the leaf.
- Emits a machine-readable starter plan with promotion steps.
- Gives the agent a stable local entry point before a full runtime skill exists.
How to use it
Run python3 skills/robotics-lab-automation-and-scientific-instrumentation/active-learning-experiment-loops-starter/scripts/run_frontier_starter.py --out scratch/frontier/active-learning-experiment-loops-starter.json.
Then inspect refs.md and examples/resource_context.json to promote the starter into a concrete executable workflow.
What ships with it: 7 files
5.3 KB alongside SKILL.md, 2 of them executable
assets/
- README.md105 B
examples/
- README.md140 B
- resource_context.json811 B
scripts/
- run_frontier_starter.pyruns1.4 KB
tests/
- metadata.yaml1.4 KB
- refs.md329 B