2026-08-09 18:31:46 +00:00
1 changed files with 7 additions and 5 deletions
@@ -1,16 +1,18 @@
 ---
 lineage_type: import
-upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/9c9bd2e9/skills/experimental-design/SKILL.md
-upstream_sha: 9c9bd2e9
-imported_at: 2026-06-26
+upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/991bd993/skills/experimental-design/SKILL.md
+upstream_sha: 991bd993
+imported_at: 2026-08-08
 prompt_class: prompt
 upstream_changes: accepted
 name: experimental-design
-description: Design experiments and studies BEFORE data is collected — choosing a design, randomizing, blocking, and laying out treatment combinations so the results will actually be interpretable. Use whenever someone is planning a study, asks how to assign subjects/samples to groups, mentions randomization, blocking, stratification, controls, factorial or fractional-factorial designs, design of experiments (DOE), screening many factors, response-surface optimization, crossover or repeated-measures or split-plot designs, cluster/group randomization, Latin squares, plate layouts, batch/run-order effects, replication vs. pseudoreplication, or sequential/adaptive/group-sequential designs. Trigger this even for informal phrasings like "how should I set up this experiment", "how do I avoid confounding", "what's the best way to test these 6 factors", or "assign these mice to conditions". For computing the sample size or power once the design is chosen, use statistical-power; for analyzing data already collected, use statistical-analysis.
+description: Design experiments and studies BEFORE data is collected — choosing a design, randomizing, blocking, and laying out treatment combinations so results are interpretable. Use whenever someone is planning a study, asks how to assign subjects/samples to groups, mentions randomization, blocking, stratification, controls, factorial or fractional-factorial designs, design of experiments (DOE), screening many factors, response-surface optimization, crossover or repeated-measures or split-plot designs, cluster/group randomization, Latin squares, plate layouts, batch/run-order effects, replication vs. pseudoreplication, or sequential/adaptive/group-sequential designs. Trigger even for informal phrasings like "how should I set up this experiment", "how do I avoid confounding", "what's the best way to test these 6 factors", or "assign these mice to conditions". For computing the sample size or power once the design is chosen, use statistical-power; for analyzing data already collected, use statistical-analysis.
 allowed-tools: Read Write Edit Bash
 compatibility: Requires Python >=3.10. Scripts use numpy, pandas, and pyDOE3 (DOE matrices). Install with uv as shown below.
 license: MIT license
-metadata: {"version": "1.0", "skill-author": "K-Dense Inc."}
+metadata:
+  version: "1.1"
+  skill-author: K-Dense Inc.
 ---

 # Experimental Design