design-research-experiments
The study-design and orchestration layer for reproducible design research.
What This Library Does
design-research-experiments defines study structure: hypotheses, factors,
blocking, admissible conditions, replications, and artifact flows. It
coordinates how agents, problems, and downstream analysis are connected in a
controlled experimental pipeline.
Highlights
Hypothesis schemas
DOE builders
Condition generation
Run orchestration
Replication control
Artifact export
This library is the methodological control layer of the ecosystem. It is not just another execution utility. It encodes experimental method in software and is where design choices about rigor, admissibility, and reproducibility are made.
Typical Workflow
Define hypotheses, factors, outcomes, and constraints.
Materialize admissible conditions from the chosen DOE strategy.
Bind agent and problem references.
Execute runs and replications under explicit seed policy and budgets.
Export canonical artifacts for analysis and reporting.
Integration With The Ecosystem
The Design Research Collective maintains a modular ecosystem of libraries for studying human and AI design behavior.
design-research-agents implements AI participants, workflows, and tool-using reasoning patterns.
design-research-problems provides benchmark design tasks, prompts, grammars, and evaluators.
design-research-analysis analyzes the traces, event tables, and outcomes generated during studies.
design-research-experiments sits above the stack as the study-design and orchestration layer, defining hypotheses, factors, conditions, replications, and artifact flows across agents, problems, and analysis.
Together these libraries support end-to-end design research pipelines, from study design through execution and interpretation.
