Design and run controlled agent behavior experiments with baselines and variants.
npx skills add https://github.com/dylan-conlin/orch-go --skill experiment-dylan-conlin
Please help me install this Agent Skill. Skill: experiment Source: https://github.com/dylan-conlin/orch-go/tree/main/skills/src/worker/experiment Command: npx skills add https://github.com/dylan-conlin/orch-go --skill experiment-dylan-conlin
This skill enables teams to rigorously test hypotheses about how constraints affect agent behavior through controlled experiments, delivering reproducible results and structured guidance for next steps.
Define your hypothesis, design a bare baseline and variants, then run skillc test to execute trials and compile the results.
High-intent search queries and answers about installing and using this skill.
To measure causal effects on agent behavior, you can run controlled experiments with repeatable baselines and variants. This skill isolates variables across multiple runs to build robust evidence of how specific constraints affect outcomes.
Designing controlled experiments for AI agents requires articulating a hypothesis, establishing a bare baseline, and creating constrained variants. You then execute trials and compile run data to identify causal relationships in agent behavior.
Reproducibility when testing model configurations is ensured by maintaining repeatable baselines and running multiple trials per variant. This structured approach generates traceable artifacts and robust evidence for your findings.
Yes, you can test multiple hypotheses and constraints across different agent runs. The skill applies to experiments that vary hypotheses, constraints, and model configurations to identify and measure causal relationships in behavior.
To structure uncertainty after an agent experiment, the skill requires a structured uncertainty section in the deliverables. This analyzes per-indicator detection rates and assembles a narrative to guide subsequent work and next steps.
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