hri-experiments
Use when designing or auditing the human-subjects study at the heart of an ACM/IEEE HRI full paper — choosing between/within-subjects designs, running Wizard-of-Oz honestly, powering the sample, reporting statistics with effect sizes and qualitative rigor, selecting validated scales, adding manipulation checks, pre-registering, and meeting HRI's human-participants ethics obligations.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill hri-experiments --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# HRI Experiments The human-subjects study is HRI's currency. A brilliant robot behavior with a broken study fails; a modest behavior with an airtight study can win a Best Paper. HRI reviewers — drawn from psychology and HCI as well as robotics — hold study design to a standard closer to experimental psychology than to a robotics benchmark. This skill covers the design decisions that decide the paper, and HRI's specific ethics obligations. It pairs with the shared reporting kit in [`../../resources/code/README.md`](../../resources/code/README.md). ## Match the evidence to the claim Decide what *kind* of claim you are making, then design to it: | Claim shape | Evidence HRI expects | | --- | --- | | "Robot behavior X changes outcome Y" (causal) | A controlled experiment manipulating X, measuring Y, with a manipulation check and effect sizes | | "People experience the robot as Z" (perception) | A validated instrument for Z, adequate power, and honest CIs | | "This interaction/design works better" | A comparison with a fair baseline and a behavioral or task outcome, ideally shown on video | | "Here is how people make sense of robots" (qualitative) | A rigorous qualitative method (thema
- Match the evidence to the claim
- Choose the design deliberately
- Wizard-of-Oz, done honestly
- Power, sample size, and analysis
- Validated scales and constructs
- Qualitative and mixed methods
- Ethics is not optional at HRI
- Anti-patterns HRI reviewers flag
- Output format
What does the hri-experiments skill do?
Use when designing or auditing the human-subjects study at the heart of an ACM/IEEE HRI full paper — choosing between/within-subjects designs, running Wizard-of-Oz honestly, powering the sample, reporting statistics with effect sizes and qualitative rigor, selecting validated scales, adding manipulation checks, pre-registering, and meeting HRI's human-participants ethics obligations.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill hri-experiments --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From brycewang-stanford/Awesome-Journal-Skills, a repository with 909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.