icra-experiments
Use when designing or auditing the experimental section of an ICRA paper — real-robot versus simulation-only evidence, trial counts and success-rate reporting, task distributions and resets, baseline fairness on shared hardware, sim-to-real transfer claims, failure-mode analysis, and the statistics robotics reviewers actually expect.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill icra-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.
# ICRA Experiments Experimental evidence is where ICRA reviews are won and lost. The community's core suspicion is the cherry-picked demo: one lucky run, filmed once, presented as capability. The experiments section exists to prove the demo was not luck. ## The evidence ladder Climb as high as the claim requires; state the rung explicitly in the paper. | Rung | Evidence | Supports claims like | |---|---|---| | 1 | Simulation only, single environment | "the formulation is feasible" | | 2 | Simulation, randomized dynamics/scenes | "the method is robust in sim" | | 3 | Real robot, controlled lab task | "works on hardware" | | 4 | Real robot, varied objects/terrains/subjects | "generalizes physically" | | 5 | Extended/field deployment, uncontrolled conditions | "works in the world" | Simulation-only papers are not banned at ICRA, but a rung-2 evidence base cannot carry rung-4 language. The mismatch between claim altitude and evidence rung is the single most cited weakness in robotics reviews. If hardware is unreachable, scope the claims to simulation and say why the sim is trustworthy (validated dynamics, established benchmark, physics-accurate contact). ## Trials, resets, and what a s
- The evidence ladder
- Trials, resets, and what a success rate means
- Baseline fairness on hardware
- Sim-to-real claims
- Failure analysis as a first-class section
- Ablations with hardware budgets
- Statistics that fit robotics sample sizes
- Pre-deadline experiment audit
- Output format
What does the icra-experiments skill do?
Use when designing or auditing the experimental section of an ICRA paper — real-robot versus simulation-only evidence, trial counts and success-rate reporting, task distributions and resets, baseline fairness on shared hardware, sim-to-real transfer claims, failure-mode analysis, and the statistics robotics reviewers actually expect.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill icra-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.