iros-reproducibility
Use when strengthening IROS reproducibility evidence — splitting rerunnable claims from auditable-only real-robot claims, the hardware specification ledger, calibration and parameter disclosure, log capture discipline, honest code/data availability statements, and sim-to-real accounting, all inside a page budget with no supplementary PDF.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill iros-reproducibility --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.
# IROS Reproducibility Use this before submission and again before camera-ready. Robotics reproducibility is not the same as ML reproducibility: a reader usually cannot rerun your robot, so the goal is to make every claim either **rerunnable** (code/sim someone can execute) or **auditable** (logs and specs detailed enough to check), and to be honest about which is which. ## Evidence map - Split each claim into rerunnable or auditable. A simulation result should be rerunnable; a real-robot reliability number is auditable through logs and a stated protocol, not rerunnable by a reader. - For the **rerunnable** part: pin dependencies, seeds, configs, and an entry point; state the hardware it assumes. - For the **auditable** part: give the hardware ledger, calibration, parameters, trial protocol, resets, and representative logs. - Report the **sim-to-real gap** explicitly; never let simulation numbers stand in for real ones. - Write an **honest availability statement**: what code and data are released, what is withheld and why (proprietary hardware, safety, licensing), and how a reader could approximate reproduction. - Keep it all in the **body** — there is no supplementary PDF to park
- Evidence map
- Rerunnable-versus-auditable table
- The hardware specification ledger
- Vignette: a manipulation-reliability paper
- Output format
What does the iros-reproducibility skill do?
Use when strengthening IROS reproducibility evidence — splitting rerunnable claims from auditable-only real-robot claims, the hardware specification ledger, calibration and parameter disclosure, log capture discipline, honest code/data availability statements, and sim-to-real accounting, all inside a page budget with no supplementary PDF.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill iros-reproducibility --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.