Agent skill · Data & Analytics

mobisys-reproducibility

Use when strengthening MobiSys reproducibility evidence — capturing device, SoC, OS build, framework and model versions, power-instrument setup, seeds, and thermal conditions so an on-device result survives a different phone, deciding what data and firmware can legally ship, and keeping the paper consistent with the artifact for the ACM badge pipeline.

brycew6m4,252★ · +31/wk · 3 repos on radarProfile →
claude-codeMIT
Install
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill mobisys-reproducibility --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 4 KB
Bundled scripts: none
Path: MobiSys-Skills/skills/mobisys-reproducibility/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 909 · +31 this week
Language: Stata
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# MobiSys Reproducibility Use this before submission and again before the artifact-evaluation deadline. On-device results are fragile across hardware and framework versions, so reproducibility at MobiSys is mostly about **provenance**: recording enough of the device and measurement context that someone on a different phone can rebuild the result. ## Evidence map - Map each latency, energy, throughput, and accuracy claim to a verifiable location in the paper, appendix, or artifact package. - For each on-device result, record device model, SoC, OS build, framework/runtime version, model checkpoint hash, power source, ambient temperature, and thermal state at run start. - Record the power-instrument setup and the energy boundary so an energy figure can be re-derived rather than trusted. - For stochastic results, report seeds, repeated runs, and the spread; a single number from a single phone is not reproducible evidence. - Explain missing data, firmware, or hardware honestly, and describe how a reader could reproduce the result in principle on a different device. - Keep the artifact consistent with the manuscript; a number in the PDF that the artifact cannot regenerate is a review-ris

What's inside
Steps it walks through
  1. Evidence map
  2. What survives a different device
  3. Vignette: an on-device inference paper
  4. Degrees of reproducibility
  5. Legal and privacy provenance
  6. Output format
More from Awesome-Journal-Skills
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About this skill
What does the mobisys-reproducibility skill do?

Use when strengthening MobiSys reproducibility evidence — capturing device, SoC, OS build, framework and model versions, power-instrument setup, seeds, and thermal conditions so an on-device result survives a different phone, deciding what data and firmware can legally ship, and keeping the paper consistent with the artifact for the ACM badge pipeline.

How do I install it?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill mobisys-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.

Keep going