Agent skill

mobicom-experiments

Use when designing or auditing the evaluation of a MobiCom submission — building real-device testbeds, choosing RF and channel measurement methodology, injecting realistic mobility and interference, profiling energy on hardware, picking tuned baselines, and reporting distributions so wireless reviewers see where the mechanism wins and breaks.

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

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

Facts
Files in the skill folder: 1
SKILL.md size: 6 KB
Bundled scripts: none
Path: MobiCom-Skills/skills/mobicom-experiments/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 984 · +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

# MobiCom Experiments MobiCom's evidence culture is physical: a mobile/wireless mechanism is believed when it is **measured over the air, on real hardware, under conditions that resemble deployment**. A simulation-only or single-run evaluation reads as under-done here. Design the evaluation as a set of questions about the mechanism, then build the smallest measurement campaign that answers them on real radios. ## Questions before measurements Write the evaluation's subsection titles as questions first — *Does the mechanism hold under mobility? What does it cost in energy at rest? When does the channel defeat it?* — then design one experiment per question. The inverted approach (run everything, narrate the survivors) produces the benchmark tour that MobiCom reviews call unfocused. A minimal matrix for a wireless-mechanism paper: | Question | Experiment | Metrics that answer it | |---|---|---| | Does it work in the motivating condition? | over-the-air run under the target channel/mobility | delivery rate, goodput, SNR/BER distribution | | What does it cost when idle? | baseline with no stress | energy-per-bit, power draw, CPU/airtime overhead | | Why does it work? | component breakdo

What's inside
Steps it walks through
  1. Questions before measurements
  2. Measurement methodology reviewers check
  3. Energy is a first-class metric
  4. Baselines on tuned hardware
  5. Distributions, not superlatives
  6. Audit checklist
  7. Output format
More from Awesome-Journal-Skills
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About this skill
What does the mobicom-experiments skill do?

Use when designing or auditing the evaluation of a MobiCom submission — building real-device testbeds, choosing RF and channel measurement methodology, injecting realistic mobility and interference, profiling energy on hardware, picking tuned baselines, and reporting distributions so wireless reviewers see where the mechanism wins and breaks.

How do I install it?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill mobicom-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 984 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