Kubeshark Installer
kubeshark/kubeshark
Installs and configures Kubeshark on a Kubernetes cluster, choosing between the quick CLI path and a Helm install with custom values.
A skill your agent uses when designing or auditing the evaluation of a MobiSys submission — building real-device testbeds, instrumenting energy and thermal behavior, measuring latency and frame-rate…
Install Mobisys Experiments
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill mobisys-experiments -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills mobisys-experiments --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/MobiSys-Skills/skills/mobisys-experiments .claude/skills/mobisys-experiments && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "mobisys-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/MobiSys-Skills/skills/mobisys-experiments into .claude/skills/mobisys-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mobisys-experiments", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/MobiSys-Skills/skills/mobisys-experimentsType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill mobisys-experiments -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills mobisys-experiments --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/MobiSys-Skills/skills/mobisys-experiments .agents/skills/mobisys-experiments && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "mobisys-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/MobiSys-Skills/skills/mobisys-experiments into .agents/skills/mobisys-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mobisys-experiments", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill mobisys-experiments -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills mobisys-experiments --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/MobiSys-Skills/skills/mobisys-experiments .cursor/skills/mobisys-experiments && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "mobisys-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/MobiSys-Skills/skills/mobisys-experiments into .cursor/skills/mobisys-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mobisys-experiments", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/brycewang-stanford/Awesome-Journal-Skills.git --path MobiSys-Skills/skills/mobisys-experiments--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill mobisys-experiments -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills mobisys-experiments --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/MobiSys-Skills/skills/mobisys-experiments .gemini/skills/mobisys-experiments && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "mobisys-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/MobiSys-Skills/skills/mobisys-experiments into .gemini/skills/mobisys-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mobisys-experiments", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills mobisys-experimentsInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill mobisys-experiments -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/MobiSys-Skills/skills/mobisys-experiments .github/skills/mobisys-experiments && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "mobisys-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/MobiSys-Skills/skills/mobisys-experiments into .github/skills/mobisys-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mobisys-experiments", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill mobisys-experiments -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills mobisys-experiments --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/MobiSys-Skills/skills/mobisys-experiments .opencode/skills/mobisys-experiments && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "mobisys-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/MobiSys-Skills/skills/mobisys-experiments into .opencode/skills/mobisys-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mobisys-experiments", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
mobisys-experiments- GitHub stars
- 1.2k
- Token cost
- ~1.5k tokens
- SKILL.md length
- 647 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when designing or auditing the evaluation of a MobiSys submission — building real-device testbeds, instrumenting energy and thermal behavior, measuring latency and frame-rate…
- Auditing the evaluation of a MobiSys submission — building real-device testbeds
- SKILL.md covers Turn each claim into one…, What the setup must state, Making energy and heat auditable and Comparators a systems reviewer…, plus 3 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Instrumenting energy and thermal behavior
What it does
Mobisys Experiments is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when designing or auditing the evaluation of a MobiSys submission — building real-device testbeds, instrumenting energy and thermal behavior, measuring latency and frame-rate tails, bounding memory footprint, choosing tuned system baselines, and running deployments or user studies, so systems reviewers see where the system wins and breaks on the device.
Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in DevOps & Cloud, covering Deployment. The repository describes itself as: Journal-specific Claude Code/Codex skill packs covering mainstream journals — AER, QJE, Nature, Cell, 管理世界, 经济研究 & 200+ more — your fast track to getting published. ｜ 覆盖主流期刊的… The licence is MIT.
When your agent uses it
- Auditing the evaluation of a MobiSys submission — building real-device testbeds
- Instrumenting energy and thermal behavior
- Measuring latency and frame-rate tails
- Bounding memory footprint
Example prompts
- “/mobisys-experiments”
What it can do on your machine
Read from SKILL.md and the folder at commit 932eb23. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Mobisys Experiments loads about 1.5k tokens when it runs. Until then it costs about 95 tokens; SKILL.md has 647 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from brycewang-stanford/Awesome-Journal-Skills at commit 932eb23, republished under its MIT licence (© brycewang-stanford). 647 words, ~1,503 tokens.
Download SKILL.mdSave it as
.claude/skills/mobisys-experiments/SKILL.md (or your agent's skills folder).- name
- mobisys-experiments
- description
- Use when designing or auditing the evaluation of a MobiSys submission — building real-device testbeds, instrumenting energy and thermal behavior, measuring latency and frame-rate tails, bounding memory footprint, choosing tuned system baselines, and running deployments or user studies, so systems reviewers see where the system wins and breaks on the device.
MobiSys Experiments
A MobiSys result becomes believable only when it is measured on real hardware, driven to steady state, and reported in latency, energy, memory, and thermal terms. Simulation-only or single-run numbers read as under-done. The evaluation axis here is the device and platform — compute, energy, latency, memory, heat — not the radio or channel a wireless venue grades, and not the traffic-and-topology an infrastructure venue grades. Build the evaluation as one device-behavior claim per experiment.
Turn each claim into one device experiment
The clean structure gives each subsection a claim about the running system, then the one experiment that settles it. The opposite habit — run a benchmark suite and describe whatever survives — is the unfocused evaluation MobiSys reviewers push back on. The claim-to-experiment map for a running mobile system:
| Claim about the system | Experiment that settles it | Metrics |
|---|---|---|
| It meets the target in the motivating scenario | on-device run under the real workload | p50/p95 latency, throughput, task success |
| Its energy cost is acceptable | instrumented run on a power monitor | energy-per-operation, average and peak power |
| It survives sustained use | multi-minute run to thermal steady state | frame-rate stability, temperature trace, throttle onset |
| Each mechanism earns its place | component breakdown / ablation | per-mechanism contribution |
| It fits within device memory | peak-memory and storage accounting | peak RSS, model and cache size |
| Its failure mode is understood | hot, low-memory, low-battery device states | the state where a baseline wins |
What the setup must state
- The full device context: phone/board model, SoC, OS build, framework/runtime version, battery vs. wall power, and ambient temperature. A number without its device is not interpretable.
- Define the energy boundary: the power instrument (on-device rail, external monitor, shunt + DAQ), the sampling rate, and what is inside the measured envelope (SoC only? whole device?). Do not let "efficient" stand in for a measured joules figure.
- Make load explicit: the workload trace, its duration, and whether the run reached thermal steady state; a 30-second benchmark hides the throttling that a 20-minute run shows.
- Report ground truth honestly: for a service or inference claim, how correctness was established and its own error.
Making energy and heat auditable
Battery, energy, and thermal claims are common at MobiSys and are held to instrument-level scrutiny:
Energy/thermal report checklist:
instrument: power monitor / on-device rail / shunt + DAQ, sampling rate
quantity: energy-per-operation (mJ), not just average power (mW)
boundary: what is inside the measured envelope (SoC? whole device?)
thermal: skin/SoC temperature trace and whether steady state was reached
battery: state-of-charge span, or wall power stated explicitlyAn energy or thermal claim that cannot be re-derived from a described setup should not survive your own audit.
Show full SKILL.md (264 more words)Show less
Comparators a systems reviewer will trust
- Compare against the system people actually run, configured the way its own documentation prescribes — an untuned baseline is the most common credibility wound in systems reviewing.
- Include the do-less baseline: the trivial fix (a smaller model, a fixed low frame rate, more aggressive quantization). If the system cannot beat it at equal quality, that is the finding.
- When a competitor cannot be run (proprietary runtime, unavailable device), reimplement and label it a reimplementation, or compare on published numbers with the configuration deltas stated.
Report the spread, never a lone peak
- Report percentiles and confidence intervals for latency, energy, and throughput; a
single "up to N×" without the distribution is a review risk (
mobisys-writing-style). - Show tails and CDFs for headline latency results, and repeat runs across enough devices, thermal states, or battery levels to expose run-to-run spread.
- On-device results are device- and state-dependent — a number from one phone at full charge in a cool room is not a claim about the system until the spread is characterized.
Pre-submission evaluation pass
- Every evaluation subsection answers a named question.
- Device, OS, runtime version, power source, and ambient fully specified per experiment.
- Energy measured with a described instrument and boundary, not estimated.
- Sustained-load run reaches steady state; thermal behavior reported.
- Incumbent-grade baseline present and tuned; do-less baseline present.
- Percentiles + tails for headline latency; multi-device or multi-state spread reported.
- At least one device state the system does not win, discussed rather than buried.
- Numbers in abstract/intro regenerate from the recorded runs.
- A hardware-optional or downscaled variant exists for artifact evaluators
(
mobisys-artifact-evaluation).
Output format
[Evidence form] on-device measurement / deployment / user study / trace / simulation (claimed vs actual)
[Question map] question -> experiment -> metric (gaps flagged)
[Device+energy] setup and boundary specified? y/n per headline experiment
[Sustained load] steady state reached and thermal reported? y/n
[Baseline audit] incumbent tuned? do-less present?
[Break condition] device state where the system loses: <named or MISSING>
[Priority additions] ordered by review-risk reduction per bench-day© brycewang-stanford, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in MobiSys-Skills/skills/mobisys-experiments of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Mobisys Experiments next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Mobisys Experiments this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.5k | Automated safety check: Pass | MIT | |
| Kubeshark Installerkubeshark/kubeshark | 12k | — | ~3.6k | Automated safety check: Notes | Apache-2.0 | |
| GreptimeDB Dev Docker ImageGreptimeTeam/greptimedb | 6.7k | — | ~4k | Automated safety check: Notes | Apache-2.0 | |
| KubeSphere ServiceMesh Managerkubesphere/kubesphere | 17k | — | ~2.4k | Automated safety check: Pass | Custom licence | |
| Vercelremotion-dev/remotion | 63k | — | ~1.2k | Automated safety check: Pass | Custom licence | |
| AWS Cdk Developmentzxkane/aws-skills | 367 | 2 repos | ~2.5k | Automated safety check: Pass | MIT |
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Related
Categories
Questions about Mobisys Experiments
What does Mobisys Experiments do?
A skill your agent uses when designing or auditing the evaluation of a MobiSys submission — building real-device testbeds, instrumenting energy and thermal behavior, measuring latency and frame-rate…. Mobisys Experiments is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when designing or auditing the evaluation of a MobiSys submission — building real-device testbeds, instrumenting energy and thermal behavior, measuring latency and frame-rate tails, bounding memory footprint, choosing tuned system baselines, and running deployments or user studies, so systems reviewers see where the system wins and breaks on the device.
When should I use Mobisys Experiments?
Mobisys Experiments fits situations like: auditing the evaluation of a MobiSys submission — building real-device testbeds; instrumenting energy and thermal behavior; measuring latency and frame-rate tails; bounding memory footprint.
How do I install Mobisys Experiments in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill mobisys-experiments -a claude-code`. Or copy the skill folder (MobiSys-Skills/skills/mobisys-experiments in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/mobisys-experiments in your project. Claude Code loads it when a task matches its description.
How do I install Mobisys Experiments in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill mobisys-experiments -a codex`. Or copy the skill folder (MobiSys-Skills/skills/mobisys-experiments in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/mobisys-experiments in your project. Codex loads it when a task matches its description.
Can I use Mobisys Experiments in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill mobisys-experiments -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/mobisys-experiments, .gemini/skills/mobisys-experiments, .github/skills/mobisys-experiments and .opencode/skills/mobisys-experiments in your project.
What does Mobisys Experiments need to run?
SKILL.md names no scripts, command-line tools or credentials: Mobisys Experiments is instructions for the agent only.
Does Mobisys Experiments access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Mobisys Experiments safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Mobisys Experiments use?
Mobisys Experiments is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Mobisys Experiments use?
About 1.5k tokens (SKILL.md is roughly 6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Mobisys Experiments?
Skills that share tags, products or a category with Mobisys Experiments: Kubeshark Installer (kubeshark/kubeshark, 12k stars), GreptimeDB Dev Docker Image (GreptimeTeam/greptimedb, 6.7k stars), KubeSphere ServiceMesh Manager (kubesphere/kubesphere, 17k stars) and Vercel (remotion-dev/remotion, 63k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Mobisys Experiments?
brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,228 GitHub stars. The repository holds 2,387 skills in this directory. The repository was last updated on September 27, 2026.
Source: brycewang-stanford/Awesome-Journal-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.