Design Audit Against Rams' Principles
thedotmack/claude-mem
Audits a design against Dieter Rams' ten principles of good design, scores each with evidence, and hands off a make-plan prompt for a new, refined or redesigned outcome.
A skill your agent uses when designing or auditing the evaluation of a EuroSys paper — choosing workloads that earn the word realistic, tuning baselines beyond their defaults, decomposing end-to-end…
MITAuto-check passed
Install Eurosys Experiments
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill eurosys-experiments -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills eurosys-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/EuroSys-Skills/skills/eurosys-experiments .claude/skills/eurosys-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 "eurosys-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/EuroSys-Skills/skills/eurosys-experiments into .claude/skills/eurosys-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eurosys-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/EuroSys-Skills/skills/eurosys-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 eurosys-experiments -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills eurosys-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/EuroSys-Skills/skills/eurosys-experiments .agents/skills/eurosys-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 "eurosys-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/EuroSys-Skills/skills/eurosys-experiments into .agents/skills/eurosys-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eurosys-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 eurosys-experiments -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills eurosys-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/EuroSys-Skills/skills/eurosys-experiments .cursor/skills/eurosys-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 "eurosys-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/EuroSys-Skills/skills/eurosys-experiments into .cursor/skills/eurosys-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eurosys-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 EuroSys-Skills/skills/eurosys-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 eurosys-experiments -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills eurosys-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/EuroSys-Skills/skills/eurosys-experiments .gemini/skills/eurosys-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 "eurosys-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/EuroSys-Skills/skills/eurosys-experiments into .gemini/skills/eurosys-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eurosys-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 eurosys-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 eurosys-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/EuroSys-Skills/skills/eurosys-experiments .github/skills/eurosys-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 "eurosys-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/EuroSys-Skills/skills/eurosys-experiments into .github/skills/eurosys-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eurosys-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 eurosys-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 eurosys-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/EuroSys-Skills/skills/eurosys-experiments .opencode/skills/eurosys-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 "eurosys-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/EuroSys-Skills/skills/eurosys-experiments into .opencode/skills/eurosys-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eurosys-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
eurosys-experiments- GitHub stars
- 1.2k
- Token cost
- ~1.4k tokens
- SKILL.md length
- 651 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 EuroSys paper — choosing workloads that earn the word realistic, tuning baselines beyond their defaults, decomposing end-to-end…
- Auditing the evaluation of a EuroSys paper — choosing workloads that earn the word realistic
- SKILL.md covers The four-layer evidence stack, Workload realism, argued not…, Baseline fairness — the… and Experiment matrix as an artifact, plus 4 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Tuning baselines beyond their defaults
What it does
Eurosys Experiments is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when designing or auditing the evaluation of a EuroSys paper — choosing workloads that earn the word realistic, tuning baselines beyond their defaults, decomposing end-to-end wins into per-mechanism gains, measuring overheads and worst cases, and sizing experiments to the claims the paper actually makes.
Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
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 EuroSys paper — choosing workloads that earn the word realistic
- Tuning baselines beyond their defaults
- Decomposing end-to-end wins into per-mechanism gains
- Measuring overheads and worst cases
Example prompts
- “/eurosys-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 (its code samples are yaml).
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
Eurosys Experiments loads about 1.4k tokens when it runs. Until then it costs about 82 tokens; SKILL.md has 651 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). 651 words, ~1,418 tokens.
Download SKILL.mdSave it as
.claude/skills/eurosys-experiments/SKILL.md (or your agent's skills folder).- name
- eurosys-experiments
- description
- Use when designing or auditing the evaluation of a EuroSys paper — choosing workloads that earn the word realistic, tuning baselines beyond their defaults, decomposing end-to-end wins into per-mechanism gains, measuring overheads and worst cases, and sizing experiments to the claims the paper actually makes.
EuroSys Experiments
Use this while the evaluation is still designable. EuroSys reviewers treat the evaluation as the paper's testimony about itself: the design section says what should happen, and §Evaluation is cross-examination. Plan it as a set of questions with falsifiable answers, not as a benchmark tour.
The four-layer evidence stack
| Layer | Question it answers | Typical EuroSys instrument |
|---|---|---|
| End-to-end | Does the system win where users live? | Full application or serving workload, realistic scale |
| Decomposition | Which mechanism buys which fraction? | Factor analysis: enable components one at a time |
| Cost | What does the win spend? | Memory/CPU/network overhead, code and ops complexity |
| Boundary | Where does it stop winning? | Adversarial mixes, saturation, failure injection |
A submission with only the first layer reads as a demo; the middle layers are what convert "it is faster" into "we understand why it is faster", which is the systems-research standard of proof.
Workload realism, argued not asserted
- Prefer published traces and standard suites with named versions; when using a synthetic generator, calibrate it against a real distribution and say how.
- Match the workload to the claim's regime: a memory-efficiency claim needs memory pressure; a tail-latency claim needs load near saturation, not at 30%.
- Scale honestly: if the pitch is rack-scale, a two-node result needs an explicit extrapolation argument or a scoped-down claim.
- Report the workload's own parameters (skew, read ratio, arrival process) so the experiment is reconstructible without your cluster.
Baseline fairness — the venue's sharpest knife
The reflexive EuroSys reviewer question is "did they tune the baseline?" Answer it before it is asked:
- Run baselines at their documented best configuration for your hardware, and cite where that configuration comes from.
- Include the strongest deployed alternative, not only research prototypes — losing to a well-tuned production system on some axis is survivable; omitting it is not.
- Same hardware, same workload generator, same measurement harness for every system; any asymmetry gets a sentence of justification.
- When your system loses a metric, plot it anyway and explain the tradeoff.
Experiment matrix as an artifact
Freeze the plan in a machine-checkable form before running:
# eval-matrix.yaml — one row per claim the paper will make
- claim: "cuts p99 GET latency ≥40% under skewed load"
figure: fig8
workload: {trace: twitter-cache-2020, skew: zipf-0.99, load: 0.85sat}
systems: [ours@v1.4, baselineA@3.2-tuned, baselineB@1.9-tuned]
reps: 10
metrics: [p50, p99, p999, throughput]
status: pendingThe matrix doubles as the reproducibility ledger (eurosys-reproducibility)
and later as the artifact's claims map (eurosys-artifact-evaluation).
Show full SKILL.md (294 more words)Show less
Result invalidators to design out early
Each of these has sunk otherwise strong EuroSys evaluations; each is cheap to prevent and expensive to discover in a review:
- Measuring through a bottleneck that is not the system under test — a saturated client, a slow log disk, a debug build of a dependency.
- Comparing your warm system against cold baselines (or vice versa) because warm-up policy was never standardized across systems.
- A "scalability" curve whose x-axis grows load and resources together, so nothing about scaling behavior is actually isolated.
- Reporting means over runs that include documented failures — decide the failure-handling policy for measurements before running them.
- Config drift between the end-to-end and decomposition experiments, so the component gains do not sum to anything resembling the headline.
Sizing runs for the claim
- Comparative bar charts: ≥5–10 repetitions with dispersion shown; single-run bars invite a one-line rejection rationale.
- Tail latencies: enough requests that the quoted percentile has support — a p999 from 10k requests is ten samples of noise.
- Ablations: vary one factor per experiment; a config delta of two changes attributes nothing.
- Timeboxing: reserve cluster time for the boundary layer explicitly; it is always the layer teams drop under deadline pressure and the layer reviewers miss loudest.
Reporting floor for the paper
- Hardware and topology for every experiment, once, in a table the reader can find (§Evaluation setup), with per-figure deviations noted.
- Software versions for every system in every comparison, including yours.
- Load points quoted with the metric ("85% of measured peak throughput"), never as bare client counts whose meaning depends on the cluster.
- Repetition count and dispersion type in every caption that shows a comparison.
- A sentence on measurement methodology for anything subtle: how latency is timestamped, where the measurement harness sits, what it costs.
Output format
[Claim -> evidence map] <each paper claim: figure, workload, systems, reps>
[Stack coverage] end-to-end / decomposition / cost / boundary: present or missing
[Baseline fairness] <tuning provenance and deployed-alternative status>
[Realism audit] <trace provenance, load regime, scale honesty>
[Highest-value missing run] <the one experiment to schedule next>© 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 EuroSys-Skills/skills/eurosys-experiments of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Eurosys 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 |
|---|---|---|---|---|---|---|
| Eurosys Experiments this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.4k | Automated safety check: Pass | MIT | |
| Design Audit Against Rams' Principlesthedotmack/claude-mem | 99k | — | ~4.6k | Automated safety check: Pass | Apache-2.0 | |
| Experiment Auditwanshuiyin/Auto-claude-code-research-in-sleep | 17k | 1 repos | ~2.7k | Automated safety check: Notes | MIT | |
| Experiment Auditwanshuiyin/Auto-claude-code-research-in-sleep | 17k | — | ~3.2k | Automated safety check: Notes | MIT | |
| Experiment Designeralirezarezvani/claude-skills | 28k | 1 repos | ~783 | Automated safety check: Pass | MIT | |
| OpenClaw Design Auditopenclaw/clawhub | 9.5k | — | ~498 | Automated safety check: Pass | MIT |
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Questions about Eurosys Experiments
What does Eurosys Experiments do?
A skill your agent uses when designing or auditing the evaluation of a EuroSys paper — choosing workloads that earn the word realistic, tuning baselines beyond their defaults, decomposing end-to-end…. Eurosys Experiments is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when designing or auditing the evaluation of a EuroSys paper — choosing workloads that earn the word realistic, tuning baselines beyond their defaults, decomposing end-to-end wins into per-mechanism gains, measuring overheads and worst cases, and sizing experiments to the claims the paper actually makes.
When should I use Eurosys Experiments?
Eurosys Experiments fits situations like: auditing the evaluation of a EuroSys paper — choosing workloads that earn the word realistic; tuning baselines beyond their defaults; decomposing end-to-end wins into per-mechanism gains; measuring overheads and worst cases.
How do I install Eurosys Experiments in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill eurosys-experiments -a claude-code`. Or copy the skill folder (EuroSys-Skills/skills/eurosys-experiments in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/eurosys-experiments in your project. Claude Code loads it when a task matches its description.
How do I install Eurosys Experiments in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill eurosys-experiments -a codex`. Or copy the skill folder (EuroSys-Skills/skills/eurosys-experiments in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/eurosys-experiments in your project. Codex loads it when a task matches its description.
Can I use Eurosys 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 eurosys-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/eurosys-experiments, .gemini/skills/eurosys-experiments, .github/skills/eurosys-experiments and .opencode/skills/eurosys-experiments in your project.
What does Eurosys Experiments need to run?
SKILL.md names no scripts, command-line tools or credentials: Eurosys Experiments is instructions for the agent only.
Does Eurosys 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 Eurosys 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 Eurosys Experiments use?
Eurosys 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 Eurosys Experiments use?
About 1.4k tokens (SKILL.md is roughly 5.7k 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 Eurosys Experiments?
Skills that share tags, products or a category with Eurosys Experiments: Design Audit Against Rams' Principles (thedotmack/claude-mem, 99k stars), Experiment Audit (wanshuiyin/Auto-claude-code-research-in-sleep, 17k stars), Experiment Audit (wanshuiyin/Auto-claude-code-research-in-sleep, 17k stars) and Experiment Designer (alirezarezvani/claude-skills, 28k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Eurosys 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.