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 EDBT empirical evaluations for database-systems work, covering real workloads and datasets, fair and tuned baselines, honest measurement across…
MITAuto-check passed
Install Edbt Experiments
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill edbt-experiments -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills edbt-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/EDBT-Skills/skills/edbt-experiments .claude/skills/edbt-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 "edbt-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/EDBT-Skills/skills/edbt-experiments into .claude/skills/edbt-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "edbt-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/EDBT-Skills/skills/edbt-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 edbt-experiments -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills edbt-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/EDBT-Skills/skills/edbt-experiments .agents/skills/edbt-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 "edbt-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/EDBT-Skills/skills/edbt-experiments into .agents/skills/edbt-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "edbt-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 edbt-experiments -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills edbt-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/EDBT-Skills/skills/edbt-experiments .cursor/skills/edbt-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 "edbt-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/EDBT-Skills/skills/edbt-experiments into .cursor/skills/edbt-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "edbt-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 EDBT-Skills/skills/edbt-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 edbt-experiments -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills edbt-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/EDBT-Skills/skills/edbt-experiments .gemini/skills/edbt-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 "edbt-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/EDBT-Skills/skills/edbt-experiments into .gemini/skills/edbt-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "edbt-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 edbt-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 edbt-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/EDBT-Skills/skills/edbt-experiments .github/skills/edbt-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 "edbt-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/EDBT-Skills/skills/edbt-experiments into .github/skills/edbt-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "edbt-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 edbt-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 edbt-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/EDBT-Skills/skills/edbt-experiments .opencode/skills/edbt-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 "edbt-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/EDBT-Skills/skills/edbt-experiments into .opencode/skills/edbt-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "edbt-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
edbt-experiments- GitHub stars
- 1.2k
- Token cost
- ~1.3k tokens
- SKILL.md length
- 476 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 EDBT empirical evaluations for database-systems work, covering real workloads and datasets, fair and tuned baselines, honest measurement across…
- Auditing EDBT empirical evaluations for database-systems work
- SKILL.md covers Evaluation audit, Claim-to-evidence design table, Measurement discipline… and The Experiments & Analysis…, plus 2 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Covering real workloads and datasets
What it does
Edbt Experiments is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when designing or auditing EDBT empirical evaluations for database-systems work, covering real workloads and datasets, fair and tuned baselines, honest measurement across realistic scales, reproducible harnesses, and the higher bar of the Experiments & Analysis paper where the measurement itself is the contribution.
Its SKILL.md is about 1.3k 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 EDBT empirical evaluations for database-systems work
- Covering real workloads and datasets
- Fair and tuned baselines
- Honest measurement across realistic scales
Example prompts
- “/edbt-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
Edbt Experiments loads about 1.3k tokens when it runs. Until then it costs about 85 tokens; SKILL.md has 476 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). 476 words, ~1,310 tokens.
Download SKILL.mdSave it as
.claude/skills/edbt-experiments/SKILL.md (or your agent's skills folder).- name
- edbt-experiments
- description
- Use when designing or auditing EDBT empirical evaluations for database-systems work, covering real workloads and datasets, fair and tuned baselines, honest measurement across realistic scales, reproducible harnesses, and the higher bar of the Experiments & Analysis paper where the measurement itself is the contribution.
EDBT Experiments
Use this before submission when the evaluation is not yet locked. EDBT reviewers are database-systems empiricists; the evaluation is where a good idea is won or lost. The organizing principle is evidence proportional to the claim — the study must measure the thing the paper actually asserts, on workloads, datasets, and scales a skeptic would accept, against baselines a skeptic would accept.
Evaluation audit
- Match evidence to the claim shape. A claim about latency needs latency measurements under a realistic workload; a claim about scalability needs runs across a realistic range of sizes/nodes; a claim about space needs memory/footprint numbers; a claim about accuracy needs a labeled ground truth. "Faster on a dataset" is not evidence for a scalability claim.
- Use real workloads and datasets, named and sourced (standard benchmarks, real query logs, real corpora), not a single toy input. Say how the workload was derived.
- Choose fair, tuned baselines, including the strongest current technique and a simple-but-reasonable alternative, configured with a documented, equal budget. An untuned baseline is the most common EDBT reviewer objection.
- Measure honestly: report variance across repeated runs, warm/cold state, the metric definition, and the hardware/cluster configuration. State what you controlled and what you did not.
- Cover the regimes: where the technique helps, where it is neutral, and its overhead or failure cases — quantified, not asserted.
- Make the harness reproducible (see
edbt-reproducibility): the evaluation should re-run from the artifact rather than being re-measured from scratch.
Claim-to-evidence design table
| Database claim | Matching evidence | Reject pattern avoided |
|---|---|---|
| "Lower query latency" | Latency under a named workload vs. tuned baseline, with variance | "One unnamed dataset, no baseline config" |
| "Scales to large data / many nodes" | Runs across a realistic size/node range | "Only small inputs / single node tested" |
| "Lower space / memory" | Footprint measured under realistic load | "Asymptotic argument, no measurement" |
| "Robust to skew / adversarial input" | Results across skew levels incl. worst case | "Only uniform / benign inputs" |
| "General across engines / settings" | Multiple engines or configurations + explicit limits | "One engine, claimed universal" |
Show full SKILL.md (147 more words)Show less
Measurement discipline (database-systems flavor)
[Workload] name it, source it, say how it was derived; prefer real logs / standard benchmarks
[Baseline] the strongest current technique, TUNED, with the configuration documented
[Scale] realistic sizes and node counts; report where behavior changes
[Variance] repeated runs; report spread, not a single best number
[State] warm vs cold, cache effects, and what was controlled
[Environment] hardware, memory, network, engine build/commit — enough to size a reproductionThe Experiments & Analysis paper (a distinct, higher bar)
When the paper's contribution is the study — a benchmarking, repeatability, or comparative analysis — the methodology is not support, it is the deliverable:
[Subjects] the systems/techniques compared, chosen by a stated, defensible criterion
[Coverage] the workload and parameter space actually spanned, and what was left out and why
[Fairness] every compared system tuned by its own experts' guidance, not just yours
[Repeatability] the harness re-runs the whole comparison from the artifact
[Findings] the analysis, with the surprising or actionable results foregroundedAn Experiments & Analysis paper that tunes only its authors' preferred system, or spans a workload space too narrow to generalize, fails on its core contribution, not on a side point.
Vignette: evaluating a query-processing operator
Suppose the paper claims an operator lowers straggler time under skew. The matching plan: derive workloads from real query logs at several skew levels; run the operator and a tuned skew-aware baseline across 8-128 workers; report straggler time and total latency with variance; measure the overhead on skew-free workloads to bound the worst case; and state the boundary (very short queries, undetectable skew) with a measurement — every number traceable to a logged run in the artifact.
Output format
[Evaluation readiness] strong / adequate / weak
[Claim -> evidence map] <claim: workload / metric / scale>
[Baseline fairness] <baseline -> tuned? equal config? documented?>
[Scale + variance] <realistic range tested? variance reported?>
[Regimes] <helps / neutral / cost / failure all measured? yes/no>
[E&A bar (if applicable)] <methodology, coverage, fairness, repeatability adequate?>
[Decision-critical next run] <one experiment to add>© 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 EDBT-Skills/skills/edbt-experiments of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Edbt 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 |
|---|---|---|---|---|---|---|
| Edbt Experiments this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.3k | Automated safety check: Pass | MIT | |
| Design Audit Against Rams' Principlesthedotmack/claude-mem | 98k | — | ~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 Edbt Experiments
What does Edbt Experiments do?
A skill your agent uses when designing or auditing EDBT empirical evaluations for database-systems work, covering real workloads and datasets, fair and tuned baselines, honest measurement across…. Edbt Experiments is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when designing or auditing EDBT empirical evaluations for database-systems work, covering real workloads and datasets, fair and tuned baselines, honest measurement across realistic scales, reproducible harnesses, and the higher bar of the Experiments & Analysis paper where the measurement itself is the contribution.
When should I use Edbt Experiments?
Edbt Experiments fits situations like: auditing EDBT empirical evaluations for database-systems work; covering real workloads and datasets; fair and tuned baselines; honest measurement across realistic scales.
How do I install Edbt Experiments in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill edbt-experiments -a claude-code`. Or copy the skill folder (EDBT-Skills/skills/edbt-experiments in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/edbt-experiments in your project. Claude Code loads it when a task matches its description.
How do I install Edbt Experiments in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill edbt-experiments -a codex`. Or copy the skill folder (EDBT-Skills/skills/edbt-experiments in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/edbt-experiments in your project. Codex loads it when a task matches its description.
Can I use Edbt 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 edbt-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/edbt-experiments, .gemini/skills/edbt-experiments, .github/skills/edbt-experiments and .opencode/skills/edbt-experiments in your project.
What does Edbt Experiments need to run?
SKILL.md names no scripts, command-line tools or credentials: Edbt Experiments is instructions for the agent only.
Does Edbt 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 Edbt 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 Edbt Experiments use?
Edbt 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 Edbt Experiments use?
About 1.3k tokens (SKILL.md is roughly 5.2k 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 Edbt Experiments?
Skills that share tags, products or a category with Edbt Experiments: Design Audit Against Rams' Principles (thedotmack/claude-mem, 98k 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 Edbt Experiments?
brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,219 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.