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 analytical "evidence" of an ACM PODS paper — worst-case and average-case analyses, matching upper and lower bounds, dichotomy completeness…
MITAuto-check passed
Install Pods Experiments
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill pods-experiments -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills pods-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/PODS-Skills/skills/pods-experiments .claude/skills/pods-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 "pods-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/PODS-Skills/skills/pods-experiments into .claude/skills/pods-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pods-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/PODS-Skills/skills/pods-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 pods-experiments -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills pods-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/PODS-Skills/skills/pods-experiments .agents/skills/pods-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 "pods-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/PODS-Skills/skills/pods-experiments into .agents/skills/pods-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pods-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 pods-experiments -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills pods-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/PODS-Skills/skills/pods-experiments .cursor/skills/pods-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 "pods-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/PODS-Skills/skills/pods-experiments into .cursor/skills/pods-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pods-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 PODS-Skills/skills/pods-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 pods-experiments -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills pods-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/PODS-Skills/skills/pods-experiments .gemini/skills/pods-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 "pods-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/PODS-Skills/skills/pods-experiments into .gemini/skills/pods-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pods-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 pods-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 pods-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/PODS-Skills/skills/pods-experiments .github/skills/pods-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 "pods-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/PODS-Skills/skills/pods-experiments into .github/skills/pods-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pods-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 pods-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 pods-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/PODS-Skills/skills/pods-experiments .opencode/skills/pods-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 "pods-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/PODS-Skills/skills/pods-experiments into .opencode/skills/pods-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pods-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
pods-experiments- GitHub stars
- 1.2k
- Token cost
- ~1.3k tokens
- SKILL.md length
- 589 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 analytical "evidence" of an ACM PODS paper — worst-case and average-case analyses, matching upper and lower bounds, dichotomy completeness…
- Auditing the analytical evidence of an ACM PODS paper — worst-case and average-case analyses
- SKILL.md covers Analysis audit, Claim-to-rigor design table, Assumption and model discipline and Optional empirical validation…, plus 3 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Matching upper and lower bounds
What it does
Pods Experiments is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when designing or auditing the analytical "evidence" of an ACM PODS paper — worst-case and average-case analyses, matching upper and lower bounds, dichotomy completeness, correct complexity assumptions, and the occasional empirical validation when a theory paper claims practicality — matching the rigor to the shape of each theoretical claim.
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 the analytical evidence of an ACM PODS paper — worst-case and average-case analyses
- Matching upper and lower bounds
- Dichotomy completeness
- Correct complexity assumptions
Example prompts
- “evidence”
- “/pods-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
Pods Experiments loads about 1.3k tokens when it runs. Until then it costs about 91 tokens; SKILL.md has 589 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). 589 words, ~1,348 tokens.
Download SKILL.mdSave it as
.claude/skills/pods-experiments/SKILL.md (or your agent's skills folder).- name
- pods-experiments
- description
- Use when designing or auditing the analytical "evidence" of an ACM PODS paper — worst-case and average-case analyses, matching upper and lower bounds, dichotomy completeness, correct complexity assumptions, and the occasional empirical validation when a theory paper claims practicality — matching the rigor to the shape of each theoretical claim.
PODS Experiments
Use this before submission when the technical story is not yet locked. For PODS the "experiments" are mostly analyses and proofs, because the reviewers are theoreticians and the evidence is a theorem, not a benchmark. The organizing principle is rigor proportional to the claim — the analysis must establish exactly what the paper asserts, in the model it names, with no hidden gap.
Analysis audit
- Match the analysis to the claim shape. A claim of optimality needs a matching lower bound; a claim of a classification needs completeness (every case decided); a claim of efficiency needs an exact complexity in a stated measure (data vs. combined), not an asymptotic hand-wave.
- Close the upper/lower-bound gap, or state it. An upper bound without a lower bound is not optimality; if the gap is open, say so precisely rather than implying tightness.
- State every complexity assumption. Conditional hardness (ETH, SETH, OMv, the exponential-time
hypothesis,
P ≠ NP,#P-hardness) must be named where the bound is stated; never dress a conditional lower bound as unconditional. - Check the model does not smuggle the result. A cost model, a data model restriction, or an encoding choice can trivialize or inflate a bound; make the modeling assumptions explicit and defend them as realistic for data management.
- Handle constants and parameters honestly. Hidden dependence on the query size, the schema, or a fixed parameter can turn a "linear" claim into something else; state what is held constant.
- When you claim practicality, show it — carefully. PODS papers occasionally include a small empirical validation to illustrate that the theory's constants are reasonable. If you do, it is a supporting illustration, not the contribution: report it modestly, and never let a benchmark stand in for a missing proof.
Claim-to-rigor design table
| PODS claim | Matching rigor | Reject pattern avoided |
|---|---|---|
| "Our algorithm is worst-case optimal" | Upper bound + matching lower bound in the same model | "Fast in experiments" with no lower bound |
| "We classify the whole query class" | A dichotomy proof covering every case, both sides | A tractability result for some queries only |
"Evaluation is coNP-complete" | Membership proof + a hardness reduction | Hardness asserted from a single example |
| "The semantics is well-defined and computable" | Well-definedness proof + a decidability/complexity result | A definition with no algorithmic content |
| "This bound is unconditional" | A proof that names no unproven conjecture | A conditional bound presented as absolute |
Show full SKILL.md (202 more words)Show less
Assumption and model discipline
[Complexity measure] data complexity / combined complexity / parameterized — state which and stay consistent
[Cost model] RAM / arithmetic / communication (MPC rounds) — fix it before stating a bound
[Conjectures] name each (ETH/SETH/OMv/#P) exactly where a conditional bound depends on it
[Encoding] make input encoding explicit when it affects the bound (unary vs. binary, etc.)
[Parameters] say what is fixed and what varies; expose hidden query-size dependenceOptional empirical validation (when a paper claims practicality)
- Keep it small and clearly secondary; state the implementation and inputs so the illustration is reproducible, but do not turn the paper into a systems submission.
- Never use measured speed to substitute for an unproven bound — a PODS reviewer reads that as a gap.
- If the practical behavior diverges from the worst-case theory, say so; the honesty strengthens the paper.
Vignette: proving an algorithm optimal
Suppose the paper claims a new join-evaluation algorithm is worst-case optimal. The matching plan: state the exact output-size bound the algorithm meets; prove the running-time upper bound in the stated cost model; prove a matching lower bound showing no algorithm in the model beats it (or cite the known information-theoretic bound and prove your algorithm meets it); and state precisely the class of queries and inputs for which optimality holds, flagging what is left open — every step in the body or the at-submission appendix.
Rigor reporting floor
- A matching lower bound for every optimality claim, or an explicit open-gap statement.
- Every conditional result labeled with its assumption at the point of statement.
- The complexity measure and cost model fixed once and used consistently.
Output format
[Rigor readiness] strong / adequate / gap present
[Claim -> rigor map] <claim: upper bound / lower bound / completeness / assumption>
[Tightness] <matching bound present? or open gap stated precisely?>
[Assumptions] <every conditional bound labeled with ETH/OMv/#P/etc.? yes/no>
[Model check] <cost/data model explicit and not smuggling the result? yes/no>
[Decision-critical next step] <the one proof to finish or the one bound to match>© 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 PODS-Skills/skills/pods-experiments of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Pods 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 |
|---|---|---|---|---|---|---|
| Pods Experiments this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.3k | 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 Pods Experiments
What does Pods Experiments do?
A skill your agent uses when designing or auditing the analytical "evidence" of an ACM PODS paper — worst-case and average-case analyses, matching upper and lower bounds, dichotomy completeness…. Pods Experiments is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when designing or auditing the analytical "evidence" of an ACM PODS paper — worst-case and average-case analyses, matching upper and lower bounds, dichotomy completeness, correct complexity assumptions, and the occasional empirical validation when a theory paper claims practicality — matching the rigor to the shape of each theoretical claim.
When should I use Pods Experiments?
Pods Experiments fits situations like: auditing the analytical evidence of an ACM PODS paper — worst-case and average-case analyses; matching upper and lower bounds; dichotomy completeness; correct complexity assumptions.
How do I install Pods Experiments in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill pods-experiments -a claude-code`. Or copy the skill folder (PODS-Skills/skills/pods-experiments in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/pods-experiments in your project. Claude Code loads it when a task matches its description.
How do I install Pods Experiments in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill pods-experiments -a codex`. Or copy the skill folder (PODS-Skills/skills/pods-experiments in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/pods-experiments in your project. Codex loads it when a task matches its description.
Can I use Pods 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 pods-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/pods-experiments, .gemini/skills/pods-experiments, .github/skills/pods-experiments and .opencode/skills/pods-experiments in your project.
What does Pods Experiments need to run?
SKILL.md names no scripts, command-line tools or credentials: Pods Experiments is instructions for the agent only.
Does Pods 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 Pods 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 Pods Experiments use?
Pods 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 Pods Experiments use?
About 1.3k tokens (SKILL.md is roughly 5.4k 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 Pods Experiments?
Skills that share tags, products or a category with Pods 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 Pods 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.