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 experiments of an ACM MM (ACM Multimedia) paper — matched baselines per modality, ablations that isolate the cross-modal fusion, user studies…
MITAuto-check passed
Install Acmmm Experiments
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill acmmm-experiments -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills acmmm-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/ACM-MM-Skills/skills/acmmm-experiments .claude/skills/acmmm-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 "acmmm-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ACM-MM-Skills/skills/acmmm-experiments into .claude/skills/acmmm-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "acmmm-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/ACM-MM-Skills/skills/acmmm-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 acmmm-experiments -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills acmmm-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/ACM-MM-Skills/skills/acmmm-experiments .agents/skills/acmmm-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 "acmmm-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ACM-MM-Skills/skills/acmmm-experiments into .agents/skills/acmmm-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "acmmm-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 acmmm-experiments -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills acmmm-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/ACM-MM-Skills/skills/acmmm-experiments .cursor/skills/acmmm-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 "acmmm-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ACM-MM-Skills/skills/acmmm-experiments into .cursor/skills/acmmm-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "acmmm-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 ACM-MM-Skills/skills/acmmm-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 acmmm-experiments -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills acmmm-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/ACM-MM-Skills/skills/acmmm-experiments .gemini/skills/acmmm-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 "acmmm-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ACM-MM-Skills/skills/acmmm-experiments into .gemini/skills/acmmm-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "acmmm-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 acmmm-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 acmmm-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/ACM-MM-Skills/skills/acmmm-experiments .github/skills/acmmm-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 "acmmm-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ACM-MM-Skills/skills/acmmm-experiments into .github/skills/acmmm-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "acmmm-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 acmmm-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 acmmm-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/ACM-MM-Skills/skills/acmmm-experiments .opencode/skills/acmmm-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 "acmmm-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ACM-MM-Skills/skills/acmmm-experiments into .opencode/skills/acmmm-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "acmmm-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
acmmm-experiments- GitHub stars
- 1.2k
- Token cost
- ~1.3k tokens
- SKILL.md length
- 598 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 experiments of an ACM MM (ACM Multimedia) paper — matched baselines per modality, ablations that isolate the cross-modal fusion, user studies…
- Auditing the experiments of an ACM MM (ACM Multimedia) paper — matched baselines per modality
- SKILL.md covers The four questions and how to…, Matched baselines, Ablations that isolate the… and User studies and QoE, plus 5 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Ablations that isolate the cross-modal fusion
What it does
Acmmm Experiments is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when designing or auditing the experiments of an ACM MM (ACM Multimedia) paper — matched baselines per modality, ablations that isolate the cross-modal fusion, user studies or QoE measurement where the claim is subjective, dataset and media licensing, and honest compute reporting, so evidence supports a multimedia 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 experiments of an ACM MM (ACM Multimedia) paper — matched baselines per modality
- Ablations that isolate the cross-modal fusion
- QoE measurement where the claim is subjective
- Dataset and media licensing
Example prompts
- “/acmmm-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
Acmmm Experiments loads about 1.3k tokens when it runs. Until then it costs about 86 tokens; SKILL.md has 598 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). 598 words, ~1,336 tokens.
Download SKILL.mdSave it as
.claude/skills/acmmm-experiments/SKILL.md (or your agent's skills folder).- name
- acmmm-experiments
- description
- Use when designing or auditing the experiments of an ACM MM (ACM Multimedia) paper — matched baselines per modality, ablations that isolate the cross-modal fusion, user studies or QoE measurement where the claim is subjective, dataset and media licensing, and honest compute reporting, so evidence supports a multimedia claim.
ACM MM Experiments
Use this to make an ACM Multimedia paper's evidence match its claim. The reviewer's implicit questions are: does it work, does the cross-modal part cause the gain, when does it fail, and — if the target is perceptual — do people actually prefer it.
The four questions and how to answer them
| Question | Evidence that answers it |
|---|---|
| Does it work? | The headline metric on a recognized benchmark, against strong, matched baselines |
| Does the fusion cause the gain? | A leave-one-modality-out / component ablation isolating the cross-modal term |
| When does it fail? | Failure cases per modality (e.g., noisy audio, missing captions) shown honestly |
| Do people prefer it? | A user study with reported N, protocol, and inter-rater agreement — for subjective claims |
The second row is what separates an ACM MM experiment section from a single-modality one: if removing a modality does not move the result, the paper is not really cross-modal.
Matched baselines
- Compare against the strongest existing method, re-run under your data and preprocessing where feasible, not a weakened reimplementation.
- Include a late-fusion / naive-concatenation baseline so the reader sees what the fancy fusion buys over the obvious one.
- Hold everything but the mechanism fixed: same backbone, same features, same training budget, so the delta is attributable.
Ablations that isolate the cross-modal claim
Full model .................... reference
- audio stream ................ tests whether audio carries signal
- text/caption stream ......... tests whether language carries signal
- alignment / fusion module ... replaced by concatenation: tests the MECHANISM
- synchronization assumption .. shuffled timing: tests whether cross-modal timing mattersReport each ablation with the same metric and variance as the headline, and state which term carries most of the gain — reviewers reward a paper that can point to why it works.
User studies and QoE
When the claim is subjective (quality, naturalness, engagement, aesthetics), a benchmark number is not enough:
- Pre-register the protocol: task, number of raters, stimuli, and the question asked.
- Report inter-rater agreement and a significance test, not just a mean preference.
- Describe compensation and consent briefly; a study a reviewer cannot assess is discounted.
Data, media, and compute honesty
- State dataset licenses and any consent/usage terms for media, especially for user-generated or scraped content.
- Report compute (hardware, training time) so cost is legible; a cross-modal model that only wins at 10x compute should say so.
- Fix and report seeds; report variance over runs where the margin is small.
Show full SKILL.md (246 more words)Show less
Benchmarks and metrics per modality
A cross-modal paper is judged against each community's expectations at once, so pick metrics each sub-field recognizes rather than a single convenient number.
- Retrieval / recommendation — report ranking metrics (Recall@K, mAP, NDCG) and say which gallery/query split, because cross-modal retrieval numbers are split-sensitive.
- Generation / synthesis — pair a distributional metric with a human/QoE judgment; automatic scores for generated media correlate imperfectly with perceived quality.
- Recognition / detection — use the standard task metric, but show the multimodal case, not only the clean single-modality one.
- Systems / delivery — report latency, throughput, and bitrate/quality trade-offs, not just accuracy.
State the metric's direction and any threshold, and keep the same metric across the headline table and every ablation so the reader can trace the fusion's contribution row by row.
Statistical reporting
- Report variance (standard deviation or confidence interval) over runs when margins are small; a single-seed win on a close benchmark is not persuasive.
- For user studies, report a significance test and inter-rater agreement, not a bare mean.
- Do not average away modality-specific behavior: a model that helps on audio-rich clips and hurts on silent ones should show that split, not hide it in a global mean.
Common ACM MM experiment failures
- Fusion that does not matter — ablations show no modality is load-bearing.
- Weak baselines — beating only a vision-only or text-only strawman.
- Asserted perception — "more natural" with no user study.
- Unlicensed media — datasets used without stating rights.
- Hidden cost — big gains that quietly require far more compute.
Output format
[Works] strong/matched baselines / weak or unmatched: <which>
[Fusion causal] ablation isolates the mechanism / does not
[Failure analysis] present per modality / missing
[Perceptual claim] user study with agreement / asserted
[Data + compute] licenses and cost reported / gaps: <list>
[Top fixes] <ordered before submission or rebuttal>© 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 ACM-MM-Skills/skills/acmmm-experiments of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Acmmm 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 |
|---|---|---|---|---|---|---|
| Acmmm 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 Acmmm Experiments
What does Acmmm Experiments do?
A skill your agent uses when designing or auditing the experiments of an ACM MM (ACM Multimedia) paper — matched baselines per modality, ablations that isolate the cross-modal fusion, user studies…. Acmmm Experiments is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when designing or auditing the experiments of an ACM MM (ACM Multimedia) paper — matched baselines per modality, ablations that isolate the cross-modal fusion, user studies or QoE measurement where the claim is subjective, dataset and media licensing, and honest compute reporting, so evidence supports a multimedia claim.
When should I use Acmmm Experiments?
Acmmm Experiments fits situations like: auditing the experiments of an ACM MM (ACM Multimedia) paper — matched baselines per modality; ablations that isolate the cross-modal fusion; qoE measurement where the claim is subjective; dataset and media licensing.
How do I install Acmmm Experiments in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill acmmm-experiments -a claude-code`. Or copy the skill folder (ACM-MM-Skills/skills/acmmm-experiments in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/acmmm-experiments in your project. Claude Code loads it when a task matches its description.
How do I install Acmmm Experiments in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill acmmm-experiments -a codex`. Or copy the skill folder (ACM-MM-Skills/skills/acmmm-experiments in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/acmmm-experiments in your project. Codex loads it when a task matches its description.
Can I use Acmmm 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 acmmm-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/acmmm-experiments, .gemini/skills/acmmm-experiments, .github/skills/acmmm-experiments and .opencode/skills/acmmm-experiments in your project.
What does Acmmm Experiments need to run?
SKILL.md names no scripts, command-line tools or credentials: Acmmm Experiments is instructions for the agent only.
Does Acmmm 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 Acmmm 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 Acmmm Experiments use?
Acmmm 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 Acmmm Experiments use?
About 1.3k tokens (SKILL.md is roughly 5.3k 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 Acmmm Experiments?
Skills that share tags, products or a category with Acmmm 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 Acmmm 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.