Peer Review
K-Dense-AI/claude-scientific-writer
Prepare evidence-bounded, constructive peer-review drafts and structured manuscript assessments.
Agent skill
Acmmm Artifact Evaluation
by brycewang-stanford in brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when packaging code, models, datasets, or media as ACM MM (ACM Multimedia) artifacts — building the anonymous review package versus the public release, and choosing between…
Install Acmmm Artifact Evaluation
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill acmmm-artifact-evaluation -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills acmmm-artifact-evaluation --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-artifact-evaluation .claude/skills/acmmm-artifact-evaluation && 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-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ACM-MM-Skills/skills/acmmm-artifact-evaluation into .claude/skills/acmmm-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "acmmm-artifact-evaluation", 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-artifact-evaluationType 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-artifact-evaluation -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills acmmm-artifact-evaluation --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-artifact-evaluation .agents/skills/acmmm-artifact-evaluation && 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-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ACM-MM-Skills/skills/acmmm-artifact-evaluation into .agents/skills/acmmm-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "acmmm-artifact-evaluation", 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-artifact-evaluation -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills acmmm-artifact-evaluation --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-artifact-evaluation .cursor/skills/acmmm-artifact-evaluation && 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-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ACM-MM-Skills/skills/acmmm-artifact-evaluation into .cursor/skills/acmmm-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "acmmm-artifact-evaluation", 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-artifact-evaluation--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-artifact-evaluation -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills acmmm-artifact-evaluation --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-artifact-evaluation .gemini/skills/acmmm-artifact-evaluation && 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-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ACM-MM-Skills/skills/acmmm-artifact-evaluation into .gemini/skills/acmmm-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "acmmm-artifact-evaluation", 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-artifact-evaluationInstalls 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-artifact-evaluation -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-artifact-evaluation .github/skills/acmmm-artifact-evaluation && 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-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ACM-MM-Skills/skills/acmmm-artifact-evaluation into .github/skills/acmmm-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "acmmm-artifact-evaluation", 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-artifact-evaluation -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-artifact-evaluation --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-artifact-evaluation .opencode/skills/acmmm-artifact-evaluation && 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-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ACM-MM-Skills/skills/acmmm-artifact-evaluation into .opencode/skills/acmmm-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "acmmm-artifact-evaluation", 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-artifact-evaluation- GitHub stars
- 1.2k
- Token cost
- ~1.1k tokens
- SKILL.md length
- 454 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when packaging code, models, datasets, or media as ACM MM (ACM Multimedia) artifacts — building the anonymous review package versus the public release, and choosing between…
- Media as ACM MM (ACM Multimedia) artifacts — building the anonymous review package versus the public release
- SKILL.md covers Which track is the artifact?, Two artifacts, two audiences, Open Source Software Competition and Dataset track, plus 4 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Choosing between the Open Source Software Competition
What it does
Acmmm Artifact Evaluation is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when packaging code, models, datasets, or media as ACM MM (ACM Multimedia) artifacts — building the anonymous review package versus the public release, and choosing between the Open Source Software Competition, the Dataset track, the Reproducibility track, and main-track supplementary evidence, each with its own blinding and expectations.
Its SKILL.md is about 1.1k 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 Research & Science, covering Reproducible research. 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
- Media as ACM MM (ACM Multimedia) artifacts — building the anonymous review package versus the public release
- Choosing between the Open Source Software Competition
- The Dataset track
- The Reproducibility track
Example prompts
- “/acmmm-artifact-evaluation”
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 Artifact Evaluation loads about 1.1k tokens when it runs. Until then it costs about 93 tokens; SKILL.md has 454 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). 454 words, ~1,138 tokens.
Download SKILL.mdSave it as
.claude/skills/acmmm-artifact-evaluation/SKILL.md (or your agent's skills folder).- name
- acmmm-artifact-evaluation
- description
- Use when packaging code, models, datasets, or media as ACM MM (ACM Multimedia) artifacts — building the anonymous review package versus the public release, and choosing between the Open Source Software Competition, the Dataset track, the Reproducibility track, and main-track supplementary evidence, each with its own blinding and expectations.
ACM MM Artifact Evaluation
Use this to turn an ACM Multimedia project's code, models, media, and data into the right artifact for the right track. ACM MM has a track economy around artifacts, and the choice determines blinding, format, and what reviewers judge.
Which track is the artifact?
| Artifact is primarily... | Route to | Blinding | Judged on |
|---|---|---|---|
| A reusable software system/framework | Open Source Software Competition | Single-blind | Adoption, quality, license, docs |
| A new dataset/benchmark | Dataset track | Single-blind | Scale, quality, ethics, usefulness |
| A reproduction of published results | Reproducibility track | Single-blind | Whether results rebuild; ACM badges |
| Supporting evidence for a method paper | Main-track supplement | Double-blind | Whether it backs the paper's claims |
The named single-blind tracks exist because the artifact's identity cannot be hidden; a main-track method paper's artifact, by contrast, must be anonymous through review.
Two artifacts, two audiences
Plan both from the start:
- Anonymous review artifact — what reviewers see during double-blind review: an anonymized repository, an anonymous data mirror, stripped media metadata, and a README that reveals no author identity.
- Public release artifact — what ships at/after camera-ready: the de-anonymized repository, a permanent archive (DOI), the license, and the final dataset/model.
review/ -> anonymous repo, anon data mirror, no names in code/media, run instructions
release/ -> public repo + DOI, LICENSE, model weights, dataset card, citationOpen Source Software Competition
- The bar is a system others will use: clear install, documentation, examples, an OSI-approved license, and evidence of quality or adoption.
- Reference models and reproducible examples matter more than a single benchmark number — this is the lane exemplified by community frameworks and portable libraries.
Dataset track
- Ship a dataset card: collection method, size, splits, license, consent, and known biases or limitations.
- Address ethics and rights explicitly, especially for user-generated or scraped media; a dataset a reviewer cannot legally use is not a contribution.
Show full SKILL.md (180 more words)Show less
Licensing and rights decisions
- Choose a code license (permissive vs. copyleft) and a data license separately; they are not the same choice.
- For media, confirm you have the right to redistribute; where you cannot, provide a retrieval script or agreement path instead of the raw files.
- Record third-party asset licenses so the release is clean.
Ethics and consent for media artifacts
Multimedia artifacts carry people's faces, voices, and content, so the ethics review is not a formality:
- Consent and rights — confirm you may redistribute the media; user-generated content often cannot be re-hosted, so ship a retrieval script or agreement path instead.
- Privacy — remove or justify identifiable individuals who did not consent; a dataset of scraped faces is a rejection risk regardless of its scale.
- Documentation — a dataset card that states collection method, consent, license, and known biases is part of the contribution, not paperwork.
Timeline: review artifact, then release
before paper deadline: anonymous review artifact ready (repo + data mirror, no identity)
during review: reviewers/AC access the anonymous artifact
on acceptance: build the public release (de-anonymized repo + DOI + license)
by camera-ready: release replaces the anonymous mirror; dataset/model finalPlan the public release early even though it ships late — a scramble at camera-ready is how projects end up with a broken anonymous link and no working public archive.
Output format
[Track] Open Source / Dataset / Reproducibility / main-track supplement
[Blinding] correct for track / mismatch
[Review artifact] anonymous + runnable / gaps: <list>
[Release artifact] archived + licensed / gaps: <list>
[Rights] code+data+media licenses set / open questions: <list>
[Top fixes] <ordered>© 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-artifact-evaluation of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Acmmm Artifact Evaluation 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 Artifact Evaluation this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.1k | Automated safety check: Pass | MIT | |
| Peer ReviewK-Dense-AI/claude-scientific-writer | 2.4k | 2 repos | ~3.1k | Automated safety check: Notes | MIT | |
| CHARLS Paper Reproduction Guidexjtulyc/MedgeClaw | 617 | 1 repos | ~1.8k | Automated safety check: Pass | None | |
| Compute Environment Setupaipoch/open-science | 5.5k | — | ~2.6k | Automated safety check: Pass | Apache-2.0 | |
| Figure Styleaipoch/open-science | 5.5k | — | ~5.1k | Automated safety check: Pass | Apache-2.0 | |
| Add Bactopia Toolbactopia/bactopia | 522 | — | ~4.1k | Automated safety check: Pass | MIT |
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xjtulyc/MedgeClaw
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Compute Environment Setup
aipoch/open-science
Prepares setup instructions and a named activation file for a user-managed software environment on an Open-Science SSH or Slurm compute host.
Figure Style
aipoch/open-science
Publication-grade correctness and legibility rules for final-deliverable scientific figures, not exploratory plots.
Add Bactopia Tool
bactopia/bactopia
Scaffold a complete Bactopia Tool across all three tiers -- module, subworkflow, and workflow entry point under workflows/bactopia-tools/.
Modeling Code and Result Contracts
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Generates result-evidence contracts, tables and runnable q1 to q3 modeling code scaffolds for a math modeling paper from a model route, a data plan and cleaned data.
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Categories
Questions about Acmmm Artifact Evaluation
What does Acmmm Artifact Evaluation do?
A skill your agent uses when packaging code, models, datasets, or media as ACM MM (ACM Multimedia) artifacts — building the anonymous review package versus the public release, and choosing between…. Acmmm Artifact Evaluation is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when packaging code, models, datasets, or media as ACM MM (ACM Multimedia) artifacts — building the anonymous review package versus the public release, and choosing between the Open Source Software Competition, the Dataset track, the Reproducibility track, and main-track supplementary evidence, each with its own blinding and expectations.
When should I use Acmmm Artifact Evaluation?
Acmmm Artifact Evaluation fits situations like: media as ACM MM (ACM Multimedia) artifacts — building the anonymous review package versus the public release; choosing between the Open Source Software Competition; the Dataset track; the Reproducibility track.
How do I install Acmmm Artifact Evaluation in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill acmmm-artifact-evaluation -a claude-code`. Or copy the skill folder (ACM-MM-Skills/skills/acmmm-artifact-evaluation in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/acmmm-artifact-evaluation in your project. Claude Code loads it when a task matches its description.
How do I install Acmmm Artifact Evaluation in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill acmmm-artifact-evaluation -a codex`. Or copy the skill folder (ACM-MM-Skills/skills/acmmm-artifact-evaluation in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/acmmm-artifact-evaluation in your project. Codex loads it when a task matches its description.
Can I use Acmmm Artifact Evaluation 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-artifact-evaluation -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-artifact-evaluation, .gemini/skills/acmmm-artifact-evaluation, .github/skills/acmmm-artifact-evaluation and .opencode/skills/acmmm-artifact-evaluation in your project.
What does Acmmm Artifact Evaluation need to run?
SKILL.md names no scripts, command-line tools or credentials: Acmmm Artifact Evaluation is instructions for the agent only.
Does Acmmm Artifact Evaluation 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 Artifact Evaluation 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 Artifact Evaluation use?
Acmmm Artifact Evaluation 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 Artifact Evaluation use?
About 1.1k tokens (SKILL.md is roughly 4.6k 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 Acmmm Artifact Evaluation?
Skills that share tags, products or a category with Acmmm Artifact Evaluation: Peer Review (K-Dense-AI/claude-scientific-writer, 2.4k stars), CHARLS Paper Reproduction Guide (xjtulyc/MedgeClaw, 617 stars), Compute Environment Setup (aipoch/open-science, 5.5k stars) and Figure Style (aipoch/open-science, 5.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Acmmm Artifact Evaluation?
brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,231 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.