Hypothesis Generation
spacering-net/codeg
Structured hypothesis formulation from observations. An agent skill from spacering-net/codeg.
A skill your agent uses when reasoning about the ACM MM (ACM Multimedia) review pipeline — thematic-area routing to reviewers and area chairs, the OpenReview double-blind process and its…
Install Acmmm Review Process
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill acmmm-review-process -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills acmmm-review-process --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-review-process .claude/skills/acmmm-review-process && 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-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ACM-MM-Skills/skills/acmmm-review-process into .claude/skills/acmmm-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "acmmm-review-process", 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-review-processType 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-review-process -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills acmmm-review-process --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-review-process .agents/skills/acmmm-review-process && 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-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ACM-MM-Skills/skills/acmmm-review-process into .agents/skills/acmmm-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "acmmm-review-process", 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-review-process -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills acmmm-review-process --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-review-process .cursor/skills/acmmm-review-process && 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-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ACM-MM-Skills/skills/acmmm-review-process into .cursor/skills/acmmm-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "acmmm-review-process", 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-review-process--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-review-process -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills acmmm-review-process --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-review-process .gemini/skills/acmmm-review-process && 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-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ACM-MM-Skills/skills/acmmm-review-process into .gemini/skills/acmmm-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "acmmm-review-process", 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-review-processInstalls 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-review-process -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-review-process .github/skills/acmmm-review-process && 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-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ACM-MM-Skills/skills/acmmm-review-process into .github/skills/acmmm-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "acmmm-review-process", 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-review-process -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-review-process --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-review-process .opencode/skills/acmmm-review-process && 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-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ACM-MM-Skills/skills/acmmm-review-process into .opencode/skills/acmmm-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "acmmm-review-process", 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-review-process- GitHub stars
- 1.2k
- Token cost
- ~1.1k tokens
- SKILL.md length
- 529 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when reasoning about the ACM MM (ACM Multimedia) review pipeline — thematic-area routing to reviewers and area chairs, the OpenReview double-blind process and its…
- Works in 6 steps: Submission + thematic area. The paper… → Assignment. Reviewers and an AC are… → Reviews. Reviewers assess novelty,… → …
- Reasoning about the ACM MM (ACM Multimedia) review pipeline — thematic-area routing to reviewers and area chairs
- SKILL.md covers The pipeline, Where leverage exists, Reading a review set and Double-blind and its exceptions, plus 5 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Acmmm Review Process is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when reasoning about the ACM MM (ACM Multimedia) review pipeline — thematic-area routing to reviewers and area chairs, the OpenReview double-blind process and its single-blind track exceptions, the optional anonymous rebuttal, the meta-review and decision, and the oral/poster and award tiers, and where an author actually has leverage.
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. 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
- Reasoning about the ACM MM (ACM Multimedia) review pipeline — thematic-area routing to reviewers and area chairs
- The OpenReview double-blind process and its single-blind track exceptions
- The optional anonymous rebuttal
- The meta-review and decision
Example prompts
- “/acmmm-review-process”
Workflow steps
6 steps, taken from the first numbered list in SKILL.md.
- Submission + thematic area. The paper enters OpenReview under a chosen thematic area,
- Assignment. Reviewers and an AC are assigned; a mismatched thematic area is where papers
- Reviews. Reviewers assess novelty, cross-modal soundness, evidence (including user
- Rebuttal. An optional, anonymous author response addresses reviews; new external
- Discussion + meta-review. Reviewers and the AC discuss; the AC writes a meta-review and
- Decision + tiers. Accept/reject, with accepted papers sorted into presentation tiers
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 Review Process loads about 1.1k tokens when it runs. Until then it costs about 90 tokens; SKILL.md has 529 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). 529 words, ~1,134 tokens.
Download SKILL.mdSave it as
.claude/skills/acmmm-review-process/SKILL.md (or your agent's skills folder).- name
- acmmm-review-process
- description
- Use when reasoning about the ACM MM (ACM Multimedia) review pipeline — thematic-area routing to reviewers and area chairs, the OpenReview double-blind process and its single-blind track exceptions, the optional anonymous rebuttal, the meta-review and decision, and the oral/poster and award tiers, and where an author actually has leverage.
ACM MM Review Process
Use this to build an accurate mental model of how an ACM Multimedia paper is judged, so strategy targets the points where an author can move the outcome and not the points where they cannot.
The pipeline
- Submission + thematic area. The paper enters OpenReview under a chosen thematic area, which routes it to a matching reviewer pool and area chair.
- Assignment. Reviewers and an AC are assigned; a mismatched thematic area is where papers get reviewers who cannot judge the contribution.
- Reviews. Reviewers assess novelty, cross-modal soundness, evidence (including user studies where relevant), and reproducibility.
- Rebuttal. An optional, anonymous author response addresses reviews; new external links are not allowed.
- Discussion + meta-review. Reviewers and the AC discuss; the AC writes a meta-review and recommendation.
- Decision + tiers. Accept/reject, with accepted papers sorted into presentation tiers (oral vs. poster) and award consideration.
Where leverage exists
| Stage | Author leverage | Reality |
|---|---|---|
| Thematic-area choice | High | You pick who reviews you — choose the area that can judge the contribution |
| Submission quality | High | The paper is the main lever; the rebuttal only patches |
| Rebuttal | Medium | Fix factual errors and add small confirmatory results; rarely flips a strong reject |
| Discussion | Low/indirect | You cannot see it; a clean rebuttal gives the AC ammunition |
| Decision/tiers | None directly | Set by AC/PC after discussion |
Reading a review set
- Separate factual errors (a reviewer misread a result) from judgment (they find the delta small); the first is fixable in rebuttal, the second usually is not.
- Weight the cross-modal critiques: "the fusion is not shown to matter" is often the decisive line, and an ablation is the answer.
- Note the AC's implicit questions in the meta-review; that is who the rebuttal is really written for.
Double-blind and its exceptions
The main track and Brave New Ideas are double-blind; the Reproducibility, Open Source Software, and Dataset tracks are single-blind because the artifact carries its identity. Confidentiality runs both ways: reviewers must not deanonymize authors, and authors must not try to identify or contact reviewers.
Show full SKILL.md (191 more words)Show less
What the rebuttal cannot do
CAN: correct misreadings, add a promised small experiment/ablation, clarify scope, concede narrowly
CANNOT: add new external links, change the contribution, add pages, argue the reviewer is unqualifiedReading scores and the meta-review
- A spread of scores (one champion, one detractor) is normal; the rebuttal targets the detractor's concrete objection and gives the champion and AC something to cite.
- A uniform lukewarm set is harder than a split — there is no champion to convert, so the rebuttal must move a shared concern, usually the cross-modal-significance one.
- Weight the AC's meta-review most: it is the synthesis the decision rests on, and its implicit questions are what your response should answer.
The dates that constrain strategy
The pipeline has a long middle: reviews and rebuttal cluster in late spring, and the decision lands in early July (2026: rebuttal around June 4, notification early July). The strategic consequence is that the confirmatory experiments a reviewer will ask for should be ready before reviews arrive — the rebuttal window is too short to start a new user study or a large ablation from scratch.
Confidentiality and conduct
- Treat all reviews and discussion as confidential.
- Do not attempt to deanonymize reviewers or lobby ACs outside the system.
- Report suspected violations through the official channel, not by public posting.
Output format
[Area routing] well-matched / mismatched (off-topic review risk)
[Review split] factual-fixable: <list> | judgment: <list>
[Decisive critique] <usually the cross-modal/evidence line>
[Rebuttal leverage] high / medium / low
[Next action] <what to fix vs. what to accept>© 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-review-process of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Acmmm Review Process 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 Review Process this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.1k | Automated safety check: Pass | MIT | |
| Hypothesis Generationspacering-net/codeg | 3.9k | 14 repos | ~3.6k | Automated safety check: Notes | MIT | |
| GitHub Deep Researchbytedance/deer-flow | 84k | 4 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Nature Paper CardYuan1z0825/nature-skills | 47k | 2 repos | ~2.1k | Automated safety check: Pass | Apache-2.0 | |
| Content Research Writerweapp-tailwindcss/weapp-tailwindcss | 1.9k | 25 repos | ~3.5k | Automated safety check: Pass | MIT | |
| Last30daysmvanhorn/last30days-skill | 64k | — | ~7.9k | Automated safety check: Notes | MIT |
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GitHub Deep Research
bytedance/deer-flow
Researches a GitHub repository over four rounds using the GitHub API and web search, then writes a structured markdown report with timeline, metrics and Mermaid diagrams.
Nature Paper Card
Yuan1z0825/nature-skills
Builds a structured deep-reading card for one scientific paper, covering methods, how experiments support claims, limitations and research ideas, with a script to prepare the source.
Content Research Writer
weapp-tailwindcss/weapp-tailwindcss
Assists in writing high-quality content by conducting research, adding citations, improving hooks, iterating on outlines, and providing real-time feedback on each section.
Last30days
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Research what people actually say about any topic in the last 30 days.
Peer Review
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Structured manuscript/grant review with checklist-based evaluation.
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Categories
Questions about Acmmm Review Process
What does Acmmm Review Process do?
A skill your agent uses when reasoning about the ACM MM (ACM Multimedia) review pipeline — thematic-area routing to reviewers and area chairs, the OpenReview double-blind process and its…. Acmmm Review Process is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when reasoning about the ACM MM (ACM Multimedia) review pipeline — thematic-area routing to reviewers and area chairs, the OpenReview double-blind process and its single-blind track exceptions, the optional anonymous rebuttal, the meta-review and decision, and the oral/poster and award tiers, and where an author actually has leverage.
When should I use Acmmm Review Process?
Acmmm Review Process fits situations like: reasoning about the ACM MM (ACM Multimedia) review pipeline — thematic-area routing to reviewers and area chairs; the OpenReview double-blind process and its single-blind track exceptions; the optional anonymous rebuttal; the meta-review and decision.
How do I install Acmmm Review Process in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill acmmm-review-process -a claude-code`. Or copy the skill folder (ACM-MM-Skills/skills/acmmm-review-process in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/acmmm-review-process in your project. Claude Code loads it when a task matches its description.
How do I install Acmmm Review Process in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill acmmm-review-process -a codex`. Or copy the skill folder (ACM-MM-Skills/skills/acmmm-review-process in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/acmmm-review-process in your project. Codex loads it when a task matches its description.
Can I use Acmmm Review Process 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-review-process -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-review-process, .gemini/skills/acmmm-review-process, .github/skills/acmmm-review-process and .opencode/skills/acmmm-review-process in your project.
What does Acmmm Review Process need to run?
SKILL.md names no scripts, command-line tools or credentials: Acmmm Review Process is instructions for the agent only.
Does Acmmm Review Process 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 Review Process 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 Review Process use?
Acmmm Review Process 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 Review Process use?
About 1.1k tokens (SKILL.md is roughly 4.5k 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 Review Process?
Skills that share tags, products or a category with Acmmm Review Process: Hypothesis Generation (spacering-net/codeg, 3.9k stars), GitHub Deep Research (bytedance/deer-flow, 84k stars), Nature Paper Card (Yuan1z0825/nature-skills, 47k stars) and Content Research Writer (weapp-tailwindcss/weapp-tailwindcss, 1.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Acmmm Review Process?
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.