acmmm-experiments

acmmm-experiments is a skill for Claude Code from brycewang-stanford/Awesome-Journal-Skills. It costs 68 tokens per session (1,154 once invoked), scanned A, original, MIT.

A guide for designing or reviewing experiments in an ACM Multimedia research paper. It covers comparisons, component-removal tests, failure cases, user studies, datasets, licensing, and computing details.

In plain words
What is it for?
Use it to plan benchmarks, compare against strong existing methods, test whether each input modality matters, report failures, and evaluate subjective results with users.
Why use it?
It helps ensure that the evidence actually supports the paper's claims, especially when a method combines multiple media types.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the ACM-MM-Skills plugin — 6 skills shipped together

Good fit Use it to plan benchmarks, compare against strong existing methods, test whether each input modality matters, report failures, and evaluate subjective results with users.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/brycewang-stanford/awesome-journal-skills/acmmm-experiments
About the project

Awesome Journal Skills is a collection of agent skill packs tailored to hundreds of academic journals across fields including economics, social science, medicine, science, and engineering. Researchers use the packs for tasks such as choosing topics, designing empirical strategies, preparing tables and figures, submitting papers, and responding to reviewers. The catalogue entries are the project's journal-specific skills and related plugins.

brycewang-stanford/Awesome-Journal-Skills · 1,090 stars · on GitHub · copaper.ai

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill acmmm-experiments
Clone the repo
git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills

Made for: Claude Code.

Or install ACM-MM-Skills, the plugin that ships this one along with the rest of its 6 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for acmmm-experiments

README.md
[![agentmods](https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/acmmm-experiments/github.svg)](https://agentmods.dev/skills/brycewang-stanford/awesome-journal-skills/acmmm-experiments)
Your own site
<a href="https://agentmods.dev/skills/brycewang-stanford/awesome-journal-skills/acmmm-experiments"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/acmmm-experiments/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for acmmm-experiments

Your own site · 80×15
<a href="https://agentmods.dev/skills/brycewang-stanford/awesome-journal-skills/acmmm-experiments"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/acmmm-experiments.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 68 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,154 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00068 $0.01154
Opus 5 $0.00034 $0.00577
Sonnet 5 $0.00014 $0.00231
Haiku 4.5 $0.00007 $0.00115

Measured 11d ago against content hash ca3721ccc229, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

acmmm-experiments scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

ACM-MM-Skills/skills/acmmm-experiments/SKILL.md · 106 lines

How it starts

The opening of the file, as written. The whole thing — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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 matters

Report 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.

Read the full file on GitHub · 106 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 11d ago First seen · 106 lines · 68 tokens per session scan A ca3721ccc229

Subscribe to this mod's changes

acmmm-experiments is a skill published in the GitHub repository brycewang-stanford/Awesome-Journal-Skills (1,090 stars, last pushed 15d ago), licensed MIT. It adds 68 tokens to every session and 1,154 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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