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 experimental program of an ECCV paper — benchmark selection that survives a September conference, matched-substrate baseline fairness in the…
MITAuto-check passed
Install Eccv Experiments
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill eccv-experiments -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills eccv-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/ECCV-Skills/skills/eccv-experiments .claude/skills/eccv-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 "eccv-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ECCV-Skills/skills/eccv-experiments into .claude/skills/eccv-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eccv-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/ECCV-Skills/skills/eccv-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 eccv-experiments -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills eccv-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/ECCV-Skills/skills/eccv-experiments .agents/skills/eccv-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 "eccv-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ECCV-Skills/skills/eccv-experiments into .agents/skills/eccv-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eccv-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 eccv-experiments -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills eccv-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/ECCV-Skills/skills/eccv-experiments .cursor/skills/eccv-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 "eccv-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ECCV-Skills/skills/eccv-experiments into .cursor/skills/eccv-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eccv-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 ECCV-Skills/skills/eccv-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 eccv-experiments -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills eccv-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/ECCV-Skills/skills/eccv-experiments .gemini/skills/eccv-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 "eccv-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ECCV-Skills/skills/eccv-experiments into .gemini/skills/eccv-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eccv-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 eccv-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 eccv-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/ECCV-Skills/skills/eccv-experiments .github/skills/eccv-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 "eccv-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ECCV-Skills/skills/eccv-experiments into .github/skills/eccv-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eccv-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 eccv-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 eccv-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/ECCV-Skills/skills/eccv-experiments .opencode/skills/eccv-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 "eccv-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ECCV-Skills/skills/eccv-experiments into .opencode/skills/eccv-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eccv-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
eccv-experiments- GitHub stars
- 1.2k
- Token cost
- ~1.1k tokens
- SKILL.md length
- 431 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 experimental program of an ECCV paper — benchmark selection that survives a September conference, matched-substrate baseline fairness in the…
- Auditing the experimental program of an ECCV paper — benchmark selection that survives a September conference
- SKILL.md covers The six-month-staleness test, Matched-substrate fairness, Ablations that isolate, not… and Qualitative evidence discipline, plus 2 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Matched-substrate baseline fairness in the foundation-model era
What it does
Eccv Experiments is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when designing or auditing the experimental program of an ECCV paper — benchmark selection that survives a September conference, matched-substrate baseline fairness in the foundation-model era, ablations that isolate the claimed mechanism, qualitative failure evidence, and run sequencing toward a March freeze.
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.
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 experimental program of an ECCV paper — benchmark selection that survives a September conference
- Matched-substrate baseline fairness in the foundation-model era
- Ablations that isolate the claimed mechanism
- Qualitative failure evidence
Example prompts
- “/eccv-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
Eccv Experiments loads about 1.1k tokens when it runs. Until then it costs about 83 tokens; SKILL.md has 431 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). 431 words, ~1,055 tokens.
Download SKILL.mdSave it as
.claude/skills/eccv-experiments/SKILL.md (or your agent's skills folder).- name
- eccv-experiments
- description
- Use when designing or auditing the experimental program of an ECCV paper — benchmark selection that survives a September conference, matched-substrate baseline fairness in the foundation-model era, ablations that isolate the claimed mechanism, qualitative failure evidence, and run sequencing toward a March freeze.
ECCV Experiments
Use this while the experimental plan is still changeable. ECCV's calendar shapes the evidence problem: results freeze in early March, reviews weigh them in May against everything published since, and the field first reads the paper at a September conference — the numbers must still look current six months after the freeze.
The six-month-staleness test
For each headline table, ask: if the strongest lab in this niche publishes their CVPR camera-ready in June, does this table still support the claim in September? Evidence that passes: mechanism-isolating ablations, efficiency frontiers (accuracy vs compute), and generality sweeps across datasets. Evidence that fails: a raw leaderboard number 0.2 points above a moving SOTA. Build the paper's claim on the first kind and let the leaderboard row be corroboration, not the thesis.
Matched-substrate fairness
The first thing a 2026-era vision reviewer checks is whether wins come from the method or from what it was fed:
| Axis to match | Unfair pattern | Fair protocol |
|---|---|---|
| Backbone / pretraining | Your ViT-L vs their ResNet-50 numbers | Re-run the top baselines on your backbone, or add a matched-backbone row |
| Training data | Extra pseudo-labeled or web data only on your side | A same-data row, with the extra-data row labeled as such |
| Input resolution / TTA | Higher test resolution quoted against lower | State resolution and TTA per row |
| Compute / epochs | 4x schedule vs baselines' 1x | Report schedule; add an equal-budget row |
| Foundation-model access | API model in your pipeline, none in baselines | Give baselines the same tool or ablate it out |
One honest matched row protects the paper better than three inflated rows — the mismatched-substrate objection is the most common substantive ECCV review attack and cannot be answered in a one-page rebuttal without a matched number already in hand.
Show full SKILL.md (146 more words)Show less
Ablations that isolate, not decorate
- Each claimed component gets exactly one toggle row; combinatorial grids go to the supplement.
- Include the "replace with the dumb version" row (attention → average, learned prior → uniform): it distinguishes mechanism from capacity.
- Ablate on the mid-sized benchmark, not the smallest one, so effects clear
seed noise (
eccv-reproducibilityfor the variance bar).
Qualitative evidence discipline
Vision panels weigh pixels. Ship, in body or supplement: same-scene comparisons against the two strongest baselines; a random-sample grid (not curated) for at least one dataset; and a failure panel tied to the limitations paragraph. A paper with only curated successes reads as hiding something — the failure panel is credibility infrastructure.
Run sequencing toward March 5
T-10 weeks: falsifier first — the experiment most likely to kill the
claim (matched-substrate row on the main benchmark)
T-8: main-table runs launched; seeds x3 on deciding rows
T-6: ablation toggles; efficiency/frontier measurements
T-4: cross-dataset generality; qualitative harvesting begins
T-2: freeze new runs; regenerate all tables from logged results
T-1: random-sample grids, failure panel, supplement tables
T-0 (Mar 5): body tables locked; supplement week polishes, never addsLaunching the falsifier first is the ECCV-specific discipline: with a biennial venue, discovering at T-2 that the matched row erases the win wastes not a cycle but two years.
Output format
[Evidence verdict] mechanism-backed / leaderboard-fragile / incomplete
[Staleness test] <headline table -> survives September? why>
[Substrate audit] <axis -> matched / mismatched -> repair row needed>
[Ablation map] <claimed component -> isolating toggle present?>
[Run queue] <next runs in falsifier-first order with weeks-to-freeze>© 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 ECCV-Skills/skills/eccv-experiments of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Eccv 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 |
|---|---|---|---|---|---|---|
| Eccv Experiments this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.1k | Automated safety check: Pass | MIT | |
| Design Audit Against Rams' Principlesthedotmack/claude-mem | 98k | — | ~4.6k | Automated safety check: Pass | Apache-2.0 | |
| Experiment Designeralirezarezvani/claude-skills | 28k | 1 repos | ~783 | Automated safety check: Pass | MIT | |
| Experimental Designaiming-lab/AutoResearchClaw | 15k | — | ~286 | Automated safety check: Pass | MIT | |
| 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 |
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Experimental Design
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Experiment Audit
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Questions about Eccv Experiments
What does Eccv Experiments do?
A skill your agent uses when designing or auditing the experimental program of an ECCV paper — benchmark selection that survives a September conference, matched-substrate baseline fairness in the…. Eccv Experiments is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when designing or auditing the experimental program of an ECCV paper — benchmark selection that survives a September conference, matched-substrate baseline fairness in the foundation-model era, ablations that isolate the claimed mechanism, qualitative failure evidence, and run sequencing toward a March freeze.
When should I use Eccv Experiments?
Eccv Experiments fits situations like: auditing the experimental program of an ECCV paper — benchmark selection that survives a September conference; matched-substrate baseline fairness in the foundation-model era; ablations that isolate the claimed mechanism; qualitative failure evidence.
How do I install Eccv Experiments in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill eccv-experiments -a claude-code`. Or copy the skill folder (ECCV-Skills/skills/eccv-experiments in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/eccv-experiments in your project. Claude Code loads it when a task matches its description.
How do I install Eccv Experiments in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill eccv-experiments -a codex`. Or copy the skill folder (ECCV-Skills/skills/eccv-experiments in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/eccv-experiments in your project. Codex loads it when a task matches its description.
Can I use Eccv 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 eccv-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/eccv-experiments, .gemini/skills/eccv-experiments, .github/skills/eccv-experiments and .opencode/skills/eccv-experiments in your project.
What does Eccv Experiments need to run?
SKILL.md names no scripts, command-line tools or credentials: Eccv Experiments is instructions for the agent only.
Does Eccv 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 Eccv 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 Eccv Experiments use?
Eccv 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 Eccv Experiments use?
About 1.1k tokens (SKILL.md is roughly 4.2k 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 Eccv Experiments?
Skills that share tags, products or a category with Eccv Experiments: Design Audit Against Rams' Principles (thedotmack/claude-mem, 98k stars), Experiment Designer (alirezarezvani/claude-skills, 28k stars), Experimental Design (aiming-lab/AutoResearchClaw, 15k stars) and Experiment Audit (wanshuiyin/Auto-claude-code-research-in-sleep, 17k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Eccv Experiments?
brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,219 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.