Peer Review
K-Dense-AI/claude-scientific-writer
Prepare evidence-bounded, constructive peer-review drafts and structured manuscript assessments.
Agent skill
Ecai Artifact Evaluation
by brycewang-stanford in brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when planning the reproducibility/artifact story for an ECAI paper — noting that ECAI/FAIA has NO ACM/IEEE-style artifact-badging committee, so credibility is carried by the…
Install Ecai Artifact Evaluation
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ecai-artifact-evaluation -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills ecai-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/ECAI-Skills/skills/ecai-artifact-evaluation .claude/skills/ecai-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 "ecai-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ECAI-Skills/skills/ecai-artifact-evaluation into .claude/skills/ecai-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ecai-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/ECAI-Skills/skills/ecai-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 ecai-artifact-evaluation -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills ecai-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/ECAI-Skills/skills/ecai-artifact-evaluation .agents/skills/ecai-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 "ecai-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ECAI-Skills/skills/ecai-artifact-evaluation into .agents/skills/ecai-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ecai-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 ecai-artifact-evaluation -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills ecai-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/ECAI-Skills/skills/ecai-artifact-evaluation .cursor/skills/ecai-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 "ecai-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ECAI-Skills/skills/ecai-artifact-evaluation into .cursor/skills/ecai-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ecai-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 ECAI-Skills/skills/ecai-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 ecai-artifact-evaluation -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills ecai-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/ECAI-Skills/skills/ecai-artifact-evaluation .gemini/skills/ecai-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 "ecai-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ECAI-Skills/skills/ecai-artifact-evaluation into .gemini/skills/ecai-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ecai-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 ecai-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 ecai-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/ECAI-Skills/skills/ecai-artifact-evaluation .github/skills/ecai-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 "ecai-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ECAI-Skills/skills/ecai-artifact-evaluation into .github/skills/ecai-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ecai-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 ecai-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 ecai-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/ECAI-Skills/skills/ecai-artifact-evaluation .opencode/skills/ecai-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 "ecai-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ECAI-Skills/skills/ecai-artifact-evaluation into .opencode/skills/ecai-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ecai-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
ecai-artifact-evaluation- GitHub stars
- 1.2k
- Token cost
- ~1.3k tokens
- SKILL.md length
- 507 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when planning the reproducibility/artifact story for an ECAI paper — noting that ECAI/FAIA has NO ACM/IEEE-style artifact-badging committee, so credibility is carried by the…
- Planning the reproducibility/artifact story for an ECAI paper — noting that ECAI/FAIA has NO ACM/IEEE-style artifact-badging committee
- SKILL.md covers Match the artifact to the…, What "good" looks like at…, A pragmatic checklist (adapt,… and Do not import the wrong…, plus 2 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- So credibility is carried by the paper and its supplement and judged by the same reviewers
What it does
Ecai Artifact Evaluation is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when planning the reproducibility/artifact story for an ECAI paper — noting that ECAI/FAIA has NO ACM/IEEE-style artifact-badging committee, so credibility is carried by the paper and its supplement and judged by the same reviewers, and adapting an ML-style reproducibility package (or a complete proof appendix for theory work) to that reality.
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.
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
- Planning the reproducibility/artifact story for an ECAI paper — noting that ECAI/FAIA has NO ACM/IEEE-style artifact-badging committee
- So credibility is carried by the paper and its supplement and judged by the same reviewers
- Adapting an ML-style reproducibility package (or a complete proof appendix for theory work) to that reality
Example prompts
- “/ecai-artifact-evaluation”
Requirements
- Docker
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
Ecai Artifact Evaluation loads about 1.3k tokens when it runs. Until then it costs about 94 tokens; SKILL.md has 507 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). 507 words, ~1,272 tokens.
Download SKILL.mdSave it as
.claude/skills/ecai-artifact-evaluation/SKILL.md (or your agent's skills folder).- name
- ecai-artifact-evaluation
- description
- Use when planning the reproducibility/artifact story for an ECAI paper — noting that ECAI/FAIA has NO ACM/IEEE-style artifact-badging committee, so credibility is carried by the paper and its supplement and judged by the same reviewers, and adapting an ML-style reproducibility package (or a complete proof appendix for theory work) to that reality.
ECAI Artifact Evaluation
Start with a correction that saves authors from importing the wrong workflow: ECAI does not run an ACM/IEEE-style artifact-evaluation track with a separate badge committee. There is no "Artifacts Available / Functional / Reusable / Reproduced" pipeline as at ACM SIGSOFT venues, and no separate artifact deadline to hit after acceptance. In ECAI, the reproducibility story is carried by the paper and its supplement and judged by the same reviewers who read the paper, during the one review round.
That makes the "artifact" a submission-time asset, not a post-acceptance badge chase. Its job is to make the reviewer trust the claim inside a 7-page body. (Confirm on the current call whether the edition adds any optional reproducibility checklist or appendix mechanism — this is 待核实 per cycle and can differ between a standalone ECAI and the joint IJCAI-ECAI 2026.)
Match the artifact to the contribution shape
ECAI is a general-AI venue, so "artifact" means different things:
| Contribution shape | The credibility artifact is... |
|---|---|
| Theory / KR / argumentation | A complete proof appendix (full proofs the body only sketches) plus, if applicable, a reference solver/encoding |
| Planning / search / optimization | The domain files, instances, seeds, and a runnable implementation reproducing the reported node/quality numbers |
| Machine learning | Code, data (or a loader), configs, seeds, and cached outputs so results reproduce without live API calls |
| Multi-agent systems | The environment, agent code, and the exact evaluation protocol (episodes, seeds, metrics) |
| Applied AI (PAIS) | Enough of the pipeline and (sanitized) data to make the deployment claim credible |
What "good" looks like at review time
- Anonymized. The supplement is read under double-blind review; strip repository owners,
institution names, and system names that identify you (
ecai-submission). - Self-contained. A reviewer opens it once, in a short window; it must run or be readable without chasing dependencies or your lab's private data.
- Decision-critical content stays in the body. The supplement holds support (full proofs,
extra tables, code) — not the claim itself. Nothing a reviewer needs to judge the paper may
live only in the supplement (
ecai-supplementary). - Proportional. Match effort to the claim: a theory paper's artifact is a rigorous proof appendix, not a Docker image; an empirical paper's artifact is a runnable, seeded package.
Show full SKILL.md (148 more words)Show less
A pragmatic checklist (adapt, don't badge-chase)
[ ] Full proofs present for every theorem the body sketches (theory work)
[ ] Code runs from a clean checkout with a documented entrypoint (empirical work)
[ ] Data included or a script fetches a versioned public source; seeds fixed
[ ] Cached model/API outputs included so results do not re-sample at run time
[ ] A short README maps each paper claim/table -> the file that reproduces it
[ ] Archive anonymized: no owner, institution, funding, or system-name leaks
[ ] Total size and runtime reasonable for a reviewer's one-pass readDo not import the wrong machinery
- No ACM/IEEE badges. Do not promise "Artifacts Evaluated - Reusable" or design around a badge committee — none exists at ECAI. Credibility is reviewer-judged, in-band.
- No separate artifact-track deadline. Everything ships with the paper (abstract 12 Jan / paper 19 Jan for IJCAI-ECAI 2026); there is no later artifact submission.
- Not a leaderboard. ECAI values understanding (a proof, a fair comparison) over a single
benchmark number; an artifact that only re-prints a leaderboard score misses the venue's bar
(
ecai-experiments).
Post-acceptance: make it permanent and open
Once accepted, convert the anonymized supplement into a permanent, open release to match ECAI's open-access ethos:
- Deposit code/data in a DOI-issuing archive (e.g. Zenodo/Software Heritage) with an open license.
- De-anonymize repository owners and restore acknowledgements (
ecai-camera-ready). - Put the permanent link in the camera-ready so the open-access paper points to a stable artifact.
Output format
[Artifact type] proof appendix / runnable code+data / environment+protocol / deployment pipeline
[Anonymity] clean / leaks: <where>
[Claim map] each theorem/table -> proof or reproducing file
[Self-containment] runs/readable in one pass? missing deps: <list>
[Reality check] no ACM/IEEE badge assumed; nothing decision-critical hidden in the supplement
[Post-acceptance] DOI archive + open license + de-anonymized link planned for camera-ready© 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 ECAI-Skills/skills/ecai-artifact-evaluation of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Ecai 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 |
|---|---|---|---|---|---|---|
| Ecai Artifact Evaluation this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.3k | 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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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/.
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Categories
Questions about Ecai Artifact Evaluation
What does Ecai Artifact Evaluation do?
A skill your agent uses when planning the reproducibility/artifact story for an ECAI paper — noting that ECAI/FAIA has NO ACM/IEEE-style artifact-badging committee, so credibility is carried by the…. Ecai Artifact Evaluation is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when planning the reproducibility/artifact story for an ECAI paper — noting that ECAI/FAIA has NO ACM/IEEE-style artifact-badging committee, so credibility is carried by the paper and its supplement and judged by the same reviewers, and adapting an ML-style reproducibility package (or a complete proof appendix for theory work) to that reality.
When should I use Ecai Artifact Evaluation?
Ecai Artifact Evaluation fits situations like: planning the reproducibility/artifact story for an ECAI paper — noting that ECAI/FAIA has NO ACM/IEEE-style artifact-badging committee; so credibility is carried by the paper and its supplement and judged by the same reviewers; adapting an ML-style reproducibility package (or a complete proof appendix for theory work) to that reality.
How do I install Ecai Artifact Evaluation in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ecai-artifact-evaluation -a claude-code`. Or copy the skill folder (ECAI-Skills/skills/ecai-artifact-evaluation in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/ecai-artifact-evaluation in your project. Claude Code loads it when a task matches its description.
How do I install Ecai Artifact Evaluation in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ecai-artifact-evaluation -a codex`. Or copy the skill folder (ECAI-Skills/skills/ecai-artifact-evaluation in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/ecai-artifact-evaluation in your project. Codex loads it when a task matches its description.
Can I use Ecai 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 ecai-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/ecai-artifact-evaluation, .gemini/skills/ecai-artifact-evaluation, .github/skills/ecai-artifact-evaluation and .opencode/skills/ecai-artifact-evaluation in your project.
What does Ecai Artifact Evaluation need to run?
SKILL.md names no scripts, command-line tools or credentials: Ecai Artifact Evaluation is instructions for the agent only. Our summary lists: Docker.
Does Ecai 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 Ecai 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 Ecai Artifact Evaluation use?
Ecai 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 Ecai Artifact Evaluation use?
About 1.3k tokens (SKILL.md is roughly 5.1k 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 Ecai Artifact Evaluation?
Skills that share tags, products or a category with Ecai 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 Ecai 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.