Peer Review
K-Dense-AI/claude-scientific-writer
Prepare evidence-bounded, constructive peer-review drafts and structured manuscript assessments.
Agent skill
Conext Artifact Evaluation
by brycewang-stanford in brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when converting an accepted ACM CoNEXT paper's package into optional ACM reproducibility badges via the CoNEXT reproducibility committee — from the badge opt-in due before…
Install Conext Artifact Evaluation
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill conext-artifact-evaluation -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills conext-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/CoNEXT-Skills/skills/conext-artifact-evaluation .claude/skills/conext-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 "conext-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/CoNEXT-Skills/skills/conext-artifact-evaluation into .claude/skills/conext-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "conext-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/CoNEXT-Skills/skills/conext-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 conext-artifact-evaluation -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills conext-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/CoNEXT-Skills/skills/conext-artifact-evaluation .agents/skills/conext-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 "conext-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/CoNEXT-Skills/skills/conext-artifact-evaluation into .agents/skills/conext-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "conext-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 conext-artifact-evaluation -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills conext-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/CoNEXT-Skills/skills/conext-artifact-evaluation .cursor/skills/conext-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 "conext-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/CoNEXT-Skills/skills/conext-artifact-evaluation into .cursor/skills/conext-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "conext-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 CoNEXT-Skills/skills/conext-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 conext-artifact-evaluation -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills conext-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/CoNEXT-Skills/skills/conext-artifact-evaluation .gemini/skills/conext-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 "conext-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/CoNEXT-Skills/skills/conext-artifact-evaluation into .gemini/skills/conext-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "conext-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 conext-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 conext-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/CoNEXT-Skills/skills/conext-artifact-evaluation .github/skills/conext-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 "conext-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/CoNEXT-Skills/skills/conext-artifact-evaluation into .github/skills/conext-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "conext-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 conext-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 conext-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/CoNEXT-Skills/skills/conext-artifact-evaluation .opencode/skills/conext-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 "conext-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/CoNEXT-Skills/skills/conext-artifact-evaluation into .opencode/skills/conext-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "conext-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
conext-artifact-evaluation- GitHub stars
- 1.2k
- Token cost
- ~1.2k tokens
- SKILL.md length
- 465 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when converting an accepted ACM CoNEXT paper's package into optional ACM reproducibility badges via the CoNEXT reproducibility committee — from the badge opt-in due before…
- The one-page artifact description due within a week of acceptance
- SKILL.md covers The badge timeline (opt-in is…, The ACM badges (what each…, The one-page artifact… and Networking-specific evaluation…, plus 3 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- The Available / Functional / Reusable / Reproduced criteria and evaluator-proof reuse docs
What it does
Conext Artifact Evaluation is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when converting an accepted ACM CoNEXT paper's package into optional ACM reproducibility badges via the CoNEXT reproducibility committee — from the badge opt-in due before submission, to the one-page artifact description due within a week of acceptance, to the Available / Functional / Reusable / Reproduced criteria and evaluator-proof reuse docs.
Its SKILL.md is about 1.2k 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
- The one-page artifact description due within a week of acceptance
- The Available / Functional / Reusable / Reproduced criteria and evaluator-proof reuse docs
Example prompts
- “/conext-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
Conext Artifact Evaluation loads about 1.2k tokens when it runs. Until then it costs about 95 tokens; SKILL.md has 465 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). 465 words, ~1,249 tokens.
Download SKILL.mdSave it as
.claude/skills/conext-artifact-evaluation/SKILL.md (or your agent's skills folder).- name
- conext-artifact-evaluation
- description
- Use when converting an accepted ACM CoNEXT paper's package into optional ACM reproducibility badges via the CoNEXT reproducibility committee — from the badge opt-in due before submission, to the one-page artifact description due within a week of acceptance, to the Available / Functional / Reusable / Reproduced criteria and evaluator-proof reuse docs.
CoNEXT Artifact Evaluation
Turn the accepted paper's package into optional ACM reproducibility badges, administered by CoNEXT's reproducibility committee. This is a distinct process from the paper review, with its own timing: the decisive move — opting in before the paper submission deadline — happens long before you have an accept. Treat badging as a track you enter at submission and complete after acceptance.
The badge timeline (opt-in is the gate)
[Before submission deadline] OPT IN for ACM badging <-- miss this and you are ineligible this cycle
[Within ~1 week of accept] send a ONE-PAGE artifact description + pointers to the committee
[Post-accept evaluation] committee reviews the artifact against the ACM badge criteria
[Camera-ready] approved badges appear on the PACMNET article (see conext-camera-ready)The ACM badges (what each requires)
CoNEXT uses the ACM Artifact Review and Badging scheme. In practice the ladder is:
| Badge | What it certifies | What you must provide |
|---|---|---|
| Artifacts Available | The artifact is publicly archived | A DOI-issuing archive (Zenodo/figshare/Software Heritage) with an open license |
| Artifacts Evaluated — Functional | It is documented, complete, and runs | Clear docs, a runnable package, and a "getting started" path that works |
| Artifacts Evaluated — Reusable | It is functional and others can build on it | Reusability docs, clean structure, parameterization, and a license that permits reuse |
| Results Reproduced | Key results were regenerated by evaluators | A scripted path that regenerates the paper's central figures/tables from the inputs |
Confirm the exact badge set and names offered by the current CoNEXT reproducibility committee — the scheme is stable but wording is cycle-volatile (待核实).
The one-page artifact description
The committee starts from your one-pager, so make it do work:
- Inventory: code, traces, configs, testbed scripts — with a pointer to each.
- Requirements: the hardware/software an evaluator needs. Networking artifacts often need specific hardware (a particular switch ASIC, NIC, or SDR); if evaluators need access to hardware you must provide, flag it prominently and describe how you will give access.
- Claims supported: which paper results the artifact reproduces, and which it cannot (be honest about hardware-bound results).
- Getting started: the shortest path to a first successful run.
Show full SKILL.md (175 more words)Show less
Networking-specific evaluation hurdles
- Hardware dependence. A result that needs a specific switch or NIC is hard for a remote evaluator; provide a testbed reservation, a remote-access path, or a faithful emulation for the parts that can run in software, and clearly mark what is hardware-bound.
- Trace size and privacy. Large or sensitive traces may not be fully releasable; ship a representative or synthetic subset plus the pipeline, and document the restriction.
- Environment drift. Pin firmware/OS/kernel versions and provide images; "works on our testbed" is not reproducible.
- Live dependencies. Cache anything that would otherwise require a live API/network call so the evaluator's run is deterministic.
Reusability that survives an evaluator
- A README that assumes nothing about your lab's setup; every path and dependency explicit.
- A single command (or a short script) for the "getting started" run, and a documented full-reproduction path for the central results.
- An open license present and consistent across the archive.
- A mapping from paper claim → artifact step → expected output, so an evaluator can check "Results Reproduced" without guessing.
Pre-evaluation checklist
[Opt-in] confirmed before the submission deadline? yes/no
[Archive] DOI-issuing archive + open license? yes/no
[One-pager] inventory + requirements + hardware-access plan + claims map? yes/no
[Functional] fresh-environment run succeeds from the docs alone? yes/no
[Reusable] structure + docs let a third party adapt it? yes/no
[Reproduced] central figures/tables regenerate by script? yes/no
[Hardware] hardware-bound results flagged; access path provided? yes/noOutput format
[Badge target] Available / Functional / Reusable / Reproduced (which are in scope)
[Opt-in status] done before submission? yes/no
[Artifact readiness] <per-badge gaps>
[Hardware plan] <how remote evaluators reach any required hardware>
[One-pager] <drafted / sent to committee>© 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 CoNEXT-Skills/skills/conext-artifact-evaluation of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Conext 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 |
|---|---|---|---|---|---|---|
| Conext Artifact Evaluation this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.2k | 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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CHARLS Paper Reproduction Guide
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
yushui2022/MathModel-Skill
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 Conext Artifact Evaluation
What does Conext Artifact Evaluation do?
A skill your agent uses when converting an accepted ACM CoNEXT paper's package into optional ACM reproducibility badges via the CoNEXT reproducibility committee — from the badge opt-in due before…. Conext Artifact Evaluation is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when converting an accepted ACM CoNEXT paper's package into optional ACM reproducibility badges via the CoNEXT reproducibility committee — from the badge opt-in due before submission, to the one-page artifact description due within a week of acceptance, to the Available / Functional / Reusable / Reproduced criteria and evaluator-proof reuse docs.
When should I use Conext Artifact Evaluation?
Conext Artifact Evaluation fits situations like: the one-page artifact description due within a week of acceptance; the Available / Functional / Reusable / Reproduced criteria and evaluator-proof reuse docs.
How do I install Conext Artifact Evaluation in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill conext-artifact-evaluation -a claude-code`. Or copy the skill folder (CoNEXT-Skills/skills/conext-artifact-evaluation in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/conext-artifact-evaluation in your project. Claude Code loads it when a task matches its description.
How do I install Conext Artifact Evaluation in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill conext-artifact-evaluation -a codex`. Or copy the skill folder (CoNEXT-Skills/skills/conext-artifact-evaluation in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/conext-artifact-evaluation in your project. Codex loads it when a task matches its description.
Can I use Conext 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 conext-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/conext-artifact-evaluation, .gemini/skills/conext-artifact-evaluation, .github/skills/conext-artifact-evaluation and .opencode/skills/conext-artifact-evaluation in your project.
What does Conext Artifact Evaluation need to run?
SKILL.md names no scripts, command-line tools or credentials: Conext Artifact Evaluation is instructions for the agent only.
Does Conext 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 Conext 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 Conext Artifact Evaluation use?
Conext 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 Conext Artifact Evaluation use?
About 1.2k tokens (SKILL.md is roughly 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 Conext Artifact Evaluation?
Skills that share tags, products or a category with Conext 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 Conext 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.