LobeHub Interactive Prototype
lobehub/lobehub
Builds single-file interactive HTML prototypes rendered with the real LobeHub UI components and written as production-style React, so they can later be split into files.
Agent skill
Chi Artifact Evaluation
by brycewang-stanford in brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when packaging the artifacts behind an ACM CHI paper — prototypes, study instruments, codebooks, datasets, analysis code — for anonymous review scrutiny and for…
MITAuto-check passed
Install Chi Artifact Evaluation
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill chi-artifact-evaluation -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills chi-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/CHI-Skills/skills/chi-artifact-evaluation .claude/skills/chi-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 "chi-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/CHI-Skills/skills/chi-artifact-evaluation into .claude/skills/chi-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chi-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/CHI-Skills/skills/chi-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 chi-artifact-evaluation -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills chi-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/CHI-Skills/skills/chi-artifact-evaluation .agents/skills/chi-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 "chi-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/CHI-Skills/skills/chi-artifact-evaluation into .agents/skills/chi-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chi-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 chi-artifact-evaluation -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills chi-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/CHI-Skills/skills/chi-artifact-evaluation .cursor/skills/chi-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 "chi-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/CHI-Skills/skills/chi-artifact-evaluation into .cursor/skills/chi-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chi-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 CHI-Skills/skills/chi-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 chi-artifact-evaluation -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills chi-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/CHI-Skills/skills/chi-artifact-evaluation .gemini/skills/chi-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 "chi-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/CHI-Skills/skills/chi-artifact-evaluation into .gemini/skills/chi-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chi-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 chi-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 chi-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/CHI-Skills/skills/chi-artifact-evaluation .github/skills/chi-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 "chi-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/CHI-Skills/skills/chi-artifact-evaluation into .github/skills/chi-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chi-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 chi-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 chi-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/CHI-Skills/skills/chi-artifact-evaluation .opencode/skills/chi-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 "chi-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/CHI-Skills/skills/chi-artifact-evaluation into .opencode/skills/chi-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chi-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
chi-artifact-evaluation- GitHub stars
- 1.2k
- Token cost
- ~1.4k tokens
- SKILL.md length
- 619 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when packaging the artifacts behind an ACM CHI paper — prototypes, study instruments, codebooks, datasets, analysis code — for anonymous review scrutiny and for…
- Works in 4 steps: Root README with a claims map: "Claim in… → One command per claim where code is… → A demo path that does not require your… → …
- Packaging the artifacts behind an ACM CHI paper — prototypes
- SKILL.md covers The CHI artifact inventory, Reviewer-facing packaging…, Post-acceptance release is a… and Honest holes beat cosmetic…, plus 2 more sections
- Calls bash
What it does
Chi Artifact Evaluation is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when packaging the artifacts behind an ACM CHI paper — prototypes, study instruments, codebooks, datasets, analysis code — for anonymous review scrutiny and for post-acceptance archival release, in a venue with no formal artifact-evaluation committee doing it for you.
Its SKILL.md is about 1.4k 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
- Packaging the artifacts behind an ACM CHI paper — prototypes
- Study instruments
- Analysis code — for anonymous review scrutiny and for post-acceptance archival release
- In a venue with no formal artifact-evaluation committee doing it for you
Example prompts
- “/chi-artifact-evaluation”
Workflow steps
4 steps, taken from the first numbered list in SKILL.md.
- Root README with a claims map: "Claim in §5.1 → analysis/h1_test.R →
- One command per claim where code is involved; vendor the environment
- A demo path that does not require your hardware. If the contribution is a
- Anonymity end to end: no .git, no metadata, no named accounts, anonymized
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
Shell commands in SKILL.md call:
bash
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
Chi Artifact Evaluation loads about 1.4k tokens when it runs. Until then it costs about 74 tokens; SKILL.md has 619 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). 619 words, ~1,353 tokens.
Download SKILL.mdSave it as
.claude/skills/chi-artifact-evaluation/SKILL.md (or your agent's skills folder).- name
- chi-artifact-evaluation
- description
- Use when packaging the artifacts behind an ACM CHI paper — prototypes, study instruments, codebooks, datasets, analysis code — for anonymous review scrutiny and for post-acceptance archival release, in a venue with no formal artifact-evaluation committee doing it for you.
CHI Artifact Evaluation
CHI's Papers track posted no separate artifact-evaluation committee or badge track for the cycles checked (2026, 2027; confirm each year — 待核实 as a standing item). That absence cuts both ways: nobody certifies your artifacts, and nobody but you ensures a skeptical reviewer can inspect them. At CHI the "artifact" is rarely just code — it is the prototype, the study instruments, the codebook, the dataset, and the video evidence of the system working. Package for two audiences with opposite needs: the anonymous reviewer with five minutes, and the future researcher with a real use for your materials.
The CHI artifact inventory
| Artifact | Reviewer's question | Archival value after acceptance |
|---|---|---|
| Prototype / system code | "Does the claimed interaction actually exist?" | Others extend or compare against it |
| Video figure of real use | "Does it work outside the authors' hands?" | Permanent DL evidence (chi-supplementary) |
| Study instruments (guides, questionnaires, tasks) | "Was the study what the paper says?" | Direct reuse in replications |
| Codebook / analysis audit trail | "Do the themes live in the data?" | Methods teaching material |
| Dataset (de-identified) | "Do the numbers re-derive?" | Secondary analysis |
| Design files (3D prints, schematics, figma) | "Could this be rebuilt?" | Fabrication replication |
| Prompts / model configs for AI conditions | "What system did participants face?" | The only record once the API moves |
Inventory first, then decide per artifact: reviewed now, released later, or honestly
withheld with a reason (chi-reproducibility has the data-sharing ladder).
Reviewer-facing packaging (anonymous, five minutes)
The review-phase archive rides the single September deadline with everything else. Design it so the first five minutes land:
- Root README with a claims map: "Claim in §5.1 →
analysis/h1_test.R→ Table 2." Three such lines are worth thirty pages of appendix. - One command per claim where code is involved; vendor the environment
(
requirements.txt,renv.lock) because a reviewer will not debug pip. - A demo path that does not require your hardware. If the contribution is a physical device, the video figure is the reviewable artifact; the archive adds schematics and firmware so the claim is auditable in principle.
- Anonymity end to end: no
.git, no metadata, no named accounts, anonymized platform views only, usernames scrubbed from notebook outputs and file paths.
# Cold-simulate the reviewer on the exact ZIP you will upload
rm -rf /tmp/ae && unzip -q supplement.zip -d /tmp/ae && cd /tmp/ae
cat README* | head -30 # does the claims map appear immediately?
grep -rEil 'author|university|(^|[^a-z])lab' --include='*.md' . | head
time bash run_minimal_demo.sh # the five-minute budget is literalShow full SKILL.md (261 more words)Show less
Post-acceptance release is a separate product
At the publication-ready stage (February for CHI 2027), rebuild the artifact set under real names for permanence, not for review:
- Deposit in a persistent home — the DL supplemental record, OSF, Zenodo, an institutional archive — with a DOI; a lab URL is a dead link in five years.
- License deliberately: code (MIT/Apache/GPL), data and instruments (CC BY or CC BY-NC), and record third-party constraints (stimuli copyrights, model terms of service for cached AI outputs).
- Re-check de-identification harder than at review: public release is forever, and participant re-identification harms real people. Where consent was narrow, release the instruments and codebook instead of the data — respected practice.
- Tag the released version to match the camera-ready ("as-published"), then develop onward in a separate branch; future readers need the paper's version, not HEAD.
Honest holes beat cosmetic completeness
A packaging note that says "the deployment used partner infrastructure we cannot ship; this archive contains the full client, the API contract, and a mock server reproducing the study conditions" earns more trust than a repo padded with dead code that hides the same gap. Reviewers at CHI read many partial artifacts; what they punish is discovering the gap themselves after the README implied completeness.
Timing inside the CHI year
- Build the claims-map README while writing §4–5 of the paper — it doubles as your
own claim-evidence audit (
chi-experiments). - Freeze the review archive at T−1 week; sweep it with
chi-submission's checks. - Diary the February release rebuild at acceptance time; rushed public releases in the TAPS window are where consent violations happen.
Output format
[Inventory] <artifact: reviewed / released-later / withheld+reason, per row>
[Claims map] present in README: yes/no · claims covered: <n>/<n>
[Five-minute test] cold demo ran in <time> / failed at <step>
[Anonymity] archive clean: yes/no — <channels checked>
[Release plan] home: <DL/OSF/Zenodo> · license: <code/data> · consent re-check owner: <name>© 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 CHI-Skills/skills/chi-artifact-evaluation of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Chi 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 |
|---|---|---|---|---|---|---|
| Chi Artifact Evaluation this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.4k | Automated safety check: Pass | MIT | |
| LobeHub Interactive Prototypelobehub/lobehub | 83k | — | ~1.6k | Automated safety check: Pass | Custom licence | |
| Arize Evaluatorgithub/awesome-copilot | 40k | 1 repos | ~8.1k | Automated safety check: Notes | MIT | |
| Ccs Artifact Evaluationbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~969 | Automated safety check: Pass | MIT | |
| Sigcomm Artifact Evaluationbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.1k | Automated safety check: Pass | MIT | |
| Sigmetrics Artifact Evaluationbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.4k | Automated safety check: Pass | MIT |
Similar skills
- Official
Arize Evaluator
github/awesome-copilot
Handles LLM-as-judge evaluation workflows on Arize including creating/updating evaluators, running evaluations on spans or experiments, managing tasks, trigger-run operations, column mapping, and…
Ccs Artifact Evaluation
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when packaging ACM CCS artifacts for the artifact-evaluation committee and the ACM badges — Artifacts Available, Artifacts Evaluated Functional, Artifacts Evaluated Reusable…
Sigcomm Artifact Evaluation
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when packaging an ACM SIGCOMM paper's code, traces, topologies, and configuration for the artifact-evaluation committee — choosing ACM badges (Artifacts Available, Evaluated…
Sigmetrics Artifact Evaluation
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when packaging an ACM SIGMETRICS artifact for the ACM Artifact Review and Badging scheme (Artifacts Available, Evaluated Functional and Reusable, Results Reproduced)…
Socc Artifact Evaluation
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when packaging an ACM SoCC artifact for the ACM Artifact Review and Badging scheme (Artifacts Available, Evaluated Functional and Reusable, Results Reproduced), covering what…
More from brycewang-stanford/Awesome-Journal-Skills
All 2,387 skills in this repoAaag Data Analysis
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when running and reporting the analysis for an Annals of the American Association of Geographers manuscript — spatial statistics and modeling, remote-sensing accuracy, or…
Aaag Literature Positioning
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when positioning an Annals of the American Association of Geographers manuscript in the literature — engaging geographic scholarship across the relevant area and the…
Aaag Rebuttal
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when responding to an Annals of the American Association of Geographers decision letter (major/minor revision) — building a point-by-point response to the subject editor and…
Aaag Research Design
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when defending the research design of an Annals of the American Association of Geographers manuscript — spatial/quantitative analysis and GIScience, remote-sensing and…
Aaag Review Process
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when you need to understand how the Annals of the American Association of Geographers evaluates a manuscript — double-anonymous review routed through a subject editor by…
Aaag Submission
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when running the final pre-submission preflight for the Annals of the American Association of Geographers via ScholarOne Manuscripts — area/article-type selection…
Questions about Chi Artifact Evaluation
What does Chi Artifact Evaluation do?
A skill your agent uses when packaging the artifacts behind an ACM CHI paper — prototypes, study instruments, codebooks, datasets, analysis code — for anonymous review scrutiny and for…. Chi Artifact Evaluation is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when packaging the artifacts behind an ACM CHI paper — prototypes, study instruments, codebooks, datasets, analysis code — for anonymous review scrutiny and for post-acceptance archival release, in a venue with no formal artifact-evaluation committee doing it for you.
When should I use Chi Artifact Evaluation?
Chi Artifact Evaluation fits situations like: packaging the artifacts behind an ACM CHI paper — prototypes; study instruments; analysis code — for anonymous review scrutiny and for post-acceptance archival release; in a venue with no formal artifact-evaluation committee doing it for you.
How do I install Chi Artifact Evaluation in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill chi-artifact-evaluation -a claude-code`. Or copy the skill folder (CHI-Skills/skills/chi-artifact-evaluation in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/chi-artifact-evaluation in your project. Claude Code loads it when a task matches its description.
How do I install Chi Artifact Evaluation in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill chi-artifact-evaluation -a codex`. Or copy the skill folder (CHI-Skills/skills/chi-artifact-evaluation in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/chi-artifact-evaluation in your project. Codex loads it when a task matches its description.
Can I use Chi 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 chi-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/chi-artifact-evaluation, .gemini/skills/chi-artifact-evaluation, .github/skills/chi-artifact-evaluation and .opencode/skills/chi-artifact-evaluation in your project.
What does Chi Artifact Evaluation need to run?
Going by SKILL.md and its folder, Chi Artifact Evaluation needs the command-line tools its instructions call (bash).
Does Chi 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 Chi 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 Chi Artifact Evaluation use?
Chi 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 Chi Artifact Evaluation use?
About 1.4k tokens (SKILL.md is roughly 5.4k 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 Chi Artifact Evaluation?
Skills that share tags, products or a category with Chi Artifact Evaluation: LobeHub Interactive Prototype (lobehub/lobehub, 83k stars), Arize Evaluator (github/awesome-copilot, 40k stars), Ccs Artifact Evaluation (brycewang-stanford/Awesome-Journal-Skills, 1.2k stars) and Sigcomm Artifact Evaluation (brycewang-stanford/Awesome-Journal-Skills, 1.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Chi 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.