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…
Agent skill
Uist Artifact Evaluation
by brycewang-stanford in brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when packaging the artifacts behind a UIST paper — code, toolkits, hardware design files, and datasets — first as anonymous review-time evidence that the system is real, then…
MITAuto-check passed
Install Uist Artifact Evaluation
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill uist-artifact-evaluation -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills uist-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/UIST-Skills/skills/uist-artifact-evaluation .claude/skills/uist-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 "uist-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/UIST-Skills/skills/uist-artifact-evaluation into .claude/skills/uist-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "uist-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/UIST-Skills/skills/uist-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 uist-artifact-evaluation -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills uist-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/UIST-Skills/skills/uist-artifact-evaluation .agents/skills/uist-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 "uist-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/UIST-Skills/skills/uist-artifact-evaluation into .agents/skills/uist-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "uist-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 uist-artifact-evaluation -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills uist-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/UIST-Skills/skills/uist-artifact-evaluation .cursor/skills/uist-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 "uist-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/UIST-Skills/skills/uist-artifact-evaluation into .cursor/skills/uist-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "uist-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 UIST-Skills/skills/uist-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 uist-artifact-evaluation -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills uist-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/UIST-Skills/skills/uist-artifact-evaluation .gemini/skills/uist-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 "uist-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/UIST-Skills/skills/uist-artifact-evaluation into .gemini/skills/uist-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "uist-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 uist-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 uist-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/UIST-Skills/skills/uist-artifact-evaluation .github/skills/uist-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 "uist-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/UIST-Skills/skills/uist-artifact-evaluation into .github/skills/uist-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "uist-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 uist-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 uist-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/UIST-Skills/skills/uist-artifact-evaluation .opencode/skills/uist-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 "uist-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/UIST-Skills/skills/uist-artifact-evaluation into .opencode/skills/uist-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "uist-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
uist-artifact-evaluation- GitHub stars
- 1.2k
- Token cost
- ~1.6k tokens
- SKILL.md length
- 699 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 a UIST paper — code, toolkits, hardware design files, and datasets — first as anonymous review-time evidence that the system is real, then…
- Works in 5 steps: De-anonymize deliberately — publish to… → Cut a release tag matching the… → Choose licenses by artifact class: code… → …
- Packaging the artifacts behind a UIST paper — code
- SKILL.md covers What counts as the artifact,…, Review-time packaging: the…, Release-time packaging:… and What the informal evaluators…, plus 3 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Uist Artifact Evaluation is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when packaging the artifacts behind a UIST paper — code, toolkits, hardware design files, and datasets — first as anonymous review-time evidence that the system is real, then as a public release engineered for reuse, in a venue with no formal badge committee doing the checking for you.
Its SKILL.md is about 1.6k 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 a UIST paper — code
- Hardware design files
- Datasets — first as anonymous review-time evidence that the system is real
- Then as a public release engineered for reuse
Example prompts
- “/uist-artifact-evaluation”
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- De-anonymize deliberately — publish to the real org, restore attribution,
- Cut a release tag matching the camera-ready ("as-published") so later
- Choose licenses by artifact class: code (e.g. MIT/Apache-2.0), hardware
- Archive beyond the repo: deposit the tagged release with a DOI service so
- State the support posture honestly in the README — "research prototype,
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
Uist Artifact Evaluation loads about 1.6k tokens when it runs. Until then it costs about 79 tokens; SKILL.md has 699 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). 699 words, ~1,582 tokens.
Download SKILL.mdSave it as
.claude/skills/uist-artifact-evaluation/SKILL.md (or your agent's skills folder).- name
- uist-artifact-evaluation
- description
- Use when packaging the artifacts behind a UIST paper — code, toolkits, hardware design files, and datasets — first as anonymous review-time evidence that the system is real, then as a public release engineered for reuse, in a venue with no formal badge committee doing the checking for you.
UIST Artifact Evaluation
UIST has no artifact-evaluation committee or badge track (none was found for the 2026 cycle — 待核实 each year); the CFP-level instrument of proof is the video figure. That absence raises rather than lowers the packaging bar: your artifacts are judged twice, informally — at review time as evidence the system exists as claimed, and after publication as infrastructure other builders adopt. Nobody will certify either; both simply succeed or fail.
What counts as the artifact, by paper type
| Paper type | Review-time artifact | Reuse-time artifact |
|---|---|---|
| Interaction technique | Reference implementation + demo scene | Portable library with the technique isolated |
| Toolkit / authoring system | Runnable toolkit + the example apps from the paper | Documented API, tutorials, package registry entry |
| Hardware / fabrication | Design files, firmware, BOM, assembly photos | Fab-ready files + sourcing notes + calibration guide |
| Sensing / recognition pipeline | Trained models + capture data + eval harness | Dataset with collection protocol + retraining scripts |
| Human-AI / LLM system | Prompts, orchestration code, pinned model IDs, logged transcripts | Same, plus cost and drift notes |
Review-time packaging: the five-minute skeptic
A reviewer gives your supplement five minutes, anonymously, on a machine you don't control. Optimize for that reader:
- One
READMEat the archive root: what this is, which paper section each directory backs, and one command (or one video) per claim. - Prefer a recorded run alongside the code for anything with hardware, drivers, or GPU dependencies — reviewers cannot rebuild your rig, so show the harness producing the paper's numbers.
- Pin everything (lockfiles, container image digests, model checkpoints); "latest" is a broken artifact by review week.
- Anonymize as strictly as the PDF: repository history, notebook authorship cells,
hardcoded home paths, calibration files named after lab members (see
uist-submissionfor the sweep).
supplement.zip
├── README.md # claim → artifact map; 5-minute quickstart
├── technique/ # core implementation, pinned deps
├── hardware/ # schematics, PCB, STL/STEP, BOM.csv, firmware/
├── eval/ # harness + raw logs behind Tables 1-2
│ └── rerun.sh # regenerates the paper's numbers from logs
├── media/ # per-claim capture clips (beyond the video figure)
└── LICENSES.md # third-party components and their termsRelease-time packaging: engineering for strangers
At camera-ready (see uist-camera-ready), the audience flips from three skeptics
to an open-ended stream of builders:
- De-anonymize deliberately — publish to the real org, restore attribution, add the paper citation and BibTeX to the README.
- Cut a release tag matching the camera-ready ("as-published") so later development never orphans the paper's claims.
- Choose licenses by artifact class: code (e.g. MIT/Apache-2.0), hardware designs (e.g. CERN-OHL), data (e.g. CC-BY) — one archive often needs all three, and institutional tech-transfer rules for hardware are worth checking early.
- Archive beyond the repo: deposit the tagged release with a DOI service so the URL in the proceedings outlives your hosting choices.
- State the support posture honestly in the README — "research prototype, issues welcome, no maintenance promised" is respectable; silence is not.
Show full SKILL.md (290 more words)Show less
What the informal evaluators open first
Order the package for actual reading behavior:
- README, thirty seconds. If the claim → artifact map is not visible without scrolling, the evaluation is over.
- The media directory, two minutes. Clips of the harness producing the paper's numbers get watched; they are the highest-credibility artifact per byte, especially for hardware.
- One quickstart command, two minutes. Whatever you name in the README as "run this" will be run in a fresh environment; test it in a container or a colleague's clean machine, not your dev box.
- Source spot-checks. Reviewers grep for the mechanism the paper claims is novel; if the "self-calibrating controller" is a 30-line stub, the paper's credibility inverts. Never ship scaffolding that contradicts the prose.
Toolkit papers: adoption is the long evaluation
For toolkit and authoring-system contributions, the release is the deferred evaluation, and small engineering choices compound:
- Publish to the ecosystem's registry (pip/npm/crates/Arduino library manager) — installability is adoption's first filter.
- Ship the paper's example applications as runnable starters; they are the tutorials people actually read.
- Keep the API surface documented at the level of the paper's abstractions, so citations of the toolkit describe your concepts in your vocabulary.
- Track downstream uses; a "built with X" list is both maintenance motivation and the evidence base for the retrospective the venue's decade-scale memory eventually invites.
Hardware honesty
Physical artifacts cannot be uploaded, so their evidence standard is
reconstruction: exact part numbers with sources, tolerances that matter, assembly
sequence photos, firmware flashing instructions, and the calibration procedure with
expected readings. A paper whose device only the authors can build has published a
demo, not a contribution — reviewers from fabrication-heavy labs apply exactly that
test (see uist-reproducibility for the replication ledger).
Output format
[Artifact class] technique / toolkit / hardware / pipeline / hybrid
[Review package] five-minute test passes? claim→artifact map complete?
[Anonymity] archive-level sweep clean?
[Release plan] tag · licenses (code/hardware/data) · DOI deposit · support posture
[Gap list] <artifacts named in the paper but absent from the package>© 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 UIST-Skills/skills/uist-artifact-evaluation of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Uist 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 |
|---|---|---|---|---|---|---|
| Uist Artifact Evaluation this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.6k | Automated safety check: Pass | MIT | |
| Arize Evaluatorgithub/awesome-copilot | 40k | 1 repos | ~8.1k | Automated safety check: Notes | MIT | |
| Artifacts Buildernexu-io/open-design | 100k | — | ~347 | Automated safety check: Pass | Apache-2.0 | |
| Ccs Artifact Evaluationbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~969 | Automated safety check: Pass | MIT | |
| Mobisys Artifact Evaluationbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1k | Automated safety check: Pass | MIT | |
| Fast Artifact Evaluationbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.6k | Automated safety check: Pass | MIT |
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Questions about Uist Artifact Evaluation
What does Uist Artifact Evaluation do?
A skill your agent uses when packaging the artifacts behind a UIST paper — code, toolkits, hardware design files, and datasets — first as anonymous review-time evidence that the system is real, then…. Uist Artifact Evaluation is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when packaging the artifacts behind a UIST paper — code, toolkits, hardware design files, and datasets — first as anonymous review-time evidence that the system is real, then as a public release engineered for reuse, in a venue with no formal badge committee doing the checking for you.
When should I use Uist Artifact Evaluation?
Uist Artifact Evaluation fits situations like: packaging the artifacts behind a UIST paper — code; hardware design files; datasets — first as anonymous review-time evidence that the system is real; then as a public release engineered for reuse.
How do I install Uist Artifact Evaluation in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill uist-artifact-evaluation -a claude-code`. Or copy the skill folder (UIST-Skills/skills/uist-artifact-evaluation in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/uist-artifact-evaluation in your project. Claude Code loads it when a task matches its description.
How do I install Uist Artifact Evaluation in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill uist-artifact-evaluation -a codex`. Or copy the skill folder (UIST-Skills/skills/uist-artifact-evaluation in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/uist-artifact-evaluation in your project. Codex loads it when a task matches its description.
Can I use Uist 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 uist-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/uist-artifact-evaluation, .gemini/skills/uist-artifact-evaluation, .github/skills/uist-artifact-evaluation and .opencode/skills/uist-artifact-evaluation in your project.
What does Uist Artifact Evaluation need to run?
SKILL.md names no scripts, command-line tools or credentials: Uist Artifact Evaluation is instructions for the agent only.
Does Uist 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 Uist 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 Uist Artifact Evaluation use?
Uist 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 Uist Artifact Evaluation use?
About 1.6k tokens (SKILL.md is roughly 6.3k 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 Uist Artifact Evaluation?
Skills that share tags, products or a category with Uist Artifact Evaluation: Arize Evaluator (github/awesome-copilot, 40k stars), Artifacts Builder (nexu-io/open-design, 100k stars), Ccs Artifact Evaluation (brycewang-stanford/Awesome-Journal-Skills, 1.2k stars) and Mobisys 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 Uist 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.