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
Icse Artifact Evaluation
by brycewang-stanford in brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when preparing an artifact for the ICSE Artifact Evaluation track after paper acceptance, covering the ACM badge system (Available, Reusable, Results Reproduced/Replicated)…
MITAuto-check passed
Install Icse Artifact Evaluation
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill icse-artifact-evaluation -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills icse-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/ICSE-Skills/skills/icse-artifact-evaluation .claude/skills/icse-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 "icse-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICSE-Skills/skills/icse-artifact-evaluation into .claude/skills/icse-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "icse-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/ICSE-Skills/skills/icse-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 icse-artifact-evaluation -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills icse-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/ICSE-Skills/skills/icse-artifact-evaluation .agents/skills/icse-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 "icse-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICSE-Skills/skills/icse-artifact-evaluation into .agents/skills/icse-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "icse-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 icse-artifact-evaluation -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills icse-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/ICSE-Skills/skills/icse-artifact-evaluation .cursor/skills/icse-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 "icse-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICSE-Skills/skills/icse-artifact-evaluation into .cursor/skills/icse-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "icse-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 ICSE-Skills/skills/icse-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 icse-artifact-evaluation -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills icse-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/ICSE-Skills/skills/icse-artifact-evaluation .gemini/skills/icse-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 "icse-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICSE-Skills/skills/icse-artifact-evaluation into .gemini/skills/icse-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "icse-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 icse-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 icse-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/ICSE-Skills/skills/icse-artifact-evaluation .github/skills/icse-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 "icse-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICSE-Skills/skills/icse-artifact-evaluation into .github/skills/icse-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "icse-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 icse-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 icse-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/ICSE-Skills/skills/icse-artifact-evaluation .opencode/skills/icse-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 "icse-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICSE-Skills/skills/icse-artifact-evaluation into .opencode/skills/icse-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "icse-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
icse-artifact-evaluation- GitHub stars
- 1.2k
- Token cost
- ~1.6k tokens
- SKILL.md length
- 739 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when preparing an artifact for the ICSE Artifact Evaluation track after paper acceptance, covering the ACM badge system (Available, Reusable, Results Reproduced/Replicated)…
- Works in 5 steps: De-anonymize deliberately — restore… → Archive with a DOI — deposit in a… → License openly — the ICSE AE guidance… → …
- Preparing an artifact for the ICSE Artifact Evaluation track after paper acceptance
- SKILL.md covers The badge system, as ICSE runs…, Timeline anchor, From review package to badge… and The evaluator-proof README, plus 4 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Icse Artifact Evaluation is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when preparing an artifact for the ICSE Artifact Evaluation track after paper acceptance, covering the ACM badge system (Available, Reusable, Results Reproduced/Replicated), evaluator-proof packaging, archival requirements, open licensing, and the January-window timeline anchored to recent cycles.
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
- Preparing an artifact for the ICSE Artifact Evaluation track after paper acceptance
- Covering the ACM badge system (Available
- Results Reproduced/Replicated)
- Evaluator-proof packaging
Example prompts
- “/icse-artifact-evaluation”
Requirements
- Docker
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- De-anonymize deliberately — restore names, affiliations, the real
- Archive with a DOI — deposit in a DOI-issuing archive (Zenodo-class,
- License openly — the ICSE AE guidance encourages open-source licenses
- Write for the evaluator's clock — a stranger, on their own machine,
- Document for reuse, not just replay — the Reusable bar is repurposing
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 (its code samples are markdown).
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
Icse Artifact Evaluation loads about 1.6k tokens when it runs. Until then it costs about 82 tokens; SKILL.md has 739 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). 739 words, ~1,615 tokens.
Download SKILL.mdSave it as
.claude/skills/icse-artifact-evaluation/SKILL.md (or your agent's skills folder).- name
- icse-artifact-evaluation
- description
- Use when preparing an artifact for the ICSE Artifact Evaluation track after paper acceptance, covering the ACM badge system (Available, Reusable, Results Reproduced/Replicated), evaluator-proof packaging, archival requirements, open licensing, and the January-window timeline anchored to recent cycles.
ICSE Artifact Evaluation
ICSE's artifact track is a post-acceptance, opt-in evaluation: once the
paper is in, you submit the artifact to a separate committee that awards ACM-
standard badges printed on the published paper. It is the formal payoff of the
verifiability work done at review time — if icse-reproducibility was
followed, this skill is mostly packaging and paperwork.
The badge system, as ICSE runs it
Verified against the ICSE 2026 artifact-evaluation track (read 2026-07-08; ICSE follows the ACM artifact review and badging standard):
| Badge | Who applies | What evaluators check |
|---|---|---|
| Artifacts Available | Authors of papers accepted to Research, SEIP, NIER, SEIS, Doctoral Symposium, Demonstrations | Artifact is permanently archived in a public, DOI-issuing repository — not a personal GitHub, which can be deleted or rewritten |
| Artifacts Reusable (Evaluated) | Same tracks | Quality "significantly exceeds minimal functionality": careful documentation, structure that supports reuse and repurposing by others |
| Results Reproduced / Replicated | Authors of prior published SE work | Independent obtainment of the paper's results, per the ACM definitions |
Two structural notes. First, Available is about archival, Reusable about quality — a beautifully engineered artifact on a transient URL fails the first, a DOI'd tarball nobody can run fails the second; aim for both. Second, the Reproduced/Replicated badges are a lane for already-published work, which is also how your artifact gets used: build it expecting a stranger to attempt exactly that next year.
Timeline anchor
ICSE 2026 ran artifact registration on January 8 and submission on January 15, 2026 — weeks after final paper decisions (December 18 in the 2027-cycle calendar) and months before the conference. The 2027 dates were unposted at check time (待核实 at the ICSE 2027 artifact-evaluation page). Planning consequence: the artifact deadline lands in the first working days of January, so the package must be effectively done before the holidays.
From review package to badge submission
The anonymized review-time package needs five upgrades:
- De-anonymize deliberately — restore names, affiliations, the real license holder, and the citation file; re-point links from the anonymizing host to the permanent home.
- Archive with a DOI — deposit in a DOI-issuing archive (Zenodo-class,
institutional repository); record the DOI in the paper's availability
statement before the camera-ready freezes (
icse-camera-ready). - License openly — the ICSE AE guidance encourages open-source licenses (MIT, Apache-2.0, GPL) for code and open-data licenses (CC-BY, CC0) for data; a package with no license is legally unusable and evaluators notice.
- Write for the evaluator's clock — a stranger, on their own machine, with a review load. Provide a container or exact environment recipe, a smoke test in minutes, and the full runs' costs stated honestly up front.
- Document for reuse, not just replay — the Reusable bar is repurposing: how to run on new subjects, extend the benchmark, or swap the model — one section each in the README.
Show full SKILL.md (281 more words)Show less
The evaluator-proof README
# Artifact for "<paper title>" (ICSE 20XX, paper #NNN)
## Claims supported
Table 3 (RQ1), Fig. 5 (RQ2) fully reproducible below.
Table 6 requires 40 GPU-hours; cached outputs + verification script provided.
## Kick the tires (10 min, laptop)
docker load < artifact.tar && ./smoke_test.sh # expected output shown below
## Full reproduction
./reproduce_all.sh # ~6 h CPU; per-table scripts listed in scripts/
## Reusing beyond the paper
- New subject program: docs/add_subject.md
- Different model backend: docs/swap_model.md
## Requirements / License / CitationThe claims-supported section is the trust anchor: state plainly which paper results the artifact does and does not cover, and give a cached-output verification path for anything expensive. Evaluators reward honesty about coverage and punish discovering gaps themselves.
Scoping what the artifact claims
Badge submissions fail more often from over-claiming than under-building. Declare a claims scope narrower than the paper if that is the truth: "the artifact reproduces RQ1 and RQ2; RQ3's industrial dataset is excluded under NDA, and we include the analysis scripts plus synthetic sample data so the pipeline itself is checkable." Evaluators can only award what they can verify, and a scoped-honest artifact that fully delivers its scope reads better than an everything-artifact with two broken paths. Match the scope statement to the paper's Data Availability section — a mismatch between the two is the first thing a careful evaluator diffs.
Failure modes that cost badges
- Bit-rot between acceptance and January: dependency drift breaks the build; freeze a container image the week of acceptance.
- Undeclared network/credential needs: an artifact that must call a paid API mid-evaluation stalls; cache responses and make live calls optional.
- Doc-code mismatch after camera-ready edits changed table numbers — re-run the claims map against the final paper, not the submission.
- Repository-instead-of-archive: linking GitHub
mainwhere the badge requires an immutable DOI deposit.
Reverify each cycle
Track list, badge set, deadlines, and submission form are set by each year's AE chairs; the ACM badging vocabulary is the stable layer. Confirm the 2027 call before promising badge scope to coauthors — and note the badge is opt-in: absence of one on a published ICSE paper signals nothing about its authors, only about their January.
Output format
[Badges targeted] Available / Reusable / (Reproduced-Replicated for prior work)
[Archival] DOI minted? license file? citation file?
[Evaluator path] smoke-test minutes; full-run cost; cached-output coverage
[Reuse docs] new-subject and extension guides present?
[Deadline plan] frozen container by <date>; submission by the January window© 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 ICSE-Skills/skills/icse-artifact-evaluation of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Icse 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 |
|---|---|---|---|---|---|---|
| Icse 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 | |
| LLM Evaluationdavila7/claude-code-templates | 33k | 12 repos | ~3.5k | Automated safety check: Pass | MIT | |
| Web Artifacts Builderanthropics/skills | 180k | 40 repos | ~769 | Automated safety check: Pass | Apache-2.0 | |
| Agent Evaluationsickn33/agentic-awesome-skills | 47k | 1 repos | ~2k | Automated safety check: Pass | MIT |
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Questions about Icse Artifact Evaluation
What does Icse Artifact Evaluation do?
A skill your agent uses when preparing an artifact for the ICSE Artifact Evaluation track after paper acceptance, covering the ACM badge system (Available, Reusable, Results Reproduced/Replicated)…. Icse Artifact Evaluation is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when preparing an artifact for the ICSE Artifact Evaluation track after paper acceptance, covering the ACM badge system (Available, Reusable, Results Reproduced/Replicated), evaluator-proof packaging, archival requirements, open licensing, and the January-window timeline anchored to recent cycles.
When should I use Icse Artifact Evaluation?
Icse Artifact Evaluation fits situations like: preparing an artifact for the ICSE Artifact Evaluation track after paper acceptance; covering the ACM badge system (Available; results Reproduced/Replicated); evaluator-proof packaging.
How do I install Icse Artifact Evaluation in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill icse-artifact-evaluation -a claude-code`. Or copy the skill folder (ICSE-Skills/skills/icse-artifact-evaluation in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/icse-artifact-evaluation in your project. Claude Code loads it when a task matches its description.
How do I install Icse Artifact Evaluation in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill icse-artifact-evaluation -a codex`. Or copy the skill folder (ICSE-Skills/skills/icse-artifact-evaluation in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/icse-artifact-evaluation in your project. Codex loads it when a task matches its description.
Can I use Icse 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 icse-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/icse-artifact-evaluation, .gemini/skills/icse-artifact-evaluation, .github/skills/icse-artifact-evaluation and .opencode/skills/icse-artifact-evaluation in your project.
What does Icse Artifact Evaluation need to run?
SKILL.md names no scripts, command-line tools or credentials: Icse Artifact Evaluation is instructions for the agent only. Our summary lists: Docker.
Does Icse 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 Icse 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 Icse Artifact Evaluation use?
Icse 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 Icse Artifact Evaluation use?
About 1.6k tokens (SKILL.md is roughly 6.5k 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 Icse Artifact Evaluation?
Skills that share tags, products or a category with Icse Artifact Evaluation: Arize Evaluator (github/awesome-copilot, 40k stars), Artifacts Builder (nexu-io/open-design, 100k stars), LLM Evaluation (davila7/claude-code-templates, 33k stars) and Web Artifacts Builder (anthropics/skills, 180k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Icse 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.