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
Imc Artifact Evaluation
by brycewang-stanford in brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when preparing an ACM IMC artifact for release, covering the artifact-availability declaration, post-acceptance availability shepherding, DOI-issuing dataset archives…
MITAuto-check passed
Install Imc Artifact Evaluation
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill imc-artifact-evaluation -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills imc-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/IMC-Skills/skills/imc-artifact-evaluation .claude/skills/imc-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 "imc-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/IMC-Skills/skills/imc-artifact-evaluation into .claude/skills/imc-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "imc-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/IMC-Skills/skills/imc-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 imc-artifact-evaluation -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills imc-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/IMC-Skills/skills/imc-artifact-evaluation .agents/skills/imc-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 "imc-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/IMC-Skills/skills/imc-artifact-evaluation into .agents/skills/imc-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "imc-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 imc-artifact-evaluation -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills imc-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/IMC-Skills/skills/imc-artifact-evaluation .cursor/skills/imc-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 "imc-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/IMC-Skills/skills/imc-artifact-evaluation into .cursor/skills/imc-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "imc-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 IMC-Skills/skills/imc-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 imc-artifact-evaluation -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills imc-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/IMC-Skills/skills/imc-artifact-evaluation .gemini/skills/imc-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 "imc-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/IMC-Skills/skills/imc-artifact-evaluation into .gemini/skills/imc-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "imc-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 imc-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 imc-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/IMC-Skills/skills/imc-artifact-evaluation .github/skills/imc-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 "imc-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/IMC-Skills/skills/imc-artifact-evaluation into .github/skills/imc-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "imc-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 imc-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 imc-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/IMC-Skills/skills/imc-artifact-evaluation .opencode/skills/imc-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 "imc-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/IMC-Skills/skills/imc-artifact-evaluation into .opencode/skills/imc-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "imc-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
imc-artifact-evaluation- GitHub stars
- 1.2k
- Token cost
- ~1.3k tokens
- SKILL.md length
- 527 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 ACM IMC artifact for release, covering the artifact-availability declaration, post-acceptance availability shepherding, DOI-issuing dataset archives…
- Preparing an ACM IMC artifact for release
- SKILL.md covers Two artifacts, two audiences, The availability declaration,…, What a strong measurement… and Reproducibility for a moving…, plus 4 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Covering the artifact-availability declaration
What it does
Imc Artifact Evaluation is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when preparing an ACM IMC artifact for release, covering the artifact-availability declaration, post-acceptance availability shepherding, DOI-issuing dataset archives, documenting measurement provenance and vantage points, Community Contribution Award eligibility, and the difference between the anonymized review artifact and the public release.
Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
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 ACM IMC artifact for release
- Covering the artifact-availability declaration
- Post-acceptance availability shepherding
- DOI-issuing dataset archives
Example prompts
- “/imc-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
Imc Artifact Evaluation loads about 1.3k tokens when it runs. Until then it costs about 94 tokens; SKILL.md has 527 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). 527 words, ~1,344 tokens.
Download SKILL.mdSave it as
.claude/skills/imc-artifact-evaluation/SKILL.md (or your agent's skills folder).- name
- imc-artifact-evaluation
- description
- Use when preparing an ACM IMC artifact for release, covering the artifact-availability declaration, post-acceptance availability shepherding, DOI-issuing dataset archives, documenting measurement provenance and vantage points, Community Contribution Award eligibility, and the difference between the anonymized review artifact and the public release.
IMC Artifact Evaluation
Use this for IMC's artifact and dataset story. Unlike venues with a separate badge-granting committee, IMC's mechanism is centered on an availability declaration at submission plus shepherding after acceptance to ensure the promised data, code, or platform actually becomes available. The venue-defining incentive is the Community Contribution Award, which exists to honor a released dataset, tool, or open platform. Whether IMC also awards formal ACM reproducibility badges in a given edition is 待核实 — confirm on the current call.
Two artifacts, two audiences
- Review artifact (at submission): anonymized for the reviewers — no owner strings, testbed or AS identifiers, probe-account IDs, cluster paths, or lab-domain links. It backs the paper's claims during double-blind review.
- Public release (after acceptance): de-anonymized, licensed, permanently archived. This is what the shepherd checks, what the camera-ready cites, and what the Community Contribution Award evaluates.
The availability declaration, delivered
At submission you declared full / partial / none. After acceptance, the shepherd holds you to it:
| Declared | What the shepherd expects | Common failure caught |
|---|---|---|
| Full | The dataset/tool/platform, publicly retrievable and documented | Link promised, never published; broken archive |
| Partial | The shareable subset + a stated reason for the rest | "Partial" used to avoid work; unclear what is shared |
| None | A specific, legitimate justification (proprietary/privacy/legal) | Vague "on request"; no reason given |
"Available on request" is not availability. If law or privacy blocks release, say precisely why and, where possible, release a derived/aggregated safe version.
What a strong measurement dataset release contains
[Data] the measured dataset itself (or a documented, privacy-safe derivative)
[Schema] a documented schema/dictionary: every field, unit, and its meaning
[Provenance] vantage points (locations, ASes, probe types), measurement dates and durations,
target lists with capture dates, tool versions, sampling and rate limits
[Method] the collection scripts/tooling and how to re-run the *method* (data will differ)
[Ethics] the privacy/anonymization applied to the release; disclosure status
[License] an explicit open license (e.g., CC-BY for data, OSI license for code)
[Archive] a DOI-issuing repository (Zenodo, figshare, Software Heritage) or a durable
community archive — not a personal homepageReproducibility for a moving Internet
Measurement data cannot be re-collected identically — the Internet changes. So the release must make the captured data and its provenance the reproducible core, and the method re-runnable to produce new comparable data. Ship the analysis scripts that turn the released data into the paper's figures; a number in the PDF that no script regenerates from the released data is the contradiction a shepherd (and a reader) will flag.
Show full SKILL.md (213 more words)Show less
Community Contribution Award eligibility
The award recognizes an outstanding dataset, source-code distribution, open platform, or service to the community. To be eligible, the data/code/tool must be publicly available and usable by the time of the camera-ready deadline — not "coming soon." Aim for it by making the release:
- Usable by a stranger: documented schema, a README, and a runnable example.
- Durable: a DOI and a maintenance/versioning note.
- Reusable: an open license and, for platforms, an access path others can actually use.
Worked vignette: releasing a longitudinal scan dataset
A paper contributes a two-year scan of a protocol's deployment. For a strong, award-eligible release: publish the per-scan records with a documented schema; include vantage-point and timing metadata for every scan; apply and document IP/host anonymization consistent with the Ethics section; ship the analysis notebooks that regenerate each figure from the released data; deposit in a DOI-issuing archive with a CC-BY license; and state honestly which raw captures cannot be shared for privacy reasons and what safe derivative replaces them.
Calibration
- Availability is judged at camera-ready time for the award and during shepherding for the accepted paper — plan the release before, not after, acceptance.
- Whether formal ACM badges are offered, and the exact shepherding process, vary by edition — confirm on the current call (待核实).
Output format
[Artifact role] anonymized review artifact / public release
[Declaration] full / partial / none (+ justification)
[Contents] <data/schema/provenance/method/ethics/license/archive>
[Reproducibility] scripts regenerate figures from released data? yes/no
[Award eligibility] public + usable by camera-ready? yes/no
[Fixes before release] <ordered list>© 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 IMC-Skills/skills/imc-artifact-evaluation of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Imc 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 |
|---|---|---|---|---|---|---|
| Imc Artifact Evaluation this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.3k | 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 | |
| Ase Artifact Evaluationbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.1k | Automated safety check: Pass | MIT | |
| Sigcomm Artifact Evaluationbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.1k | Automated safety check: Pass | MIT |
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Questions about Imc Artifact Evaluation
What does Imc Artifact Evaluation do?
A skill your agent uses when preparing an ACM IMC artifact for release, covering the artifact-availability declaration, post-acceptance availability shepherding, DOI-issuing dataset archives…. Imc Artifact Evaluation is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when preparing an ACM IMC artifact for release, covering the artifact-availability declaration, post-acceptance availability shepherding, DOI-issuing dataset archives, documenting measurement provenance and vantage points, Community Contribution Award eligibility, and the difference between the anonymized review artifact and the public release.
When should I use Imc Artifact Evaluation?
Imc Artifact Evaluation fits situations like: preparing an ACM IMC artifact for release; covering the artifact-availability declaration; post-acceptance availability shepherding; DOI-issuing dataset archives.
How do I install Imc Artifact Evaluation in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill imc-artifact-evaluation -a claude-code`. Or copy the skill folder (IMC-Skills/skills/imc-artifact-evaluation in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/imc-artifact-evaluation in your project. Claude Code loads it when a task matches its description.
How do I install Imc Artifact Evaluation in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill imc-artifact-evaluation -a codex`. Or copy the skill folder (IMC-Skills/skills/imc-artifact-evaluation in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/imc-artifact-evaluation in your project. Codex loads it when a task matches its description.
Can I use Imc 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 imc-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/imc-artifact-evaluation, .gemini/skills/imc-artifact-evaluation, .github/skills/imc-artifact-evaluation and .opencode/skills/imc-artifact-evaluation in your project.
What does Imc Artifact Evaluation need to run?
SKILL.md names no scripts, command-line tools or credentials: Imc Artifact Evaluation is instructions for the agent only.
Does Imc 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 Imc 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 Imc Artifact Evaluation use?
Imc 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 Imc Artifact Evaluation use?
About 1.3k 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 Imc Artifact Evaluation?
Skills that share tags, products or a category with Imc 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 Ase 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 Imc 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.