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
Eccv Artifact Evaluation
by brycewang-stanford in brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when packaging code, models, and data around an ECCV paper — the anonymous review-time archive under the trailing supplement deadline, the do-not-cite-your-own-repo rule, and…
MITAuto-check passed
Install Eccv Artifact Evaluation
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill eccv-artifact-evaluation -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills eccv-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/ECCV-Skills/skills/eccv-artifact-evaluation .claude/skills/eccv-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 "eccv-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ECCV-Skills/skills/eccv-artifact-evaluation into .claude/skills/eccv-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eccv-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/ECCV-Skills/skills/eccv-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 eccv-artifact-evaluation -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills eccv-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/ECCV-Skills/skills/eccv-artifact-evaluation .agents/skills/eccv-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 "eccv-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ECCV-Skills/skills/eccv-artifact-evaluation into .agents/skills/eccv-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eccv-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 eccv-artifact-evaluation -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills eccv-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/ECCV-Skills/skills/eccv-artifact-evaluation .cursor/skills/eccv-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 "eccv-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ECCV-Skills/skills/eccv-artifact-evaluation into .cursor/skills/eccv-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eccv-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 ECCV-Skills/skills/eccv-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 eccv-artifact-evaluation -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills eccv-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/ECCV-Skills/skills/eccv-artifact-evaluation .gemini/skills/eccv-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 "eccv-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ECCV-Skills/skills/eccv-artifact-evaluation into .gemini/skills/eccv-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eccv-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 eccv-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 eccv-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/ECCV-Skills/skills/eccv-artifact-evaluation .github/skills/eccv-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 "eccv-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ECCV-Skills/skills/eccv-artifact-evaluation into .github/skills/eccv-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eccv-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 eccv-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 eccv-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/ECCV-Skills/skills/eccv-artifact-evaluation .opencode/skills/eccv-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 "eccv-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ECCV-Skills/skills/eccv-artifact-evaluation into .opencode/skills/eccv-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eccv-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
eccv-artifact-evaluation- GitHub stars
- 1.2k
- Token cost
- ~1k tokens
- SKILL.md length
- 455 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when packaging code, models, and data around an ECCV paper — the anonymous review-time archive under the trailing supplement deadline, the do-not-cite-your-own-repo rule, and…
- Works in 2 steps: sealed archive (review time) → the ten-week release runway
- Data around an ECCV paper — the anonymous review-time archive under the trailing supplement deadline
- SKILL.md covers Phase 1 — sealed archive…, What vision reviewers actually…, Phase 2 — the ten-week release… and Dataset and benchmark releases, plus 1 more section
- Calls python, git and pip
What it does
Eccv Artifact Evaluation is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when packaging code, models, and data around an ECCV paper — the anonymous review-time archive under the trailing supplement deadline, the do-not-cite-your-own-repo rule, and the June-to-September post-acceptance runway for a public release aligned with the ECVA and Springer copies of the paper.
Its SKILL.md is about 1k 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
- Data around an ECCV paper — the anonymous review-time archive under the trailing supplement deadline
- The do-not-cite-your-own-repo rule
- The June-to-September post-acceptance runway for a public release aligned with the ECVA and Springer copies of the paper
Example prompts
- “/eccv-artifact-evaluation”
Requirements
- Python 3
Workflow steps
2 steps, taken from the step headings in SKILL.md.
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:
pythongitpip
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use git and pip, which can reach the network depending on how they are called.
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
Eccv Artifact Evaluation loads about 1k tokens when it runs. Until then it costs about 81 tokens; SKILL.md has 455 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). 455 words, ~1,037 tokens.
Download SKILL.mdSave it as
.claude/skills/eccv-artifact-evaluation/SKILL.md (or your agent's skills folder).- name
- eccv-artifact-evaluation
- description
- Use when packaging code, models, and data around an ECCV paper — the anonymous review-time archive under the trailing supplement deadline, the do-not-cite-your-own-repo rule, and the June-to-September post-acceptance runway for a public release aligned with the ECVA and Springer copies of the paper.
ECCV Artifact Evaluation
Use this for artifact strategy at ECCV, which has no badge-granting artifact track: artifacts live in two phases with opposite rules. Before decisions, code is a sealed, anonymous supplement; after the June decision, it becomes a public release with a ten-week runway before the September conference makes the paper visible to the whole field.
Phase 1 — sealed archive (review time)
- Upload with the supplement by the trailing deadline (March 12 in 2026, one week after the paper).
- The submission text must not link to the authors' public repository even if it already exists — ECCV 2026 policy treated that as an anonymity break, while arXiv posting itself was fine.
- Assume one reviewer opens the archive for ten minutes. Optimize for that reader: a README that maps each main-table row to a command, pinned dependencies, and one tiny demo input that runs on CPU.
- Scrub the usual vision-stack leaks: wandb entity names in configs, dataset paths containing lab or cluster names, git history, notebook metadata, license headers with author names, model cards naming the group.
What vision reviewers actually probe
| Artifact | Probe | Failure they report |
|---|---|---|
| Inference code + checkpoint | Run the demo image | Output does not resemble the paper's qualitative figures |
| Training configs | Diff against the paper's Sec. 4 numbers | Config hyperparameters contradict the text |
| Evaluation script | Check the metric implementation | Nonstandard IoU/FID variant silently inflates scores |
| Data tooling | Check preprocessing + splits | Test-set contamination via cropping or dedup choices |
The metric-implementation row is the highest-yield check to run on yourself: vision metrics have venue-standard reference implementations, and a rebuttal cannot repair a nonstandard one discovered in review.
Show full SKILL.md (188 more words)Show less
Phase 2 — the ten-week release runway
The 2026 calendar gave accepted authors June 17 (decisions) to roughly mid-August (ECVA/Springer open-access copies appear ~4 weeks pre-conference) to ship the release the paper's readers will find:
- Week 1–2: de-anonymize the sealed archive; make the repo the camera-ready URL points to, not a placeholder.
- Week 3–5: release checkpoints with hashes, licences chosen deliberately (the Springer copyright covers the paper, not your code or weights — pick code and model licences yourself).
- Week 6–8: project page linking arXiv, the upcoming ECVA page, data cards, and a results table that matches the camera-ready exactly.
- Week 9–10: freeze; conference week issues should be answered from a stable main branch, because Malmö attendees will clone it during the poster session.
Dataset and benchmark releases
If the contribution is a dataset or benchmark, plan hosting that outlives the conference cycle: institutional or community storage rather than a personal drive link, versioned splits, a datasheet, and licence terms compatible with the source imagery. A benchmark whose test server or download link dies before the next even-year ECCV is a citation dead end.
# minimal release self-check before announcing
git clone <public-url> fresh && cd fresh
pip install -r requirements.txt # pinned, resolvable
python demo.py --input assets/demo.jpg # CPU-runnable smoke test
python eval.py --split val --ckpt <hash> # reproduces one paper rowOutput format
[Phase] sealed-supplement / release-runway / post-conference
[Anonymity scrub] <leaks found in configs, paths, metadata, history>
[Reviewer-probe risks] <metric impl / config-text mismatch / demo gap>
[Release plan] <repo, checkpoints, licences, hosting, freeze date>
[Paper-artifact consistency] <camera-ready row -> reproducing command>© 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 ECCV-Skills/skills/eccv-artifact-evaluation of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Eccv 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 |
|---|---|---|---|---|---|---|
| Eccv Artifact Evaluation this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1k | 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 Eccv Artifact Evaluation
What does Eccv Artifact Evaluation do?
A skill your agent uses when packaging code, models, and data around an ECCV paper — the anonymous review-time archive under the trailing supplement deadline, the do-not-cite-your-own-repo rule, and…. Eccv Artifact Evaluation is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when packaging code, models, and data around an ECCV paper — the anonymous review-time archive under the trailing supplement deadline, the do-not-cite-your-own-repo rule, and the June-to-September post-acceptance runway for a public release aligned with the ECVA and Springer copies of the paper.
When should I use Eccv Artifact Evaluation?
Eccv Artifact Evaluation fits situations like: data around an ECCV paper — the anonymous review-time archive under the trailing supplement deadline; the do-not-cite-your-own-repo rule; the June-to-September post-acceptance runway for a public release aligned with the ECVA and Springer copies of the paper.
How do I install Eccv Artifact Evaluation in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill eccv-artifact-evaluation -a claude-code`. Or copy the skill folder (ECCV-Skills/skills/eccv-artifact-evaluation in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/eccv-artifact-evaluation in your project. Claude Code loads it when a task matches its description.
How do I install Eccv Artifact Evaluation in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill eccv-artifact-evaluation -a codex`. Or copy the skill folder (ECCV-Skills/skills/eccv-artifact-evaluation in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/eccv-artifact-evaluation in your project. Codex loads it when a task matches its description.
Can I use Eccv 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 eccv-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/eccv-artifact-evaluation, .gemini/skills/eccv-artifact-evaluation, .github/skills/eccv-artifact-evaluation and .opencode/skills/eccv-artifact-evaluation in your project.
What does Eccv Artifact Evaluation need to run?
Going by SKILL.md and its folder, Eccv Artifact Evaluation needs the command-line tools its instructions call (python, git and pip). Our summary lists: Python 3.
Does Eccv Artifact Evaluation access the network?
SKILL.md contains no URLs. Its commands use git and pip, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Is Eccv 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 Eccv Artifact Evaluation use?
Eccv 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 Eccv Artifact Evaluation use?
About 1k tokens (SKILL.md is roughly 4.1k 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 Eccv Artifact Evaluation?
Skills that share tags, products or a category with Eccv 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 Eccv 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.