Bio Fragment Analysis
GPTomics/bioSkills
Extracts cfDNA fragmentomics features (DELFI genome-wide short/long ratios, WPS nucleosome positioning, Griffin GC-corrected accessibility profiles, end-motifs/MDS, OCF) for cancer detection and…
Agent skill
Vldb Artifact Evaluation
by brycewang-stanford in brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when preparing a PVLDB artifact for the pVLDB Reproducibility Evaluation or the ACM availability badge, covering the mandatory participation rule for EA&B papers, the four…
Install Vldb Artifact Evaluation
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill vldb-artifact-evaluation -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills vldb-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/VLDB-Skills/skills/vldb-artifact-evaluation .claude/skills/vldb-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 "vldb-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/VLDB-Skills/skills/vldb-artifact-evaluation into .claude/skills/vldb-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vldb-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/VLDB-Skills/skills/vldb-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 vldb-artifact-evaluation -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills vldb-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/VLDB-Skills/skills/vldb-artifact-evaluation .agents/skills/vldb-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 "vldb-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/VLDB-Skills/skills/vldb-artifact-evaluation into .agents/skills/vldb-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vldb-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 vldb-artifact-evaluation -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills vldb-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/VLDB-Skills/skills/vldb-artifact-evaluation .cursor/skills/vldb-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 "vldb-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/VLDB-Skills/skills/vldb-artifact-evaluation into .cursor/skills/vldb-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vldb-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 VLDB-Skills/skills/vldb-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 vldb-artifact-evaluation -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills vldb-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/VLDB-Skills/skills/vldb-artifact-evaluation .gemini/skills/vldb-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 "vldb-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/VLDB-Skills/skills/vldb-artifact-evaluation into .gemini/skills/vldb-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vldb-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 vldb-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 vldb-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/VLDB-Skills/skills/vldb-artifact-evaluation .github/skills/vldb-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 "vldb-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/VLDB-Skills/skills/vldb-artifact-evaluation into .github/skills/vldb-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vldb-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 vldb-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 vldb-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/VLDB-Skills/skills/vldb-artifact-evaluation .opencode/skills/vldb-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 "vldb-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/VLDB-Skills/skills/vldb-artifact-evaluation into .opencode/skills/vldb-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vldb-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
vldb-artifact-evaluation- GitHub stars
- 1.2k
- Token cost
- ~1k tokens
- SKILL.md length
- 409 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when preparing a PVLDB artifact for the pVLDB Reproducibility Evaluation or the ACM availability badge, covering the mandatory participation rule for EA&B papers, the four…
- Works in 4 steps: Prototype — source code, build… → Input data — the datasets themselves, or… → Workload — the exact queries, client… → …
- Preparing a PVLDB artifact for the pVLDB Reproducibility Evaluation
- SKILL.md covers Who must play, who should, The four surfaces evaluators…, Design for a stranger's machine and Minimal package skeleton, plus 2 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Vldb Artifact Evaluation is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when preparing a PVLDB artifact for the pVLDB Reproducibility Evaluation or the ACM availability badge, covering the mandatory participation rule for EA&B papers, the four artifact surfaces evaluators rebuild, packaging for a rerun by strangers, and positioning for the Best Reproducible Paper Award at VLDB.
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.
It sits in Research & Science, covering Reproducible research and Positioning and messaging. 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 a PVLDB artifact for the pVLDB Reproducibility Evaluation
- The ACM availability badge
- Covering the mandatory participation rule for EA&B papers
- The four artifact surfaces evaluators rebuild
Example prompts
- “/vldb-artifact-evaluation”
Workflow steps
4 steps, taken from the first numbered list in SKILL.md.
- Prototype — source code, build environment, configuration. A container
- Input data — the datasets themselves, or deterministic generators with
- Workload — the exact queries, client configuration, thread counts, and
- Analysis — scripts that transform raw measurements into each numbered
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
Vldb Artifact Evaluation loads about 1k tokens when it runs. Until then it costs about 84 tokens; SKILL.md has 409 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). 409 words, ~1,020 tokens.
Download SKILL.mdSave it as
.claude/skills/vldb-artifact-evaluation/SKILL.md (or your agent's skills folder).- name
- vldb-artifact-evaluation
- description
- Use when preparing a PVLDB artifact for the pVLDB Reproducibility Evaluation or the ACM availability badge, covering the mandatory participation rule for EA&B papers, the four artifact surfaces evaluators rebuild, packaging for a rerun by strangers, and positioning for the Best Reproducible Paper Award at VLDB.
VLDB Artifact Evaluation
Use this once a PVLDB paper is accepted (or when an EA&B submission is being planned, since participation is not optional there). The pVLDB Reproducibility Evaluation — run jointly with SIGMOD's effort since the 2018 push — has committee members rebuild your experiment from your package. Two distinct prizes exist: the ACM availability badge for sharing, and the Reproducible outcome (with a Best Reproducible Paper Award) for surviving an independent rerun.
Who must play, who should
| Situation | Obligation |
|---|---|
| EA&B paper | Required: release all data and software, submit to evaluation |
| Regular research paper | Optional but strongly encouraged; badge on offer |
| Industrial paper with proprietary core | Availability of what can be shared; document the rest |
| Vision paper | Rarely applicable |
The four surfaces evaluators rebuild
The committee's published expectations decompose an artifact into four layers. Package each one explicitly:
- Prototype — source code, build environment, configuration. A container image plus the Dockerfile that produced it is the community's default.
- Input data — the datasets themselves, or deterministic generators with pinned seeds and a size knob, plus download scripts for public corpora.
- Workload — the exact queries, client configuration, thread counts, and run durations behind every experiment, not a representative sample.
- Analysis — scripts that transform raw measurements into each numbered figure and table in the PDF. This layer is the one authors most often skip and evaluators most often need.
Show full SKILL.md (181 more words)Show less
Design for a stranger's machine
- Assume the evaluator has no access to your cluster. Provide a scaled-down mode that demonstrates every claim's shape on one commodity machine, and document how the full-scale numbers were obtained.
- Pin everything: base images, package versions, competitor-system commits. "Latest" is where reruns go to die.
- Emit expected outputs and tolerances. A rerun that produces a plot is only useful if the evaluator can tell whether the plot is right — state which qualitative relationships must hold even when absolute numbers shift with hardware.
- Time-box honestly: state wall-clock cost per experiment so the committee can schedule, and mark the one experiment that best represents the paper if resources run short.
Minimal package skeleton
artifact/
README.md # claims map: figure/table -> command -> expected shape
Dockerfile # or image reference + build recipe
data/get_data.sh # fetch or generate, seeded
workloads/ # exact configs per experiment
run_one.sh <exp> # single experiment, scaled-down default
run_full.sh # full-scale protocol, hardware stated
plots/make_all.sh # raw results -> paper figuresAward positioning
Winning packages read like engineering products: one command to a first
result, claims mapped to figures, failures anticipated. If the evaluation
report will say "worked on the first try," you are in contention; if it says
"worked after correspondence with the authors," you got the badge and lost the
award. Current-cycle evaluation logistics and criteria wording: 待核实 on
vldb.org/pvldb/reproducibility before packaging.
Output format
[Track] EA&B-mandatory / voluntary / availability-only
[Surface coverage] prototype / data / workload / analysis — gaps listed
[Stranger test] scaled-down mode exists / cluster-only (risk)
[Pinning] images, versions, competitor commits — unpinned items
[First-command experience] <what happens>
[Fixes before submission to the committee] <ordered>© 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 VLDB-Skills/skills/vldb-artifact-evaluation of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Vldb 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 |
|---|---|---|---|---|---|---|
| Vldb Artifact Evaluation this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1k | Automated safety check: Pass | MIT | |
| Bio Fragment AnalysisGPTomics/bioSkills | 1.2k | 1 repos | ~4.3k | Automated safety check: Pass | MIT | |
| Bio Atac Seq Nucleosome PositioningGPTomics/bioSkills | 1.2k | 2 repos | ~4.9k | Automated safety check: Pass | MIT | |
| Bio Atac Seq Nucleosome PositioningFreedomIntelligence/OpenClaw-Medical-Skills | 3.1k | — | ~2.3k | Automated safety check: Pass | None | |
| Gec Literature Positioningfranklee16/academic-research-skills | 223 | 1 repos | ~855 | Automated safety check: Pass | None | |
| Jape Literature Positioningfranklee16/academic-research-skills | 223 | 1 repos | ~572 | Automated safety check: Pass | None |
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Gec Literature Positioning
franklee16/academic-research-skills
A skill your agent uses when positioning a Global Environmental Change (GEC) manuscript against the relevant literatures.
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Related
Categories
Questions about Vldb Artifact Evaluation
What does Vldb Artifact Evaluation do?
A skill your agent uses when preparing a PVLDB artifact for the pVLDB Reproducibility Evaluation or the ACM availability badge, covering the mandatory participation rule for EA&B papers, the four…. Vldb Artifact Evaluation is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when preparing a PVLDB artifact for the pVLDB Reproducibility Evaluation or the ACM availability badge, covering the mandatory participation rule for EA&B papers, the four artifact surfaces evaluators rebuild, packaging for a rerun by strangers, and positioning for the Best Reproducible Paper Award at VLDB.
When should I use Vldb Artifact Evaluation?
Vldb Artifact Evaluation fits situations like: preparing a PVLDB artifact for the pVLDB Reproducibility Evaluation; the ACM availability badge; covering the mandatory participation rule for EA&B papers; the four artifact surfaces evaluators rebuild.
How do I install Vldb Artifact Evaluation in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill vldb-artifact-evaluation -a claude-code`. Or copy the skill folder (VLDB-Skills/skills/vldb-artifact-evaluation in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/vldb-artifact-evaluation in your project. Claude Code loads it when a task matches its description.
How do I install Vldb Artifact Evaluation in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill vldb-artifact-evaluation -a codex`. Or copy the skill folder (VLDB-Skills/skills/vldb-artifact-evaluation in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/vldb-artifact-evaluation in your project. Codex loads it when a task matches its description.
Can I use Vldb 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 vldb-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/vldb-artifact-evaluation, .gemini/skills/vldb-artifact-evaluation, .github/skills/vldb-artifact-evaluation and .opencode/skills/vldb-artifact-evaluation in your project.
What does Vldb Artifact Evaluation need to run?
SKILL.md names no scripts, command-line tools or credentials: Vldb Artifact Evaluation is instructions for the agent only.
Does Vldb 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 Vldb 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 Vldb Artifact Evaluation use?
Vldb 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 Vldb 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 Vldb Artifact Evaluation?
Skills that share tags, products or a category with Vldb Artifact Evaluation: Bio Fragment Analysis (GPTomics/bioSkills, 1.2k stars), Bio Atac Seq Nucleosome Positioning (GPTomics/bioSkills, 1.2k stars), Bio Atac Seq Nucleosome Positioning (FreedomIntelligence/OpenClaw-Medical-Skills, 3.1k stars) and Gec Literature Positioning (franklee16/academic-research-skills, 223 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Vldb 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.