Peer Review
K-Dense-AI/claude-scientific-writer
Prepare evidence-bounded, constructive peer-review drafts and structured manuscript assessments.
A skill your agent uses when strengthening EDBT reproducibility for a database-systems paper, covering a runnable artifact, pinned environments and workloads, dataset and query-log provenance…
Install Edbt Reproducibility
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill edbt-reproducibility -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills edbt-reproducibility --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/EDBT-Skills/skills/edbt-reproducibility .claude/skills/edbt-reproducibility && 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 "edbt-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/EDBT-Skills/skills/edbt-reproducibility into .claude/skills/edbt-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "edbt-reproducibility", 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/EDBT-Skills/skills/edbt-reproducibilityType 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 edbt-reproducibility -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills edbt-reproducibility --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/EDBT-Skills/skills/edbt-reproducibility .agents/skills/edbt-reproducibility && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "edbt-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/EDBT-Skills/skills/edbt-reproducibility into .agents/skills/edbt-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "edbt-reproducibility", 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 edbt-reproducibility -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills edbt-reproducibility --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/EDBT-Skills/skills/edbt-reproducibility .cursor/skills/edbt-reproducibility && 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 "edbt-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/EDBT-Skills/skills/edbt-reproducibility into .cursor/skills/edbt-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "edbt-reproducibility", 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 EDBT-Skills/skills/edbt-reproducibility--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 edbt-reproducibility -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills edbt-reproducibility --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/EDBT-Skills/skills/edbt-reproducibility .gemini/skills/edbt-reproducibility && 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 "edbt-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/EDBT-Skills/skills/edbt-reproducibility into .gemini/skills/edbt-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "edbt-reproducibility", 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 edbt-reproducibilityInstalls 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 edbt-reproducibility -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/EDBT-Skills/skills/edbt-reproducibility .github/skills/edbt-reproducibility && 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 "edbt-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/EDBT-Skills/skills/edbt-reproducibility into .github/skills/edbt-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "edbt-reproducibility", 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 edbt-reproducibility -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 edbt-reproducibility --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/EDBT-Skills/skills/edbt-reproducibility .opencode/skills/edbt-reproducibility && 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 "edbt-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/EDBT-Skills/skills/edbt-reproducibility into .opencode/skills/edbt-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "edbt-reproducibility", 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
edbt-reproducibility- GitHub stars
- 1.2k
- Token cost
- ~1.3k tokens
- SKILL.md length
- 545 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when strengthening EDBT reproducibility for a database-systems paper, covering a runnable artifact, pinned environments and workloads, dataset and query-log provenance…
- Strengthening EDBT reproducibility for a database-systems paper
- SKILL.md covers Evidence map, Availability statement audit, Provenance pinning… and Degrees of reproducibility…, plus 3 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Covering a runnable artifact
What it does
Edbt Reproducibility is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when strengthening EDBT reproducibility for a database-systems paper, covering a runnable artifact, pinned environments and workloads, dataset and query-log provenance, claim-to-evidence mapping, honest degrees of reproducibility, and consistency between the paper and the package for the open-access OpenProceedings record.
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.
It sits in Research & Science, covering Reproducible research. 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
- Strengthening EDBT reproducibility for a database-systems paper
- Covering a runnable artifact
- Pinned environments and workloads
- Dataset and query-log provenance
Example prompts
- “/edbt-reproducibility”
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
Edbt Reproducibility loads about 1.3k tokens when it runs. Until then it costs about 87 tokens; SKILL.md has 545 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). 545 words, ~1,310 tokens.
Download SKILL.mdSave it as
.claude/skills/edbt-reproducibility/SKILL.md (or your agent's skills folder).- name
- edbt-reproducibility
- description
- Use when strengthening EDBT reproducibility for a database-systems paper, covering a runnable artifact, pinned environments and workloads, dataset and query-log provenance, claim-to-evidence mapping, honest degrees of reproducibility, and consistency between the paper and the package for the open-access OpenProceedings record.
EDBT Reproducibility
Use this before submission and again before camera-ready. EDBT's community has a reproducibility-forward culture, and the published record is open access on OpenProceedings — so an inspectable, re-runnable package raises a paper's standing and, for an Experiments & Analysis paper, is the contribution. The goal is that a competent reader could rebuild your measurements and reach your conclusions.
Evidence map
- Map each claim, mechanism, and reported number to a verifiable location — a paper section, a table generated from a logged run, or a script in the artifact.
- For a mechanism, give enough of the algorithm, data structures, parameters, and system integration that a reader could reimplement or rebuild it.
- For an evaluation, report workloads and their derivation, dataset versions and sources, the measurement harness, metrics, and the analysis scripts.
- Keep the availability statement truthful and specific: what is shared, the workloads and data, the hardware assumptions, and — if something cannot be shared — exactly why.
- Keep the paper and the artifact consistent: a number in the PDF that no script produces is the contradiction reviewers read as carelessness.
Availability statement audit
| Claim in the paper | Weak availability answer | EDBT-ready answer |
|---|---|---|
| "We evaluate on workload W" | "Data available on request" | Archived workload/query-log derivation + the extracted data or a documented access path |
| "Our operator lowers latency" | "Code will be released" | Runnable system/prototype with a build, a demo run, and the config |
| "We compare N systems" (E&A) | Numbers with no harness | The full comparison harness that regenerates every table |
| "On a 128-node cluster" | Nothing about environment | Hardware/cluster spec, engine build/commit, and how to size a smaller reproduction |
"Available on request" is treated as not available; convert every such line into a concrete package or an explicit, justified exception (licensing, confidentiality).
Provenance pinning (database-systems flavor)
[Data] pin dataset versions and sources; archive the derived workload/query-log, not just a
description; document filtering and sampling
[System] record the engine/prototype build or commit; ship a build recipe or container
[Environment] state hardware, memory, network, and node counts; note what a smaller reproduction changes
[Harness] the measurement scripts that produce each table/figure, with fixed configuration
[Randomness] log seeds for any stochastic step; say what is and is not deterministicShow full SKILL.md (255 more words)Show less
Degrees of reproducibility (state the one you achieved)
- Turnkey: one documented command (or container) regenerates each table/figure from a run or from logged results.
- Scripted: scripts exist but require documented manual steps, a specific cluster, or external data access.
- Descriptive: prose detailed enough that a competent reader could rebuild the pipeline.
For EDBT, aim turnkey for anything a reviewer might re-run quickly (a demo run on a small workload, a plot from logged results); large-cluster or licensed-data experiments may stay scripted with the environment and access clearly documented. Stating the achieved level honestly beats promising turnkey behavior that fails on a clean machine.
Vignette: a distributed-operator study
Consider an operator evaluated on a cluster. Its reproducibility spine: a container or build recipe for the engine plus the operator; the workload-derivation scripts with pinned dataset versions; the measurement harness that runs the operator and the tuned baseline across node counts; the logged raw results; and the analysis notebooks that turn them into the paper's tables — plus one honest sentence about the parts (the full 128-node run, a licensed dataset) that a reader reproduces at reduced scale and why.
Consistency and camera-ready pass
- Before submission: every reported number traces to the artifact; the availability statement matches reality; if the cycle is double-blind, the artifact carries no identity strings.
- Before camera-ready: deposit the package in a DOI-issuing archive (Zenodo, figshare, Software
Heritage) with an OSI-approved license, replace any anonymized links with the permanent ones, and
make the statement consistent with the open-access OpenProceedings record
(
edbt-artifact-evaluation,edbt-camera-ready).
Output format
[Claim inventory] <claim -> evidence location>
[Availability] concrete / vague / missing
[Provenance gaps] <dataset versions / engine build / environment / seeds>
[Reproducibility level] turnkey / scripted / descriptive, stated honestly
[Paper fixes] <must appear in the PDF>
[Artifact fixes] <additions before upload>© 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 EDBT-Skills/skills/edbt-reproducibility of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Edbt Reproducibility 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 |
|---|---|---|---|---|---|---|
| Edbt Reproducibility this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.3k | Automated safety check: Pass | MIT | |
| Peer ReviewK-Dense-AI/claude-scientific-writer | 2.4k | 2 repos | ~3.1k | Automated safety check: Notes | MIT | |
| CHARLS Paper Reproduction Guidexjtulyc/MedgeClaw | 617 | 1 repos | ~1.8k | Automated safety check: Pass | None | |
| Compute Environment Setupaipoch/open-science | 5.5k | — | ~2.6k | Automated safety check: Pass | Apache-2.0 | |
| Figure Styleaipoch/open-science | 5.5k | — | ~5.1k | Automated safety check: Pass | Apache-2.0 | |
| Add Bactopia Toolbactopia/bactopia | 522 | — | ~4.1k | Automated safety check: Pass | MIT |
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CHARLS Paper Reproduction Guide
xjtulyc/MedgeClaw
Guides an agent through reproducing papers built on the CHARLS health and retirement survey, from variable mapping to cognition, depression and isolation scores.
Compute Environment Setup
aipoch/open-science
Prepares setup instructions and a named activation file for a user-managed software environment on an Open-Science SSH or Slurm compute host.
Figure Style
aipoch/open-science
Publication-grade correctness and legibility rules for final-deliverable scientific figures, not exploratory plots.
Add Bactopia Tool
bactopia/bactopia
Scaffold a complete Bactopia Tool across all three tiers -- module, subworkflow, and workflow entry point under workflows/bactopia-tools/.
Modeling Code and Result Contracts
yushui2022/MathModel-Skill
Generates result-evidence contracts, tables and runnable q1 to q3 modeling code scaffolds for a math modeling paper from a model route, a data plan and cleaned data.
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Categories
Questions about Edbt Reproducibility
What does Edbt Reproducibility do?
A skill your agent uses when strengthening EDBT reproducibility for a database-systems paper, covering a runnable artifact, pinned environments and workloads, dataset and query-log provenance…. Edbt Reproducibility is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when strengthening EDBT reproducibility for a database-systems paper, covering a runnable artifact, pinned environments and workloads, dataset and query-log provenance, claim-to-evidence mapping, honest degrees of reproducibility, and consistency between the paper and the package for the open-access OpenProceedings record.
When should I use Edbt Reproducibility?
Edbt Reproducibility fits situations like: strengthening EDBT reproducibility for a database-systems paper; covering a runnable artifact; pinned environments and workloads; dataset and query-log provenance.
How do I install Edbt Reproducibility in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill edbt-reproducibility -a claude-code`. Or copy the skill folder (EDBT-Skills/skills/edbt-reproducibility in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/edbt-reproducibility in your project. Claude Code loads it when a task matches its description.
How do I install Edbt Reproducibility in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill edbt-reproducibility -a codex`. Or copy the skill folder (EDBT-Skills/skills/edbt-reproducibility in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/edbt-reproducibility in your project. Codex loads it when a task matches its description.
Can I use Edbt Reproducibility 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 edbt-reproducibility -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/edbt-reproducibility, .gemini/skills/edbt-reproducibility, .github/skills/edbt-reproducibility and .opencode/skills/edbt-reproducibility in your project.
What does Edbt Reproducibility need to run?
SKILL.md names no scripts, command-line tools or credentials: Edbt Reproducibility is instructions for the agent only.
Does Edbt Reproducibility 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 Edbt Reproducibility 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 Edbt Reproducibility use?
Edbt Reproducibility 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 Edbt Reproducibility use?
About 1.3k tokens (SKILL.md is roughly 5.2k 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 Edbt Reproducibility?
Skills that share tags, products or a category with Edbt Reproducibility: Peer Review (K-Dense-AI/claude-scientific-writer, 2.4k stars), CHARLS Paper Reproduction Guide (xjtulyc/MedgeClaw, 617 stars), Compute Environment Setup (aipoch/open-science, 5.5k stars) and Figure Style (aipoch/open-science, 5.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Edbt Reproducibility?
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.