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 hardening an OOPSLA paper's empirical claims to the SIGPLAN Empirical Evaluation Guidelines — managed-runtime measurement discipline, warmup and variance reporting…
Install Oopsla Reproducibility
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill oopsla-reproducibility -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills oopsla-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/OOPSLA-Skills/skills/oopsla-reproducibility .claude/skills/oopsla-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 "oopsla-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/OOPSLA-Skills/skills/oopsla-reproducibility into .claude/skills/oopsla-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "oopsla-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/OOPSLA-Skills/skills/oopsla-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 oopsla-reproducibility -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills oopsla-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/OOPSLA-Skills/skills/oopsla-reproducibility .agents/skills/oopsla-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 "oopsla-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/OOPSLA-Skills/skills/oopsla-reproducibility into .agents/skills/oopsla-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "oopsla-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 oopsla-reproducibility -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills oopsla-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/OOPSLA-Skills/skills/oopsla-reproducibility .cursor/skills/oopsla-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 "oopsla-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/OOPSLA-Skills/skills/oopsla-reproducibility into .cursor/skills/oopsla-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "oopsla-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 OOPSLA-Skills/skills/oopsla-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 oopsla-reproducibility -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills oopsla-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/OOPSLA-Skills/skills/oopsla-reproducibility .gemini/skills/oopsla-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 "oopsla-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/OOPSLA-Skills/skills/oopsla-reproducibility into .gemini/skills/oopsla-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "oopsla-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 oopsla-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 oopsla-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/OOPSLA-Skills/skills/oopsla-reproducibility .github/skills/oopsla-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 "oopsla-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/OOPSLA-Skills/skills/oopsla-reproducibility into .github/skills/oopsla-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "oopsla-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 oopsla-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 oopsla-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/OOPSLA-Skills/skills/oopsla-reproducibility .opencode/skills/oopsla-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 "oopsla-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/OOPSLA-Skills/skills/oopsla-reproducibility into .opencode/skills/oopsla-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "oopsla-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
oopsla-reproducibility- GitHub stars
- 1.2k
- Token cost
- ~1.1k tokens
- SKILL.md length
- 404 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when hardening an OOPSLA paper's empirical claims to the SIGPLAN Empirical Evaluation Guidelines — managed-runtime measurement discipline, warmup and variance reporting…
- Works in 3 steps: Re-derive every headline number from the… → Delete one machine from the picture:… → Hand a labmate the guidelines' four…
- Hardening an OOPSLA papers empirical claims to the SIGPLAN Empirical Evaluation Guidelines — managed-runtime measurement discipline
- SKILL.md covers The four guideline pillars,…, Managed-runtime and…, Reproducibility ledger and Statement discipline, plus 2 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Oopsla Reproducibility is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when hardening an OOPSLA paper's empirical claims to the SIGPLAN Empirical Evaluation Guidelines — managed-runtime measurement discipline, warmup and variance reporting, corpus and benchmark provenance, environment pinning, and a Data-Availability Statement that the eventual artifact can actually honor.
Its SKILL.md is about 1.1k 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. 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
- Hardening an OOPSLA papers empirical claims to the SIGPLAN Empirical Evaluation Guidelines — managed-runtime measurement discipline
- Warmup and variance reporting
- Corpus and benchmark provenance
- Environment pinning
Example prompts
- “/oopsla-reproducibility”
Workflow steps
3 steps, taken from the first numbered list in SKILL.md.
- Re-derive every headline number from the ledger with one command.
- Delete one machine from the picture: does any claim silently depend on
- Hand a labmate the guidelines' four pillars and the PDF; each pillar they
What it can do on your machine
Read from SKILL.md and the folder at commit 932eb23. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are yaml).
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
Oopsla Reproducibility loads about 1.1k tokens when it runs. Until then it costs about 83 tokens; SKILL.md has 404 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). 404 words, ~1,078 tokens.
Download SKILL.mdSave it as
.claude/skills/oopsla-reproducibility/SKILL.md (or your agent's skills folder).- name
- oopsla-reproducibility
- description
- Use when hardening an OOPSLA paper's empirical claims to the SIGPLAN Empirical Evaluation Guidelines — managed-runtime measurement discipline, warmup and variance reporting, corpus and benchmark provenance, environment pinning, and a Data-Availability Statement that the eventual artifact can actually honor.
OOPSLA Reproducibility
OOPSLA carries a particular historical burden here: the venue itself
published the papers showing that sloppy runtime measurement produces wrong
conclusions — Georges, Buytaert & Eeckhout's statistical-rigor paper (OOPSLA
2007) and the DaCapo suite's methodology argument (OOPSLA 2006); see
resources/exemplars/library.md. Reviewers steeped in that lineage apply the
SIGPLAN Empirical Evaluation Guidelines
(sigplan.org/Resources/EmpiricalEvaluation/) as a working checklist, and
the two-round model gives them a Minor/Major Revision lever to demand rigor
rather than merely complain about it. Reproducibility work done before
Round N is cheaper than the revision it preempts.
The four guideline pillars, operationalized
| Pillar | Reviewer question | Concrete obligation in the paper |
|---|---|---|
| Clear claims | What exactly is asserted, on what workloads, on what hardware? | Claims scoped with population, platform, and configuration |
| Suitable comparison | Is the baseline the strongest sensible one, correctly configured? | Baseline versions, flags, and tuning documented |
| Principled benchmarks | Why these programs/corpora and not cherry-picked ones? | Selection rule stated; exclusions listed with reasons |
| Adequate data analysis | Do the numbers separate signal from noise? | Repetitions, warmup policy, dispersion, and summary statistic all named |
Managed-runtime and PL-specific traps
- JIT warmup: steady-state and startup are different claims; measure and label both or pick one explicitly.
- Nondeterministic compilation: JIT tiering, GC scheduling, and ASLR mean run-to-run variance is structural — report distributions, not best-of.
- Geometric vs arithmetic means across benchmarks: choose deliberately and say why; ratios of means and means of ratios diverge.
- Corpus studies (the Meyerovich–Rabkin lane): repository selection bias, fork/duplicate contamination, and time-of-scrape all belong in the paper, since the corpus is the instrument.
- Mechanized proofs: state the proof assistant version, axioms/assumed lemmas, and which theorems are checked vs paper-only.
Show full SKILL.md (137 more words)Show less
Reproducibility ledger
Keep one machine-readable ledger from the first experiment; it becomes the artifact's spine and the Data-Availability Statement's evidence.
experiment: table3-throughput
runtime: OpenJDK 21.0.2 (Temurin), -Xmx16g, JIT default
hardware: 2x Xeon 6338, 256 GiB, SMT off, governor=performance
benchmarks: dacapo-23.11-chopin subset (selection rule: R1)
protocol: 30 invocations x 10 iterations, discard warmup by CUSUM
stats: geomean ratio + 95% bootstrap CI, per-benchmark violin in appendix
seed_policy: fixed seeds logged; randomized order per invocation
data: raw CSV -> artifact path /results/table3/Statement discipline
The Data-Availability Statement (required before the references —
oopsla-submission) is a promissory note the artifact must later redeem
under badge review (oopsla-artifact-evaluation). Write it from the ledger:
name what is included, what is excluded and why (license, privacy, scale),
and on what hardware results were produced. A statement that overpromises is
worse than a modest one — evaluators check.
Pre-round self-audit
- Re-derive every headline number from the ledger with one command.
- Delete one machine from the picture: does any claim silently depend on unstated hardware?
- Hand a labmate the guidelines' four pillars and the PDF; each pillar they cannot check off in the text is a revision demand waiting to be written.
Output format
[Pillar audit] claims/comparison/benchmarks/analysis: pass|gap each
[Runtime traps] <warmup, variance, mean-choice, corpus, proofs — issues found>
[Ledger] complete / missing fields: <list>
[Statement] redeemable as written: yes / overpromises: <items>
[Revision exposure] what a reviewer could demand in Round N+1© 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 OOPSLA-Skills/skills/oopsla-reproducibility of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Oopsla 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 |
|---|---|---|---|---|---|---|
| Oopsla Reproducibility this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.1k | 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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Related
Categories
Questions about Oopsla Reproducibility
What does Oopsla Reproducibility do?
A skill your agent uses when hardening an OOPSLA paper's empirical claims to the SIGPLAN Empirical Evaluation Guidelines — managed-runtime measurement discipline, warmup and variance reporting…. Oopsla Reproducibility is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when hardening an OOPSLA paper's empirical claims to the SIGPLAN Empirical Evaluation Guidelines — managed-runtime measurement discipline, warmup and variance reporting, corpus and benchmark provenance, environment pinning, and a Data-Availability Statement that the eventual artifact can actually honor.
When should I use Oopsla Reproducibility?
Oopsla Reproducibility fits situations like: hardening an OOPSLA papers empirical claims to the SIGPLAN Empirical Evaluation Guidelines — managed-runtime measurement discipline; warmup and variance reporting; corpus and benchmark provenance; environment pinning.
How do I install Oopsla Reproducibility in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill oopsla-reproducibility -a claude-code`. Or copy the skill folder (OOPSLA-Skills/skills/oopsla-reproducibility in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/oopsla-reproducibility in your project. Claude Code loads it when a task matches its description.
How do I install Oopsla Reproducibility in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill oopsla-reproducibility -a codex`. Or copy the skill folder (OOPSLA-Skills/skills/oopsla-reproducibility in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/oopsla-reproducibility in your project. Codex loads it when a task matches its description.
Can I use Oopsla 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 oopsla-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/oopsla-reproducibility, .gemini/skills/oopsla-reproducibility, .github/skills/oopsla-reproducibility and .opencode/skills/oopsla-reproducibility in your project.
What does Oopsla Reproducibility need to run?
SKILL.md names no scripts, command-line tools or credentials: Oopsla Reproducibility is instructions for the agent only.
Does Oopsla 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 Oopsla 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 Oopsla Reproducibility use?
Oopsla 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 Oopsla Reproducibility use?
About 1.1k tokens (SKILL.md is roughly 4.3k 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 Oopsla Reproducibility?
Skills that share tags, products or a category with Oopsla 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 Oopsla Reproducibility?
brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,228 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.