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 making a PPoPP paper's parallel-performance results reproducible, covering the hardware and topology description reviewers re-run, thread pinning and NUMA control, seeds…
Install Ppopp Reproducibility
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ppopp-reproducibility -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills ppopp-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/PPoPP-Skills/skills/ppopp-reproducibility .claude/skills/ppopp-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 "ppopp-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/PPoPP-Skills/skills/ppopp-reproducibility into .claude/skills/ppopp-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ppopp-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/PPoPP-Skills/skills/ppopp-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 ppopp-reproducibility -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills ppopp-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/PPoPP-Skills/skills/ppopp-reproducibility .agents/skills/ppopp-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 "ppopp-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/PPoPP-Skills/skills/ppopp-reproducibility into .agents/skills/ppopp-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ppopp-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 ppopp-reproducibility -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills ppopp-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/PPoPP-Skills/skills/ppopp-reproducibility .cursor/skills/ppopp-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 "ppopp-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/PPoPP-Skills/skills/ppopp-reproducibility into .cursor/skills/ppopp-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ppopp-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 PPoPP-Skills/skills/ppopp-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 ppopp-reproducibility -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills ppopp-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/PPoPP-Skills/skills/ppopp-reproducibility .gemini/skills/ppopp-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 "ppopp-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/PPoPP-Skills/skills/ppopp-reproducibility into .gemini/skills/ppopp-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ppopp-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 ppopp-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 ppopp-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/PPoPP-Skills/skills/ppopp-reproducibility .github/skills/ppopp-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 "ppopp-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/PPoPP-Skills/skills/ppopp-reproducibility into .github/skills/ppopp-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ppopp-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 ppopp-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 ppopp-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/PPoPP-Skills/skills/ppopp-reproducibility .opencode/skills/ppopp-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 "ppopp-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/PPoPP-Skills/skills/ppopp-reproducibility into .opencode/skills/ppopp-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ppopp-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
ppopp-reproducibility- GitHub stars
- 1.2k
- Token cost
- ~1.1k tokens
- SKILL.md length
- 394 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when making a PPoPP paper's parallel-performance results reproducible, covering the hardware and topology description reviewers re-run, thread pinning and NUMA control, seeds…
- Making a PPoPP papers parallel-performance results reproducible
- SKILL.md covers The environment description…, Control the sources of…, Reproduce the trend, not just… and Data and workloads, plus 3 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Covering the hardware and topology description reviewers re-run
What it does
Ppopp Reproducibility is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when making a PPoPP paper's parallel-performance results reproducible, covering the hardware and topology description reviewers re-run, thread pinning and NUMA control, seeds and warm-up, compiler/driver/flag provenance, and building an environment that reproduces the paper's scaling trend on different machines.
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
- Making a PPoPP papers parallel-performance results reproducible
- Covering the hardware and topology description reviewers re-run
- Thread pinning and NUMA control
- Seeds and warm-up
Example prompts
- “/ppopp-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
Ppopp Reproducibility loads about 1.1k tokens when it runs. Until then it costs about 85 tokens; SKILL.md has 394 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). 394 words, ~1,122 tokens.
Download SKILL.mdSave it as
.claude/skills/ppopp-reproducibility/SKILL.md (or your agent's skills folder).- name
- ppopp-reproducibility
- description
- Use when making a PPoPP paper's parallel-performance results reproducible, covering the hardware and topology description reviewers re-run, thread pinning and NUMA control, seeds and warm-up, compiler/driver/flag provenance, and building an environment that reproduces the paper's scaling trend on different machines.
PPoPP Reproducibility
Build the reproducibility story that a parallel-performance paper needs. Unlike a deterministic algorithm, a PPoPP result depends on the machine, the topology, and the run conditions — and an evaluator or a future reader will not have your exact node. Reproducibility here means someone else can rebuild the environment and recover the scaling trend and the relative comparison, even when their absolute numbers differ. Pin everything you can at run time; you cannot reconstruct it after the machine is released.
The environment description reviewers actually re-run
State enough that a stranger could stand up the same experiment:
[CPU] exact model, sockets, cores/threads, base/turbo policy, NUMA node layout
[Memory] size, channels, speed; per-socket bandwidth if it bounds you
[GPU] model, count, driver + CUDA/ROCm version, connection (PCIe/NVLink)
[Interconnect] for multi-node: fabric and topology
[Software] OS + kernel, compiler + version + exact flags, libraries + versions, allocator
[Runtime] thread count(s), pinning/affinity policy, scheduler settings, env varsAn evaluation whose machine is described only as "a Linux server" is the one reviewers trust least and cannot reproduce.
Control the sources of parallel non-determinism
- Thread pinning / affinity. Pin threads to cores and state the policy; unpinned runs migrate
and produce unrepeatable numbers. Document NUMA placement (e.g.,
numactl, first-touch policy). - Warm-up. Discard JIT, cache, and allocator warm-up; report the steady-state measurement protocol and how many iterations you drop.
- Seeds. Fix and record seeds for any randomized workload, input generator, or scheduler.
- Frequency scaling. Disable turbo/DVFS or report that it is on; otherwise speedups drift with temperature and neighbors.
- Isolation. Run on a quiescent machine with no co-tenants; note it.
- Repeats. Multiple runs with reported variance — reproducibility includes the spread, not just the mean.
Show full SKILL.md (172 more words)Show less
Reproduce the trend, not just the number
Because evaluators have different hardware, design the package so the conclusion survives a change of machine:
- Provide a scaled-down configuration whose curve shape (linear region, saturation point) matches the paper, runnable on modest hardware.
- State the minimum configuration on which the claim still holds, and the tolerance within which you consider a result reproduced (e.g., "monotone speedup to the machine's core count," or "within 10% at matched core counts").
- Separate machine-dependent absolute throughput from machine-independent claims (relative speedup, scaling shape, correctness).
Data and workloads
- Ship or point to the exact inputs (graphs, matrices, traces) with sizes and provenance, not just a generator script — or ship the generator with its seed.
- For real-application workloads, document versions and how they were built; a benchmark suite name without a version pin is not reproducible.
Correctness reproducibility
- If a model checker or race detector supports your correctness claim, ship its configuration and the harness so the check itself can be re-run, not just described.
Pre-submission reproducibility pass
[Fresh checkout] build from a clean clone in the pinned container -> succeeds?
[Blind re-run] a colleague re-runs a scaling figure on a *different* machine -> trend matches?
[Provenance] every number in the paper traces to a script + a recorded machine config?
[Anonymity] the review-time package hides machine names, accounts, and personal repos?Output format
[Environment] CPU/GPU/memory/interconnect/software/runtime fully stated? gaps: <...>
[Non-determinism] pinning, warm-up, seeds, frequency, isolation, repeats controlled? list gaps
[Trend portability] scaled config + minimum config + tolerance stated? yes/no
[Data] exact inputs or seeded generator shipped/pinned? yes/no
[Pass result] fresh-checkout build + cross-machine trend match? yes/no© 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 PPoPP-Skills/skills/ppopp-reproducibility of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Ppopp 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 |
|---|---|---|---|---|---|---|
| Ppopp 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
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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 Ppopp Reproducibility
What does Ppopp Reproducibility do?
A skill your agent uses when making a PPoPP paper's parallel-performance results reproducible, covering the hardware and topology description reviewers re-run, thread pinning and NUMA control, seeds…. Ppopp Reproducibility is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when making a PPoPP paper's parallel-performance results reproducible, covering the hardware and topology description reviewers re-run, thread pinning and NUMA control, seeds and warm-up, compiler/driver/flag provenance, and building an environment that reproduces the paper's scaling trend on different machines.
When should I use Ppopp Reproducibility?
Ppopp Reproducibility fits situations like: making a PPoPP papers parallel-performance results reproducible; covering the hardware and topology description reviewers re-run; thread pinning and NUMA control; seeds and warm-up.
How do I install Ppopp Reproducibility in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ppopp-reproducibility -a claude-code`. Or copy the skill folder (PPoPP-Skills/skills/ppopp-reproducibility in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/ppopp-reproducibility in your project. Claude Code loads it when a task matches its description.
How do I install Ppopp Reproducibility in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ppopp-reproducibility -a codex`. Or copy the skill folder (PPoPP-Skills/skills/ppopp-reproducibility in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/ppopp-reproducibility in your project. Codex loads it when a task matches its description.
Can I use Ppopp 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 ppopp-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/ppopp-reproducibility, .gemini/skills/ppopp-reproducibility, .github/skills/ppopp-reproducibility and .opencode/skills/ppopp-reproducibility in your project.
What does Ppopp Reproducibility need to run?
SKILL.md names no scripts, command-line tools or credentials: Ppopp Reproducibility is instructions for the agent only.
Does Ppopp 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 Ppopp 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 Ppopp Reproducibility use?
Ppopp 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 Ppopp Reproducibility use?
About 1.1k tokens (SKILL.md is roughly 4.5k 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 Ppopp Reproducibility?
Skills that share tags, products or a category with Ppopp 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 Ppopp 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.