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 IEEE PerCom reproducibility and open-data evidence for human-subjects sensing, covering the dataset-availability statement, de-identified datasets with…
Install Percom Reproducibility
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill percom-reproducibility -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills percom-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/PerCom-Skills/skills/percom-reproducibility .claude/skills/percom-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 "percom-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/PerCom-Skills/skills/percom-reproducibility into .claude/skills/percom-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "percom-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/PerCom-Skills/skills/percom-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 percom-reproducibility -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills percom-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/PerCom-Skills/skills/percom-reproducibility .agents/skills/percom-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 "percom-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/PerCom-Skills/skills/percom-reproducibility into .agents/skills/percom-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "percom-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 percom-reproducibility -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills percom-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/PerCom-Skills/skills/percom-reproducibility .cursor/skills/percom-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 "percom-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/PerCom-Skills/skills/percom-reproducibility into .cursor/skills/percom-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "percom-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 PerCom-Skills/skills/percom-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 percom-reproducibility -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills percom-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/PerCom-Skills/skills/percom-reproducibility .gemini/skills/percom-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 "percom-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/PerCom-Skills/skills/percom-reproducibility into .gemini/skills/percom-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "percom-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 percom-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 percom-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/PerCom-Skills/skills/percom-reproducibility .github/skills/percom-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 "percom-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/PerCom-Skills/skills/percom-reproducibility into .github/skills/percom-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "percom-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 percom-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 percom-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/PerCom-Skills/skills/percom-reproducibility .opencode/skills/percom-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 "percom-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/PerCom-Skills/skills/percom-reproducibility into .opencode/skills/percom-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "percom-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
percom-reproducibility- GitHub stars
- 1.2k
- Token cost
- ~1.4k tokens
- SKILL.md length
- 526 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when strengthening IEEE PerCom reproducibility and open-data evidence for human-subjects sensing, covering the dataset-availability statement, de-identified datasets with…
- Strengthening IEEE PerCom reproducibility and open-data evidence for human-subjects sensing
- SKILL.md covers Evidence map, Dataset-availability statement…, Sensing provenance floor and Degrees of reproducibility…, plus 3 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Covering the dataset-availability statement
What it does
Percom Reproducibility is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when strengthening IEEE PerCom reproducibility and open-data evidence for human-subjects sensing, covering the dataset-availability statement, de-identified datasets with IRB/consent handling, sensing provenance (devices, sampling, labeling), cross-subject reproducibility, honest degrees of reproducibility, and consistency between what the paper says and what the dataset contains.
Its SKILL.md is about 1.4k 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 IEEE PerCom reproducibility and open-data evidence for human-subjects sensing
- Covering the dataset-availability statement
- De-identified datasets with IRB/consent handling
- Sensing provenance (devices
Example prompts
- “/percom-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
Percom Reproducibility loads about 1.4k tokens when it runs. Until then it costs about 103 tokens; SKILL.md has 526 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). 526 words, ~1,375 tokens.
Download SKILL.mdSave it as
.claude/skills/percom-reproducibility/SKILL.md (or your agent's skills folder).- name
- percom-reproducibility
- description
- Use when strengthening IEEE PerCom reproducibility and open-data evidence for human-subjects sensing, covering the dataset-availability statement, de-identified datasets with IRB/consent handling, sensing provenance (devices, sampling, labeling), cross-subject reproducibility, honest degrees of reproducibility, and consistency between what the paper says and what the dataset contains.
PerCom Reproducibility
Use this before submission and again before camera-ready. In pervasive computing, reproducibility turns on the sensing data: a PerCom result is only as trustworthy as the dataset behind it, how it was collected, and whether it generalizes across people. The goal is that a competent reader could rebuild your pipeline and reach your conclusions — and, where ethics permit, on your actual data.
Evidence map
- Map each recognition/system claim and reported number to a verifiable location — a paper section, a table generated from logged data, or a script in the artifact.
- For recognizers, give enough of the features, model, hyperparameters, and evaluation split (leave-one-subject-out / leave-one-session-out) that a reader could re-run it.
- For datasets, report subjects and their selection, sensors and placement, sampling rates, labeling protocol and inter-annotator agreement, and preprocessing (filtering, windowing, normalization).
- Keep the dataset-availability statement truthful and specific: what is shared, where it will live after acceptance, and — if something cannot be shared — exactly why (privacy, IRB, consent).
- Keep the paper and the dataset consistent: a number in the PDF that no script reproduces from the released data is the contradiction reviewers read as carelessness.
Dataset-availability statement audit
| Claim in the paper | Weak availability answer | PerCom-ready answer |
|---|---|---|
| "We collected data from N participants" | "Dataset available on request" | De-identified dataset + datasheet, or a documented restricted-access path with the ethics reason |
| "Our recognizer generalizes across users" | "Code will be released" | Runnable pipeline with a LOSO reproduction script and a README demo |
| "We labeled activities" | Nothing about protocol | Labeling protocol, annotator agreement, and the label files |
| "We deployed in a smart space" | "Testbed is proprietary" | Sensor list, placement, and sampling; simulated/sample data if the raw cannot ship |
"Available on request" reads as not available; convert every such line into a concrete, de-identified dataset or an explicit, justified exception with a request path.
Sensing provenance floor
[Devices] device models + firmware, sensor types, sampling rates, placement on body/space
[Labels] labeling protocol, who labeled, inter-annotator agreement, label schema
[Preprocess] filtering, windowing, normalization, resampling -- the exact pipeline, not prose
[Splits] leave-one-subject-out / session-out defined so a reader reproduces the same folds
[Ethics] IRB/approval status, consent scope, and the de-identification performed
[Compute] hardware, training time, number of runs so a reader can size a reproduction
[Randomness] seeds for any stochastic step; say what is and is not deterministicShow full SKILL.md (221 more words)Show less
Degrees of reproducibility (state the one you achieved)
- Turnkey: one documented command regenerates each table/figure (including the LOSO result) from released data.
- Scripted: scripts exist but require documented manual steps or restricted-data access.
- Descriptive: prose detailed enough that a competent reader could rebuild the pipeline.
For PerCom, aim turnkey for anything a reviewer might rerun quickly (inference on a bundled sample, a plot from logged features); full raw human-subjects data may stay scripted with restricted access when consent/IRB forbids public release — but say so honestly rather than promising turnkey behavior that cannot legally run.
Vignette: a wearable HAR study
Consider a study collecting wrist-IMU data from participants doing daily activities. Its reproducibility spine: the collection protocol and device/sampling details; the de-identified extracted dataset with a datasheet; the labeling protocol with annotator agreement; the feature and model code; the leave-one-subject-out evaluation scripts that regenerate the F1 table; and one honest sentence about the parts (raw video used for labeling, re-identifiable timestamps) that cannot be shared and why.
Consistency and camera-ready pass
- Before submission: every scored number traces to the artifact; the availability statement matches reality; the review package is anonymized (no testbed, lab, or owner strings).
- Before camera-ready: swap anonymized links for a permanent, DOI-issuing, de-identified deposit
(IEEE DataPort / Zenodo), and align the statement with what you actually release
(
percom-artifact-evaluation).
Output format
[Claim inventory] <claim -> evidence location>
[Dataset availability] concrete / vague / restricted-with-reason / missing
[Provenance gaps] <devices / labels / preprocessing / splits / ethics / seeds / compute>
[Cross-subject reproduction] LOSO script present and matching the paper? yes/no
[Reproducibility level] turnkey / scripted / descriptive, stated honestly
[Paper fixes] <must appear in the PDF>
[Dataset fixes] <additions before release>© 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 PerCom-Skills/skills/percom-reproducibility of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Percom 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 |
|---|---|---|---|---|---|---|
| Percom Reproducibility this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.4k | 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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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
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Scaffold a complete Bactopia Tool across all three tiers -- module, subworkflow, and workflow entry point under workflows/bactopia-tools/.
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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 Percom Reproducibility
What does Percom Reproducibility do?
A skill your agent uses when strengthening IEEE PerCom reproducibility and open-data evidence for human-subjects sensing, covering the dataset-availability statement, de-identified datasets with…. Percom Reproducibility is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when strengthening IEEE PerCom reproducibility and open-data evidence for human-subjects sensing, covering the dataset-availability statement, de-identified datasets with IRB/consent handling, sensing provenance (devices, sampling, labeling), cross-subject reproducibility, honest degrees of reproducibility, and consistency between what the paper says and what the dataset contains.
When should I use Percom Reproducibility?
Percom Reproducibility fits situations like: strengthening IEEE PerCom reproducibility and open-data evidence for human-subjects sensing; covering the dataset-availability statement; de-identified datasets with IRB/consent handling; sensing provenance (devices.
How do I install Percom Reproducibility in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill percom-reproducibility -a claude-code`. Or copy the skill folder (PerCom-Skills/skills/percom-reproducibility in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/percom-reproducibility in your project. Claude Code loads it when a task matches its description.
How do I install Percom Reproducibility in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill percom-reproducibility -a codex`. Or copy the skill folder (PerCom-Skills/skills/percom-reproducibility in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/percom-reproducibility in your project. Codex loads it when a task matches its description.
Can I use Percom 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 percom-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/percom-reproducibility, .gemini/skills/percom-reproducibility, .github/skills/percom-reproducibility and .opencode/skills/percom-reproducibility in your project.
What does Percom Reproducibility need to run?
SKILL.md names no scripts, command-line tools or credentials: Percom Reproducibility is instructions for the agent only.
Does Percom 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 Percom 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 Percom Reproducibility use?
Percom 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 Percom Reproducibility use?
About 1.4k tokens (SKILL.md is roughly 5.5k 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 Percom Reproducibility?
Skills that share tags, products or a category with Percom 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 Percom 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.