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 a STOC (ACM Symposium on Theory of Computing) paper so its results can be independently checked — proof completeness across the extended-abstract/full-version…
Install Stoc Reproducibility
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill stoc-reproducibility -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills stoc-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/STOC-Skills/skills/stoc-reproducibility .claude/skills/stoc-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 "stoc-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/STOC-Skills/skills/stoc-reproducibility into .claude/skills/stoc-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "stoc-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/STOC-Skills/skills/stoc-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 stoc-reproducibility -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills stoc-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/STOC-Skills/skills/stoc-reproducibility .agents/skills/stoc-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 "stoc-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/STOC-Skills/skills/stoc-reproducibility into .agents/skills/stoc-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "stoc-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 stoc-reproducibility -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills stoc-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/STOC-Skills/skills/stoc-reproducibility .cursor/skills/stoc-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 "stoc-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/STOC-Skills/skills/stoc-reproducibility into .cursor/skills/stoc-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "stoc-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 STOC-Skills/skills/stoc-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 stoc-reproducibility -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills stoc-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/STOC-Skills/skills/stoc-reproducibility .gemini/skills/stoc-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 "stoc-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/STOC-Skills/skills/stoc-reproducibility into .gemini/skills/stoc-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "stoc-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 stoc-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 stoc-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/STOC-Skills/skills/stoc-reproducibility .github/skills/stoc-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 "stoc-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/STOC-Skills/skills/stoc-reproducibility into .github/skills/stoc-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "stoc-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 stoc-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 stoc-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/STOC-Skills/skills/stoc-reproducibility .opencode/skills/stoc-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 "stoc-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/STOC-Skills/skills/stoc-reproducibility into .opencode/skills/stoc-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "stoc-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
stoc-reproducibility- GitHub stars
- 1.2k
- Token cost
- ~1.7k tokens
- SKILL.md length
- 780 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when hardening a STOC (ACM Symposium on Theory of Computing) paper so its results can be independently checked — proof completeness across the extended-abstract/full-version…
- Works in 5 steps: Freeze statements four weeks out; from… → Assign each theorem a verifier who did… → Grep both documents for confessions:… → …
- Single-source builds that prevent statement drift between the two documents
- SKILL.md covers Statement drift: the…, Checkability audit before…, Computation that claims depend… and Verification workflow for the…, plus 3 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Stoc Reproducibility is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when hardening a STOC (ACM Symposium on Theory of Computing) paper so its results can be independently checked — proof completeness across the extended-abstract/full-version split, single-source builds that prevent statement drift between the two documents, and determinism for any computation a claim relies on.
Its SKILL.md is about 1.7k 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
- Single-source builds that prevent statement drift between the two documents
- Determinism for any computation a claim relies on
Example prompts
- “/stoc-reproducibility”
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- Freeze statements four weeks out; from then on, statement edits require a
- Assign each theorem a verifier who did not write its proof; record
- Grep both documents for confessions: wlog, clearly, standard,
- Re-derive the main constant chain once, by hand, on paper, from the final
- After camera-ready, keep the full version live-maintained: arXiv revision
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 latex).
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
Stoc Reproducibility loads about 1.7k tokens when it runs. Until then it costs about 84 tokens; SKILL.md has 780 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). 780 words, ~1,665 tokens.
Download SKILL.mdSave it as
.claude/skills/stoc-reproducibility/SKILL.md (or your agent's skills folder).- name
- stoc-reproducibility
- description
- Use when hardening a STOC (ACM Symposium on Theory of Computing) paper so its results can be independently checked — proof completeness across the extended-abstract/full-version split, single-source builds that prevent statement drift between the two documents, and determinism for any computation a claim relies on.
STOC Reproducibility
For a proofs-only venue, "reproducible" means a third party can verify every claimed theorem without contacting the authors. STOC's structure makes this a two-document problem that pure-appendix venues do not have: the committee reads a 12-page guaranteed window, the community reads the arXiv/ECCC full version, and the paper is only as checkable as the pair is consistent. No checklist form enforces any of this — the STOC 2026 CFP contains none (checked 2026-07-08) — so the discipline below is self-imposed or absent.
Statement drift: the STOC-specific failure
Whenever the same theorem exists in two documents, the versions decay apart: a hypothesis strengthened during a proof repair gets updated in one file only; a constant improves in the full version while the abstract still advertises the old one; numbering shifts and cross-references silently point at the wrong lemma. Drift is not cosmetic — a reader who finds Theorem 2's statement differing between the proceedings and arXiv cannot tell which one is proved.
The mechanical cure is a single-source build: one repository of statement files included by both documents, so a statement physically cannot fork.
% statements/thm-main.tex (the only copy of the claim, ever)
\begin{theorem}[Main; restated in the full version as Theorem~\ref{thm:main}]
\label{thm:main}
Under Assumption~\ref{ass:degree}, there is a deterministic
$O(m \log^{3} n)$-time algorithm computing a $(1+\varepsilon)$-approximate
solution for every fixed $\varepsilon > 0$.
\end{theorem}
% extended-abstract.tex % full-version.tex
\input{statements/thm-main} % \input{statements/thm-main}
\begin{proofsketch} ... \end{proofsketch} % \begin{proof} ... \end{proof}An \iffull toggle in a shared preamble achieves the same with one master file;
either way, the invariant is one copy of every statement on disk.
Checkability audit before submission
| Question a verifier will ask | Passing standard |
|---|---|
| Is every claim in the first 12 pages proved somewhere I can reach? | Each theorem carries a forward pointer (appendix section or full-version anchor) |
| Do the two documents state identical theorems? | Single-source statements, or a diff run over extracted statement blocks |
| Are all hypotheses visible at the statement? | No condition introduced only inside a proof ("assume wlog the graph is connected" that is not wlog) |
| Do invoked external theorems apply? | Citation with result number, plus a line confirming your setting meets its hypotheses |
| Can the parameter trail be followed? | Constants named where they first appear; "for sufficiently large n" bounded explicitly at least once |
| Are "standard" steps actually standard? | Anything a second-year graduate student cannot fill in gets written out |
Computation that claims depend on
If any theorem rests on a machine check (case enumeration, solver certificate, verified numerics), reproducibility requirements sharpen from "nice" to "load-bearing":
- Determinism: the run must be exactly repeatable — fixed enumeration order, no wall-clock cutoffs deciding mathematical facts, solver versions pinned.
- Independence: publish the certificate and a separate checker, so trust does
not reduce to trusting your search program (see
stoc-artifact-evaluationfor packaging mechanics). - Description: the paper itself must specify the computation precisely enough that someone could rewrite it from scratch; code is evidence, prose is the specification.
Illustrative-only plots and timing anecdotes carry no proof weight and need only
honesty: seed and instance disclosure, no claims beyond what is proved
(stoc-experiments covers when to include them at all).
Show full SKILL.md (318 more words)Show less
Verification workflow for the author team
- Freeze statements four weeks out; from then on, statement edits require a team-visible diff, because every edit can invalidate a downstream proof.
- Assign each theorem a verifier who did not write its proof; record pass/fail per proof section, and treat any "I believe it but cannot check line 5" as a fail.
- Grep both documents for confessions:
wlog,clearly,standard,similar,it is easy to see— each hit either survives justification or gets expanded. - Re-derive the main constant chain once, by hand, on paper, from the final text only. This catches the strengthened-hypothesis-updated-once bug that review will otherwise catch for you.
- After camera-ready, keep the full version live-maintained: arXiv revision with a dated changelog is the community's accepted correction channel.
Vignette: how drift actually happens
A team submits in November with Theorem 2 requiring subgaussian noise. In December a reviewer-anticipating coauthor realizes the proof of Lemma 7 uses a fourth-moment bound that subgaussianity gives but the written hypothesis does not state; she patches the full-version draft to "subgaussian with parameter $\sigma$" and adjusts two constants. The extended abstract is not touched — nobody is editing a submitted file. At camera-ready in March, the proceedings version is produced from the submitted sources, and the published extended abstract now states a theorem the team knows is proved only under the amended hypothesis. Nothing dishonest happened at any step; the pipeline had two copies of one statement and no synchronization rule. The single-source layout above makes this sequence structurally impossible, which is why it is worth the Makefile friction.
Cycle-volatility warnings
- If a future CFP introduces any structured checklist, code policy, or supplementary channel, it will say so; the 2026 cycle had none (待核实 yearly).
- The 12-page guaranteed window and the full-version expectation are 2026 wording; both shape where proofs must live, so re-read the live CFP before restructuring.
Output format
[Checkability verdict] verifiable end-to-end / gaps found
[Statement-drift control] single-source / manual sync (risk) / diverged <- fix
[Hypothesis visibility] clean / hidden conditions at: <list>
[External results] all hypothesis-checked / unchecked: <citations>
[Load-bearing computation] none / deterministic + certified / unreproducible <- blocker© 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 STOC-Skills/skills/stoc-reproducibility of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Stoc 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 |
|---|---|---|---|---|---|---|
| Stoc Reproducibility this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.7k | 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 |
Similar skills
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.
More from brycewang-stanford/Awesome-Journal-Skills
All 2,387 skills in this repoAaag Data Analysis
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when running and reporting the analysis for an Annals of the American Association of Geographers manuscript — spatial statistics and modeling, remote-sensing accuracy, or…
Aaag Literature Positioning
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when positioning an Annals of the American Association of Geographers manuscript in the literature — engaging geographic scholarship across the relevant area and the…
Aaag Rebuttal
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when responding to an Annals of the American Association of Geographers decision letter (major/minor revision) — building a point-by-point response to the subject editor and…
Aaag Research Design
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when defending the research design of an Annals of the American Association of Geographers manuscript — spatial/quantitative analysis and GIScience, remote-sensing and…
Aaag Review Process
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when you need to understand how the Annals of the American Association of Geographers evaluates a manuscript — double-anonymous review routed through a subject editor by…
Aaag Submission
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when running the final pre-submission preflight for the Annals of the American Association of Geographers via ScholarOne Manuscripts — area/article-type selection…
Related
Categories
Questions about Stoc Reproducibility
What does Stoc Reproducibility do?
A skill your agent uses when hardening a STOC (ACM Symposium on Theory of Computing) paper so its results can be independently checked — proof completeness across the extended-abstract/full-version…. Stoc Reproducibility is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when hardening a STOC (ACM Symposium on Theory of Computing) paper so its results can be independently checked — proof completeness across the extended-abstract/full-version split, single-source builds that prevent statement drift between the two documents, and determinism for any computation a claim relies on.
When should I use Stoc Reproducibility?
Stoc Reproducibility fits situations like: single-source builds that prevent statement drift between the two documents; determinism for any computation a claim relies on.
How do I install Stoc Reproducibility in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill stoc-reproducibility -a claude-code`. Or copy the skill folder (STOC-Skills/skills/stoc-reproducibility in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/stoc-reproducibility in your project. Claude Code loads it when a task matches its description.
How do I install Stoc Reproducibility in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill stoc-reproducibility -a codex`. Or copy the skill folder (STOC-Skills/skills/stoc-reproducibility in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/stoc-reproducibility in your project. Codex loads it when a task matches its description.
Can I use Stoc 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 stoc-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/stoc-reproducibility, .gemini/skills/stoc-reproducibility, .github/skills/stoc-reproducibility and .opencode/skills/stoc-reproducibility in your project.
What does Stoc Reproducibility need to run?
SKILL.md names no scripts, command-line tools or credentials: Stoc Reproducibility is instructions for the agent only.
Does Stoc 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 Stoc 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 Stoc Reproducibility use?
Stoc 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 Stoc Reproducibility use?
About 1.7k tokens (SKILL.md is roughly 6.7k 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 Stoc Reproducibility?
Skills that share tags, products or a category with Stoc 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 Stoc 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.