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 the verifiability of a SODA (ACM-SIAM Symposium on Discrete Algorithms) paper, where reproducibility means checkable mathematics — complete proofs in the…
Install Soda Reproducibility
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill soda-reproducibility -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills soda-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/SODA-Skills/skills/soda-reproducibility .claude/skills/soda-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 "soda-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/SODA-Skills/skills/soda-reproducibility into .claude/skills/soda-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "soda-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/SODA-Skills/skills/soda-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 soda-reproducibility -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills soda-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/SODA-Skills/skills/soda-reproducibility .agents/skills/soda-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 "soda-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/SODA-Skills/skills/soda-reproducibility into .agents/skills/soda-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "soda-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 soda-reproducibility -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills soda-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/SODA-Skills/skills/soda-reproducibility .cursor/skills/soda-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 "soda-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/SODA-Skills/skills/soda-reproducibility into .cursor/skills/soda-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "soda-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 SODA-Skills/skills/soda-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 soda-reproducibility -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills soda-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/SODA-Skills/skills/soda-reproducibility .gemini/skills/soda-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 "soda-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/SODA-Skills/skills/soda-reproducibility into .gemini/skills/soda-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "soda-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 soda-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 soda-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/SODA-Skills/skills/soda-reproducibility .github/skills/soda-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 "soda-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/SODA-Skills/skills/soda-reproducibility into .github/skills/soda-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "soda-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 soda-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 soda-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/SODA-Skills/skills/soda-reproducibility .opencode/skills/soda-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 "soda-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/SODA-Skills/skills/soda-reproducibility into .opencode/skills/soda-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "soda-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
soda-reproducibility- GitHub stars
- 1.2k
- Token cost
- ~1.5k tokens
- SKILL.md length
- 645 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when hardening the verifiability of a SODA (ACM-SIAM Symposium on Discrete Algorithms) paper, where reproducibility means checkable mathematics — complete proofs in the…
- Works in 6 steps: Ledger complete: every claim has a proof… → Bound re-derivation pass: recompute each… → Import pass: every external theorem… → …
- Hardening the verifiability of a SODA (ACM-SIAM Symposium on Discrete Algorithms) paper
- SKILL.md covers The verifiability ledger, Failure modes referees…, Worked micro-example: a… and Machine-checked steps, plus 3 more sections
- Calls git and python3
What it does
Soda Reproducibility is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when hardening the verifiability of a SODA (ACM-SIAM Symposium on Discrete Algorithms) paper, where reproducibility means checkable mathematics — complete proofs in the submitted full version, stable statement-proof correspondence, explicit constants and model assumptions, and certificates for any machine-checked step.
Its SKILL.md is about 1.5k 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 the verifiability of a SODA (ACM-SIAM Symposium on Discrete Algorithms) paper
- Where reproducibility means checkable mathematics — complete proofs in the submitted full version
- Stable statement-proof correspondence
- Explicit constants and model assumptions
Example prompts
- “/soda-reproducibility”
Requirements
- Python 3
Workflow steps
6 steps, taken from the first numbered list in SKILL.md.
- Ledger complete: every claim has a proof location and a blind checker.
- Bound re-derivation pass: recompute each headline bound from its final proof.
- Import pass: every external theorem quoted with hypotheses verified in-text.
- Probability pass: failure probabilities summed and stated once, correctly.
- Computation pass: certificates rerun from a clean clone on a second machine.
- Cross-version pass: submission, arXiv, and any slides state identical bounds.
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
Shell commands in SKILL.md call:
gitpython3
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.
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
Soda Reproducibility loads about 1.5k tokens when it runs. Until then it costs about 86 tokens; SKILL.md has 645 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). 645 words, ~1,499 tokens.
Download SKILL.mdSave it as
.claude/skills/soda-reproducibility/SKILL.md (or your agent's skills folder).- name
- soda-reproducibility
- description
- Use when hardening the verifiability of a SODA (ACM-SIAM Symposium on Discrete Algorithms) paper, where reproducibility means checkable mathematics — complete proofs in the submitted full version, stable statement-proof correspondence, explicit constants and model assumptions, and certificates for any machine-checked step.
SODA Reproducibility
At SODA, "reproducibility" is not seeds and GPUs — it is whether a competent reader can re-derive every claim from the submitted document. Because SODA takes full versions with no page limit (2027 CFP, checked 2026-07-08), there is no "details omitted" escape hatch: the community's expectation is that the PDF on HotCRP contains a complete, checkable argument. This skill is the audit for that standard.
The verifiability ledger
Build a table with one row per claim before the July deadline. It doubles as the
rebuttal-preparation ledger in September (soda-author-response).
| Column | What goes in it |
|---|---|
| Claim | Theorem/lemma/corollary number and one-line statement |
| Model | Computation model and input assumptions (RAM model? adversary? degree bounds?) |
| Proof location | Section and page of the complete proof — "sketch only" is a red flag |
| External results used | Exact citation with theorem number, plus where hypotheses are checked |
| Constants | Hidden-constant status: explicit / bounded / genuinely unbounded |
| Checked by | Coauthor who verified the proof without having written it |
Every row must close before submission. The last column is the single most valuable ritual an algorithms group can institutionalize: author-blind proof checking catches the drift bugs that referees otherwise find in August.
Failure modes referees actually report
- Statement-proof drift. The theorem says
O(m log n), the proof deliversO(m log^2 n)after a late edit. Mechanically re-derive the final bound from the final proof, not from memory. - Imported-theorem hypothesis gaps. A cited result requires constant degree; your graph is merely sparse. Quote the hypothesis next to each use.
- Model slippage. The lower bound is proved against oblivious adversaries; the abstract claims it for adaptive ones. State the model in the theorem, not only in the preliminaries.
- Randomness accounting. "With high probability" needs a stated exponent and a union-bound budget that survives all invocations.
- Case-analysis holes. For arguments with many cases, include the case inventory explicitly; referees count cases before reading any.
Worked micro-example: a probability budget
The randomness-accounting failure deserves its own drill because it compounds silently. Keep a single budget table in the source comments and make every "w.h.p." claim draw from it:
% Failure-probability budget for Theorem 2 (target: n^{-2} overall)
% E1: sampling lemma (Lemma 3.1), invoked <= n times ... n * n^{-4}
% E2: hash collision (Lemma 3.4), invoked once ... n^{-3}
% E3: concentration (Lemma 4.2), invoked <= log n ... log n * n^{-4}
% Union bound: n^{-3} + o(n^{-3}) <= n^{-2} for n >= n_0 (state n_0!)Audit questions the table forces: does each lemma's stated exponent survive
its actual invocation count in the final proof (invocation counts drift when
algorithms get restructured)? Is the constant n_0 stated anywhere? Does the
theorem statement promise the same exponent the budget delivers? A referee who
finds one unbudgeted invocation will re-check every probabilistic step in the
paper — the budget table is cheap insurance against that spiral.
Show full SKILL.md (235 more words)Show less
Machine-checked steps
When part of the argument is computational (exhaustive search over configurations, extremal-object certificates, verified constants), the reproducibility bar is a rerunnable check, not a claim of one:
# The paper should let a referee do exactly this:
git clone <anonymous-archive-url> && cd verification
python3 check.py # deterministic; prints per-case status
echo $? # 0 iff every case verifiedState in the paper the case count, total runtime on commodity hardware, and the
reduction proving that check.py succeeding implies the lemma. See
soda-artifact-evaluation for packaging and anonymity.
Full version as the reproducibility instrument
The arXiv full version is the community's long-term verification record — SODA
proceedings versions are often condensations (soda-camera-ready). Discipline:
- The submitted HotCRP version, the arXiv version, and the proceedings version must agree on every theorem statement; keep a single source with build flags rather than three diverging files.
- When a bug is found post-publication, fix the arXiv version with a dated erratum note; silent replacement erodes exactly the trust this skill protects.
- Version the bibliography: a "personal communication" load-bearing citation is a reproducibility hole; get the statement into a citable preprint or prove it yourself in an appendix.
Pre-submission audit sequence
- Ledger complete: every claim has a proof location and a blind checker.
- Bound re-derivation pass: recompute each headline bound from its final proof.
- Import pass: every external theorem quoted with hypotheses verified in-text.
- Probability pass: failure probabilities summed and stated once, correctly.
- Computation pass: certificates rerun from a clean clone on a second machine.
- Cross-version pass: submission, arXiv, and any slides state identical bounds.
Output format
[Verifiability verdict] Checkable / Gaps found / Not checkable
[Ledger gaps] <claims lacking proof location, blind check, or model statement>
[Drift findings] <statement-proof or cross-version mismatches>
[Import findings] <external results with unverified hypotheses>
[Computation findings] <uncertified machine-checked steps>
[Fix order] <ranked repairs before the July deadline>© 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 SODA-Skills/skills/soda-reproducibility of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Soda 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 |
|---|---|---|---|---|---|---|
| Soda Reproducibility this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.5k | 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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Figure Style
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Publication-grade correctness and legibility rules for final-deliverable scientific figures, not exploratory plots.
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Categories
Questions about Soda Reproducibility
What does Soda Reproducibility do?
A skill your agent uses when hardening the verifiability of a SODA (ACM-SIAM Symposium on Discrete Algorithms) paper, where reproducibility means checkable mathematics — complete proofs in the…. Soda Reproducibility is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when hardening the verifiability of a SODA (ACM-SIAM Symposium on Discrete Algorithms) paper, where reproducibility means checkable mathematics — complete proofs in the submitted full version, stable statement-proof correspondence, explicit constants and model assumptions, and certificates for any machine-checked step.
When should I use Soda Reproducibility?
Soda Reproducibility fits situations like: hardening the verifiability of a SODA (ACM-SIAM Symposium on Discrete Algorithms) paper; where reproducibility means checkable mathematics — complete proofs in the submitted full version; stable statement-proof correspondence; explicit constants and model assumptions.
How do I install Soda Reproducibility in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill soda-reproducibility -a claude-code`. Or copy the skill folder (SODA-Skills/skills/soda-reproducibility in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/soda-reproducibility in your project. Claude Code loads it when a task matches its description.
How do I install Soda Reproducibility in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill soda-reproducibility -a codex`. Or copy the skill folder (SODA-Skills/skills/soda-reproducibility in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/soda-reproducibility in your project. Codex loads it when a task matches its description.
Can I use Soda 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 soda-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/soda-reproducibility, .gemini/skills/soda-reproducibility, .github/skills/soda-reproducibility and .opencode/skills/soda-reproducibility in your project.
What does Soda Reproducibility need to run?
Going by SKILL.md and its folder, Soda Reproducibility needs the command-line tools its instructions call (git and python3). Our summary lists: Python 3.
Does Soda Reproducibility access the network?
SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Is Soda 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 Soda Reproducibility use?
Soda 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 Soda Reproducibility use?
About 1.5k tokens (SKILL.md is roughly 6k 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 Soda Reproducibility?
Skills that share tags, products or a category with Soda 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 Soda 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.