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 TACAS (ETAPS) reproducibility, covering the clean evaluation-VM packaging that the artifact process assumes, pinned dependencies and offline execution, a…
Install Tacas Reproducibility
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill tacas-reproducibility -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills tacas-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/TACAS-Skills/skills/tacas-reproducibility .claude/skills/tacas-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 "tacas-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/TACAS-Skills/skills/tacas-reproducibility into .claude/skills/tacas-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tacas-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/TACAS-Skills/skills/tacas-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 tacas-reproducibility -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills tacas-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/TACAS-Skills/skills/tacas-reproducibility .agents/skills/tacas-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 "tacas-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/TACAS-Skills/skills/tacas-reproducibility into .agents/skills/tacas-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tacas-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 tacas-reproducibility -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills tacas-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/TACAS-Skills/skills/tacas-reproducibility .cursor/skills/tacas-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 "tacas-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/TACAS-Skills/skills/tacas-reproducibility into .cursor/skills/tacas-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tacas-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 TACAS-Skills/skills/tacas-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 tacas-reproducibility -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills tacas-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/TACAS-Skills/skills/tacas-reproducibility .gemini/skills/tacas-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 "tacas-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/TACAS-Skills/skills/tacas-reproducibility into .gemini/skills/tacas-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tacas-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 tacas-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 tacas-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/TACAS-Skills/skills/tacas-reproducibility .github/skills/tacas-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 "tacas-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/TACAS-Skills/skills/tacas-reproducibility into .github/skills/tacas-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tacas-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 tacas-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 tacas-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/TACAS-Skills/skills/tacas-reproducibility .opencode/skills/tacas-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 "tacas-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/TACAS-Skills/skills/tacas-reproducibility into .opencode/skills/tacas-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tacas-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
tacas-reproducibility- GitHub stars
- 1.2k
- Token cost
- ~1.3k tokens
- SKILL.md length
- 487 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when strengthening TACAS (ETAPS) reproducibility, covering the clean evaluation-VM packaging that the artifact process assumes, pinned dependencies and offline execution, a…
- Strengthening TACAS (ETAPS) reproducibility
- SKILL.md covers Design for the clean ETAPS VM, Claim-to-script mapping (the…, Claim-to-evidence audit and Degrees of reproducibility…, plus 3 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Covering the clean evaluation-VM packaging that the artifact process assumes
What it does
Tacas Reproducibility is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when strengthening TACAS (ETAPS) reproducibility, covering the clean evaluation-VM packaging that the artifact process assumes, pinned dependencies and offline execution, a claim-to-script mapping so every benchmark number regenerates, honest degrees of reproducibility, consistency between the paper and the artifact, and the category difference between a mandatory tool-paper artifact and a voluntary research-paper artifact.
Its SKILL.md is about 1.3k 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 TACAS (ETAPS) reproducibility
- Covering the clean evaluation-VM packaging that the artifact process assumes
- Pinned dependencies and offline execution
- A claim-to-script mapping so every benchmark number regenerates
Example prompts
- “/tacas-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
Tacas Reproducibility loads about 1.3k tokens when it runs. Until then it costs about 113 tokens; SKILL.md has 487 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). 487 words, ~1,286 tokens.
Download SKILL.mdSave it as
.claude/skills/tacas-reproducibility/SKILL.md (or your agent's skills folder).- name
- tacas-reproducibility
- description
- Use when strengthening TACAS (ETAPS) reproducibility, covering the clean evaluation-VM packaging that the artifact process assumes, pinned dependencies and offline execution, a claim-to-script mapping so every benchmark number regenerates, honest degrees of reproducibility, consistency between the paper and the artifact, and the category difference between a mandatory tool-paper artifact and a voluntary research-paper artifact.
TACAS Reproducibility
Use this before submission (for tool papers, before the mandatory artifact deadline) and again before camera-ready. At TACAS reproducibility is not a courtesy: for a regular tool or tool-demonstration paper the artifact is mandatory and feeds acceptance, and for a research or case-study paper a voluntary artifact earns the title-page badges. The goal is that an ETAPS evaluator, on a clean virtual machine, can rebuild your evidence and reach your numbers.
Design for the clean ETAPS VM
The artifact process assumes a provided VM image with bounded evaluator time. Package accordingly:
[Self-contained] ship a VM-ready package: a Dockerfile or a pinned environment (lockfile), with
the tool prebuilt; not "apt-get install 30 things and hope"
[Offline] no network access at run time; vendor every dependency, benchmark, and model
[Bounded] a short smoke run that finishes in minutes, plus a documented full run with its
expected (possibly long) runtime
[Deterministic] fix seeds and tool options; state what is and is not deterministic
[Documented] a README that orients an evaluator in one screen: what it is, how to run the
smoke test, how to reproduce each claim, expected outputs and runtimesClaim-to-script mapping (the heart of a TACAS artifact)
- Map each reported table, figure, and headline number to a script and its expected output.
- Provide a top-level
reproduce/(or equivalent) that regenerates results from logged data, and a separate path that re-runs the tool from scratch for those who have the time budget. - State the machine you produced the numbers on; evaluators on different hardware should still see the same verdicts and the same relative comparison even if wall-clock differs.
Claim-to-evidence audit
| Claim in the paper | Weak artifact answer | TACAS-ready answer |
|---|---|---|
| "Solves N benchmarks" | "Benchmarks available on request" | The exact task set vendored + a script printing solved/unsolved |
"Faster than <baseline>" | Only your tool shipped | Both tools (or the baseline's install) with the equal-budget harness |
| "Sound / sound up to k" | Verdicts unchecked | A validation script (witness checking / cross-tool agreement) |
| "The counterexample is real" | Prose only | A replayable witness the evaluator can validate |
"Available on request" and "works on our cluster" are treated as not reproducible at TACAS; convert every such line into a concrete, VM-runnable script.
Show full SKILL.md (220 more words)Show less
Degrees of reproducibility (state the one you achieved)
- Turnkey: one documented command regenerates each table/figure from logged data on the VM.
- Scripted: scripts exist but need documented manual steps or a large external benchmark download.
- Descriptive: prose detailed enough that a competent reader could rebuild the pipeline.
For a tool paper, aim turnkey for the smoke run and the headline comparison — that is what the AEC checks against the Functional (and ideally Reusable) badge. Large full-benchmark runs may stay scripted with the time budget documented. Stating the achieved level honestly beats promising turnkey behaviour that fails on the clean VM.
Category difference
- Regular tool / tool-demonstration: the artifact is mandatory, submitted right after the paper, evaluated with the PC — plan it as a co-equal deliverable, not a follow-up.
- Regular research / case-study: the artifact is voluntary and post-acceptance; if you want the badges, prepare it after notification, but the paper must already be self-contained on the evidence side.
Consistency and camera-ready pass
- Before submission (or the artifact deadline): every scored number traces to a VM-runnable script; the paper and artifact agree; for a research paper the artifact is anonymized (no owner strings, cluster paths, lab names, identity-revealing repo URLs).
- Before camera-ready: swap any anonymized/placeholder location for a permanent, DOI-issuing archive
(Zenodo/figshare/Software Heritage) and align with the badges you earned (
tacas-artifact-evaluation).
Output format
[Claim inventory] <claim -> script -> expected output>
[Clean-VM readiness] runs offline on a fresh VM? smoke test in minutes? yes/no
[Reproducibility level] turnkey / scripted / descriptive, stated honestly
[Soundness/validation] <witness or cross-tool check present? yes/no>
[Category obligation] mandatory (tool/tool-demo) / voluntary (research/case-study)
[Fixes before upload] <ordered list>© 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 TACAS-Skills/skills/tacas-reproducibility of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Tacas 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 |
|---|---|---|---|---|---|---|
| Tacas Reproducibility this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.3k | 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 Tacas Reproducibility
What does Tacas Reproducibility do?
A skill your agent uses when strengthening TACAS (ETAPS) reproducibility, covering the clean evaluation-VM packaging that the artifact process assumes, pinned dependencies and offline execution, a…. Tacas Reproducibility is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when strengthening TACAS (ETAPS) reproducibility, covering the clean evaluation-VM packaging that the artifact process assumes, pinned dependencies and offline execution, a claim-to-script mapping so every benchmark number regenerates, honest degrees of reproducibility, consistency between the paper and the artifact, and the category difference between a mandatory tool-paper artifact and a voluntary research-paper artifact.
When should I use Tacas Reproducibility?
Tacas Reproducibility fits situations like: strengthening TACAS (ETAPS) reproducibility; covering the clean evaluation-VM packaging that the artifact process assumes; pinned dependencies and offline execution; A claim-to-script mapping so every benchmark number regenerates.
How do I install Tacas Reproducibility in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill tacas-reproducibility -a claude-code`. Or copy the skill folder (TACAS-Skills/skills/tacas-reproducibility in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/tacas-reproducibility in your project. Claude Code loads it when a task matches its description.
How do I install Tacas Reproducibility in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill tacas-reproducibility -a codex`. Or copy the skill folder (TACAS-Skills/skills/tacas-reproducibility in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/tacas-reproducibility in your project. Codex loads it when a task matches its description.
Can I use Tacas 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 tacas-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/tacas-reproducibility, .gemini/skills/tacas-reproducibility, .github/skills/tacas-reproducibility and .opencode/skills/tacas-reproducibility in your project.
What does Tacas Reproducibility need to run?
SKILL.md names no scripts, command-line tools or credentials: Tacas Reproducibility is instructions for the agent only.
Does Tacas 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 Tacas 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 Tacas Reproducibility use?
Tacas 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 Tacas Reproducibility use?
About 1.3k tokens (SKILL.md is roughly 5.1k 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 Tacas Reproducibility?
Skills that share tags, products or a category with Tacas 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 Tacas 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.