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 designing or auditing a TACAS (ETAPS) evaluation, covering shared verification benchmarks (SV-COMP-style task sets), fair baseline configuration and equal time budgets…
Install Tacas Experiments
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill tacas-experiments -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills tacas-experiments --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-experiments .claude/skills/tacas-experiments && 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-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/TACAS-Skills/skills/tacas-experiments into .claude/skills/tacas-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tacas-experiments", 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-experimentsType 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-experiments -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills tacas-experiments --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-experiments .agents/skills/tacas-experiments && 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-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/TACAS-Skills/skills/tacas-experiments into .agents/skills/tacas-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tacas-experiments", 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-experiments -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills tacas-experiments --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-experiments .cursor/skills/tacas-experiments && 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-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/TACAS-Skills/skills/tacas-experiments into .cursor/skills/tacas-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tacas-experiments", 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-experiments--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-experiments -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills tacas-experiments --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-experiments .gemini/skills/tacas-experiments && 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-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/TACAS-Skills/skills/tacas-experiments into .gemini/skills/tacas-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tacas-experiments", 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-experimentsInstalls 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-experiments -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-experiments .github/skills/tacas-experiments && 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-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/TACAS-Skills/skills/tacas-experiments into .github/skills/tacas-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tacas-experiments", 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-experiments -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-experiments --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-experiments .opencode/skills/tacas-experiments && 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-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/TACAS-Skills/skills/tacas-experiments into .opencode/skills/tacas-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tacas-experiments", 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-experiments- GitHub stars
- 1.2k
- Token cost
- ~1.4k tokens
- SKILL.md length
- 606 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when designing or auditing a TACAS (ETAPS) evaluation, covering shared verification benchmarks (SV-COMP-style task sets), fair baseline configuration and equal time budgets…
- Auditing a TACAS (ETAPS) evaluation
- SKILL.md covers Evaluation audit, Claim-to-evidence design table, Fair-comparison checklist and SV-COMP vs a TACAS tool-paper…, plus 3 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Covering shared verification benchmarks (SV-COMP-style task sets)
What it does
Tacas Experiments is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when designing or auditing a TACAS (ETAPS) evaluation, covering shared verification benchmarks (SV-COMP-style task sets), fair baseline configuration and equal time budgets, honest wall-clock/scalability reporting on stated hardware, soundness checking of results, reproducibility on the clean artifact VM, and how a TACAS tool-paper evaluation differs from a SV-COMP competition entry.
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
- Auditing a TACAS (ETAPS) evaluation
- Covering shared verification benchmarks (SV-COMP-style task sets)
- Fair baseline configuration and equal time budgets
- Honest wall-clock/scalability reporting on stated hardware
Example prompts
- “/tacas-experiments”
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 Experiments loads about 1.4k tokens when it runs. Until then it costs about 102 tokens; SKILL.md has 606 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). 606 words, ~1,441 tokens.
Download SKILL.mdSave it as
.claude/skills/tacas-experiments/SKILL.md (or your agent's skills folder).- name
- tacas-experiments
- description
- Use when designing or auditing a TACAS (ETAPS) evaluation, covering shared verification benchmarks (SV-COMP-style task sets), fair baseline configuration and equal time budgets, honest wall-clock/scalability reporting on stated hardware, soundness checking of results, reproducibility on the clean artifact VM, and how a TACAS tool-paper evaluation differs from a SV-COMP competition entry.
TACAS Experiments
Use this before submission when the empirical story is not yet locked. TACAS reviewers are verification experts, and the evaluation is where a tool or algorithm is won or lost. The organizing principle is honest, reproducible comparison: the experiment must test the claim on shared benchmarks, against a fairly configured baseline, with every number reproducible in the artifact (mandatory for tool papers).
Evaluation audit
- Use community benchmarks. Draw tasks from established suites (e.g., SV-COMP task sets, model- checking or SMT benchmark libraries, prior tool distributions) rather than a private set of favourable inputs. A benchmark nobody else uses invites the "cherry-picked" reject.
- Configure baselines fairly. Compare against the strongest available competing tool, with a documented, equal time and memory budget on the same hardware. An untuned or crippled baseline is a scored weakness, and reviewers often know the baseline's authors.
- Report the right quantities. Solved/unsolved counts, wall-clock time with the timeout stated, memory, and the largest instance handled — not a single ratio. State the machine (CPU, RAM) and the number of repetitions for any variance.
- Check your results for soundness. Verification tools can be fast because they are wrong: report how you validated answers (cross-checking against a reference tool, witness validation, known expected verdicts), and disclose any incorrect results rather than hiding them.
- Reproduce in the artifact. Every table and figure must regenerate from a script in the artifact on the clean ETAPS VM; a tool paper whose numbers cannot be reproduced fails the mandatory artifact evaluation and endangers the paper.
- Bound external validity. Say which languages, property classes, or system sizes the results cover, and name the ones they do not.
Claim-to-evidence design table
| Verification claim | Matching evidence | Reject pattern avoided |
|---|---|---|
| "Verifies more tasks than prior tools" | Solved counts on a shared benchmark set vs a tuned baseline, equal timeout | "Evaluated on our own examples only" |
| "Faster / more scalable" | Wall-clock and memory across realistic sizes, hardware stated | "Speedup ratio with no timeout or machine given" |
| "Finds real bugs" | Reproducible counterexamples/witnesses on real code, validated | "Warnings with no confirmed true positives" |
| "Sound (or sound up to k)" | Correctness argument + no incorrect verdicts on a validation set | "Fast because it silently under-approximates" |
| "General technique" | Multiple property classes / languages + stated limits | "One benchmark family, claimed universal" |
Show full SKILL.md (230 more words)Show less
Fair-comparison checklist
[Baseline] strongest competitor, latest version, cited; not a straw man
[Budget] identical timeout and memory limit for every tool; state them
[Hardware] one machine, described; note any parallelism and core counts
[Tasks] a named, shared benchmark set; report per-category, not just totals
[Validation] answers cross-checked / witnesses validated; incorrect results disclosed
[Determinism] fix seeds/options; report variance across repetitions where relevantSV-COMP vs a TACAS tool-paper evaluation
TACAS hosts SV-COMP, but a competition entry and a tool-paper evaluation are different deliverables — do not conflate them:
- SV-COMP runs your verifier on the common task set under the organizers' harness and rules, and reports a ranked, uniform comparison across all participants; your contribution is a short competition paper plus a conforming tool.
- A tool paper is peer-reviewed prose making a specific claim about your tool, evaluated on benchmarks you justify, judged on contribution and a reproducible artifact — not on a leaderboard position. You may use SV-COMP benchmarks in a tool paper, but cite them and keep the comparison fair and reproducible.
Vignette: evaluating a new model checker
Suppose the paper claims a new checker verifies more C tasks than the prior tool. The matching plan: take a shared C benchmark set (with categories), run both tools with an identical timeout and memory limit on one stated machine, report per-category solved/unsolved and wall-clock, validate verdicts (cross-check disagreements, validate violation witnesses), disclose any wrong answers, state which property classes are out of scope, and ship a clean-VM artifact whose scripts regenerate every table.
Reporting floor
- Machine description, timeout, and memory limit for every experiment.
- Per-benchmark or per-category results, not only aggregate totals.
- A soundness/validation statement and honest disclosure of incorrect results.
- Artifact scripts that regenerate each table/figure on the ETAPS VM.
Output format
[Evaluation readiness] strong / adequate / weak
[Claim -> evidence map] <claim: benchmark set / metric / baseline>
[Baseline fairness] <baseline -> latest? equal budget? same hardware? documented?>
[Soundness] <validation method; any incorrect results disclosed? yes/no>
[Reproducibility] <every number regenerates on the clean VM? yes/no>
[Decision-critical next run] <one experiment or validation to add>© 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-experiments of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Tacas Experiments 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 Experiments 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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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 Experiments
What does Tacas Experiments do?
A skill your agent uses when designing or auditing a TACAS (ETAPS) evaluation, covering shared verification benchmarks (SV-COMP-style task sets), fair baseline configuration and equal time budgets…. Tacas Experiments is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when designing or auditing a TACAS (ETAPS) evaluation, covering shared verification benchmarks (SV-COMP-style task sets), fair baseline configuration and equal time budgets, honest wall-clock/scalability reporting on stated hardware, soundness checking of results, reproducibility on the clean artifact VM, and how a TACAS tool-paper evaluation differs from a SV-COMP competition entry.
When should I use Tacas Experiments?
Tacas Experiments fits situations like: auditing a TACAS (ETAPS) evaluation; covering shared verification benchmarks (SV-COMP-style task sets); fair baseline configuration and equal time budgets; honest wall-clock/scalability reporting on stated hardware.
How do I install Tacas Experiments in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill tacas-experiments -a claude-code`. Or copy the skill folder (TACAS-Skills/skills/tacas-experiments in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/tacas-experiments in your project. Claude Code loads it when a task matches its description.
How do I install Tacas Experiments in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill tacas-experiments -a codex`. Or copy the skill folder (TACAS-Skills/skills/tacas-experiments in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/tacas-experiments in your project. Codex loads it when a task matches its description.
Can I use Tacas Experiments 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-experiments -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-experiments, .gemini/skills/tacas-experiments, .github/skills/tacas-experiments and .opencode/skills/tacas-experiments in your project.
What does Tacas Experiments need to run?
SKILL.md names no scripts, command-line tools or credentials: Tacas Experiments is instructions for the agent only.
Does Tacas Experiments 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 Experiments 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 Experiments use?
Tacas Experiments 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 Experiments use?
About 1.4k tokens (SKILL.md is roughly 5.8k 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 Experiments?
Skills that share tags, products or a category with Tacas Experiments: 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 Experiments?
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.