Peer Review
spacering-net/codeg
Structured manuscript/grant review with checklist-based evaluation.
Build and confirm the complete paper, review, constraint, concern, and reviewer-card baseline before rebuttal generation.
$ npx skills add Optima-CityU/LLM4AD_Next --skill rebuttal-baseline -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Optima-CityU/LLM4AD_Next rebuttal-baseline --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/Optima-CityU/LLM4AD_Next.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/autorebuttal/rebuttal-baseline .claude/skills/rebuttal-baseline && 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 "rebuttal-baseline" agent skill from https://github.com/Optima-CityU/LLM4AD_Next/tree/main/skills/autorebuttal/rebuttal-baseline into .claude/skills/rebuttal-baseline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "rebuttal-baseline", 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/Optima-CityU/LLM4AD_Next/tree/main/skills/autorebuttal/rebuttal-baselineType 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 Optima-CityU/LLM4AD_Next --skill rebuttal-baseline -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Optima-CityU/LLM4AD_Next rebuttal-baseline --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Optima-CityU/LLM4AD_Next.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/autorebuttal/rebuttal-baseline .agents/skills/rebuttal-baseline && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "rebuttal-baseline" agent skill from https://github.com/Optima-CityU/LLM4AD_Next/tree/main/skills/autorebuttal/rebuttal-baseline into .agents/skills/rebuttal-baseline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "rebuttal-baseline", 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 Optima-CityU/LLM4AD_Next --skill rebuttal-baseline -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Optima-CityU/LLM4AD_Next rebuttal-baseline --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Optima-CityU/LLM4AD_Next.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/autorebuttal/rebuttal-baseline .cursor/skills/rebuttal-baseline && 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 "rebuttal-baseline" agent skill from https://github.com/Optima-CityU/LLM4AD_Next/tree/main/skills/autorebuttal/rebuttal-baseline into .cursor/skills/rebuttal-baseline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "rebuttal-baseline", 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/Optima-CityU/LLM4AD_Next.git --path skills/autorebuttal/rebuttal-baseline--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 Optima-CityU/LLM4AD_Next --skill rebuttal-baseline -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Optima-CityU/LLM4AD_Next rebuttal-baseline --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Optima-CityU/LLM4AD_Next.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/autorebuttal/rebuttal-baseline .gemini/skills/rebuttal-baseline && 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 "rebuttal-baseline" agent skill from https://github.com/Optima-CityU/LLM4AD_Next/tree/main/skills/autorebuttal/rebuttal-baseline into .gemini/skills/rebuttal-baseline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "rebuttal-baseline", 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 Optima-CityU/LLM4AD_Next rebuttal-baselineInstalls 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 Optima-CityU/LLM4AD_Next --skill rebuttal-baseline -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Optima-CityU/LLM4AD_Next.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/autorebuttal/rebuttal-baseline .github/skills/rebuttal-baseline && 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 "rebuttal-baseline" agent skill from https://github.com/Optima-CityU/LLM4AD_Next/tree/main/skills/autorebuttal/rebuttal-baseline into .github/skills/rebuttal-baseline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "rebuttal-baseline", 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 Optima-CityU/LLM4AD_Next --skill rebuttal-baseline -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Optima-CityU/LLM4AD_Next rebuttal-baseline --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Optima-CityU/LLM4AD_Next.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/autorebuttal/rebuttal-baseline .opencode/skills/rebuttal-baseline && 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 "rebuttal-baseline" agent skill from https://github.com/Optima-CityU/LLM4AD_Next/tree/main/skills/autorebuttal/rebuttal-baseline into .opencode/skills/rebuttal-baseline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "rebuttal-baseline", 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.
rebuttal-baselineBuild and confirm the complete paper, review, constraint, concern, and reviewer-card baseline before rebuttal generation.
Rebuttal Baseline is an agent skill from Optima-CityU/LLM4AD_Next. Build and confirm the complete paper, review, constraint, concern, and reviewer-card baseline before rebuttal generation.
Its SKILL.md is about 920 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 Peer review. The repository describes itself as: A next-generation automatic algorithm design platform, making automated algorithm design more accessible and easier to use. The licence is BSD-3-Clause.
2 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit e3d3f7b. It shows what the files ask for, not the result of running them.
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.
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.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Rebuttal Baseline loads about 915 tokens when it runs. Until then it costs about 35 tokens; SKILL.md has 436 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.
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.
The full file from Optima-CityU/LLM4AD_Next at commit e3d3f7b, republished under its BSD-3-Clause licence (© Optima-CityU). 436 words, ~915 tokens.
.claude/skills/rebuttal-baseline/SKILL.md (or your agent's skills folder).<!-- Adapted from YoujunZhao/AutoRebuttal; see /app/skills/autorebuttal-shared/ATTRIBUTION.md. -->
Read these shared references completely before acting:
/app/skills/autorebuttal-shared/references/input-contract.md/app/skills/autorebuttal-shared/references/reviewer-analysis.md/app/skills/autorebuttal-shared/references/reviewer-model.md/app/skills/autorebuttal-shared/references/rebuttal-playbook.md/app/skills/autorebuttal-shared/references/evidence-policy.md/app/skills/autorebuttal-shared/references/artifact-contracts.mdThis author-facing phase contains two internal steps.
Read the paper entry point and follow relevant includes. Then collect reviews from the available sources:
reviewer_sources item as review_markdown, organized for display with
Markdown headings and lists. Retain the supplied details and do not invent
absent fields. The right-hand reviewer panel displays this Markdown after
baseline publication.Assign one stable reviewer UUID per distinct report. Use the indexed UUID for saved reviews; for a conversation-only report, create a UUID and retain it in the published baseline. Preserve a human-readable reviewer label separately. Do not claim to have read a linked forum unless its review text was supplied.
Normalize the paper summary, stable reviewer UUIDs and display labels, venue, response mode, output format, author notes, forbidden claims, and unresolved questions.
Split every substantive report into atomic W weaknesses, Q questions, and
M minor points. Record stable concern IDs, severity, likely answer source,
response move, and auditable source references. Build exactly one reviewer card
per indexed report and assign every concern to exactly one matching card. Use
the index reviewer_id UUID everywhere; never substitute or derive it from the
human-readable display_label.
Present the compact baseline to the author. Do not draft rebuttal prose, choose a final strategy, edit paper files, or invent venue policy. Missing venue/year, the default response mode or output format, absent numeric limits, and evidence that will require an author placeholder are not generation blockers. Record such items as assumptions, warnings, or open questions and continue.
Only set ready_for_generation false when the source material is unusable for
an evidence-grounded response: the paper has no substantive readable content,
neither the review index nor the conversation supplies a review,
or none of the collected reviews contains a substantive concern. In that case,
identify the exact missing source and required author action. Otherwise publish
the baseline with ready_for_generation true.
Publish the complete Baseline phase contract exactly once with
publish_stage_result and idempotency key rebuttal-baseline-v1.
© Optima-CityU, BSD-3-Clause. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in skills/autorebuttal/rebuttal-baseline of Optima-CityU/LLM4AD_Next.
Open the folder on GitHubat commit e3d3f7b
Rebuttal Baseline 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 |
|---|---|---|---|---|---|---|
| Rebuttal Baseline this skillOptima-CityU/LLM4AD_Next | 574 | — | ~915 | Automated safety check: Pass | BSD-3-Clause | |
| Peer Reviewspacering-net/codeg | 3.9k | 17 repos | ~5.9k | Automated safety check: Notes | MIT | |
| Scholar Evaluationspacering-net/codeg | 3.9k | 11 repos | ~3.2k | Automated safety check: Pass | MIT | |
| Academic Paper Writing PipelineImbad0202/academic-research-skills | 51k | — | ~16k | Automated safety check: Pass | Custom licence | |
| Academic Paper ReviewerImbad0202/academic-research-skills | 51k | — | ~11k | Automated safety check: Pass | Custom licence | |
| Peer ReviewK-Dense-AI/claude-scientific-writer | 2.4k | 2 repos | ~3.1k | Automated safety check: Notes | MIT |
spacering-net/codeg
Structured manuscript/grant review with checklist-based evaluation.
spacering-net/codeg
Systematically evaluate scholarly work using the ScholarEval framework, providing structured assessment across research quality dimensions including problem formulation, methodology, analysis, and…
Imbad0202/academic-research-skills
Runs a 12-agent pipeline that plans, drafts, cites, reviews and formats academic papers, with modes for revision, rebuttals, abstracts and citation checks.
Imbad0202/academic-research-skills
Simulates a journal peer review of a manuscript with a five-seat reviewer panel, an editorial synthesizer and several review modes.
K-Dense-AI/claude-scientific-writer
Prepare evidence-bounded, constructive peer-review drafts and structured manuscript assessments.
Imbad0202/academic-research-skills
Orchestrates a ten-stage academic workflow from research to finished manuscript, including integrity checks, two rounds of peer review and revision.
Optima-CityU/LLM4AD_Next
A skill your agent uses when establishing a research proposal's project foundation, submission constraints, and presentation system before section drafting begins.
Optima-CityU/LLM4AD_Next
A skill your agent uses when a user wants to build an LLM4ADNext task package — a runnable directory that lets the LLM4AD platform evolve an algorithm for their problem.
Optima-CityU/LLM4AD_Next
Organize one or more Markdown source documents into high-fidelity, editable knowledge blocks.
Optima-CityU/LLM4AD_Next
A skill your agent uses when assembling a completed staged Typst proposal and checking its evidence, logic, citations, structure, and export readiness.
Optima-CityU/LLM4AD_Next
A skill your agent uses when documenting a proposal's research foundation, available conditions, team support, feasibility, and risk controls from author-supplied facts.
Optima-CityU/LLM4AD_Next
A skill your agent uses when distilling a proposal's innovations and defining milestones, annual plans, contingency points, and expected outcomes.
Categories
Build and confirm the complete paper, review, constraint, concern, and reviewer-card baseline before rebuttal generation. Rebuttal Baseline is an agent skill from Optima-CityU/LLM4AD_Next. Build and confirm the complete paper, review, constraint, concern, and reviewer-card baseline before rebuttal generation.
Rebuttal Baseline fits situations like: tasks that involve Peer review.
Run `npx skills add Optima-CityU/LLM4AD_Next --skill rebuttal-baseline -a claude-code`. Or copy the skill folder (skills/autorebuttal/rebuttal-baseline in Optima-CityU/LLM4AD_Next) into .claude/skills/rebuttal-baseline in your project. Claude Code loads it when a task matches its description.
Run `npx skills add Optima-CityU/LLM4AD_Next --skill rebuttal-baseline -a codex`. Or copy the skill folder (skills/autorebuttal/rebuttal-baseline in Optima-CityU/LLM4AD_Next) into .agents/skills/rebuttal-baseline in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Optima-CityU/LLM4AD_Next --skill rebuttal-baseline -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/rebuttal-baseline, .gemini/skills/rebuttal-baseline, .github/skills/rebuttal-baseline and .opencode/skills/rebuttal-baseline in your project.
SKILL.md names no scripts, command-line tools or credentials: Rebuttal Baseline is instructions for the agent only.
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.
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.
Rebuttal Baseline is published under the BSD-3-Clause licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 915 tokens (SKILL.md is roughly 3.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Rebuttal Baseline: Peer Review (spacering-net/codeg, 3.9k stars), Scholar Evaluation (spacering-net/codeg, 3.9k stars), Academic Paper Writing Pipeline (Imbad0202/academic-research-skills, 51k stars) and Academic Paper Reviewer (Imbad0202/academic-research-skills, 51k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Optima-CityU (a GitHub organization) maintains it in Optima-CityU/LLM4AD_Next, which has 574 GitHub stars. The repository holds 24 skills in this directory. The repository was last updated on October 9, 2026.
Source: Optima-CityU/LLM4AD_Next on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.