Agent skill

Rebuttal Baseline

by Optima-CityU in Optima-CityU/LLM4AD_Next

Build and confirm the complete paper, review, constraint, concern, and reviewer-card baseline before rebuttal generation.

BSD-3-ClauseAuto-check passedResearch & Science

Install Rebuttal Baseline

skills CLI
$ npx skills add Optima-CityU/LLM4AD_Next --skill rebuttal-baseline -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Optima-CityU/LLM4AD_Next rebuttal-baseline --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ 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-src

Use ~/.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/

Facts

Skill name
rebuttal-baseline
GitHub stars
574
Token cost
~915 tokens
SKILL.md length
436 words
Files
1
Skills in repo
24
Repo updated
First seen
Licence
BSD-3-Clause

At a glance

Build and confirm the complete paper, review, constraint, concern, and reviewer-card baseline before rebuttal generation.

  • Works in 2 steps: Intake → Review analysis
  • Tasks that involve Peer review
  • SKILL.md covers Step 1: Intake and Step 2: Review analysis
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

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.

When your agent uses it

  • Tasks that involve Peer review

Example prompts

  • “/rebuttal-baseline”

Workflow steps

2 steps, taken from the step headings in SKILL.md.

  1. Intake
  2. Review analysis

What it can do on your machine

Read from SKILL.md and the folder at commit e3d3f7b. 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

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.

Always · name and description, kept in context so the agent knows when to use it
~35
When it runs · the whole SKILL.md, loaded when a task matches
~915

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 Optima-CityU/LLM4AD_Next at commit e3d3f7b, republished under its BSD-3-Clause licence (© Optima-CityU). 436 words, ~915 tokens.

Download SKILL.mdSave it as .claude/skills/rebuttal-baseline/SKILL.md (or your agent's skills folder).
name
rebuttal-baseline
description
Build and confirm the complete paper, review, constraint, concern, and reviewer-card baseline before rebuttal generation.
<!-- Adapted from YoujunZhao/AutoRebuttal; see /app/skills/autorebuttal-shared/ATTRIBUTION.md. -->

Rebuttal Baseline

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.md

This author-facing phase contains two internal steps.

Step 1: Intake

Read the paper entry point and follow relevant includes. Then collect reviews from the available sources:

  1. Read every report in the review index when it is non-empty.
  2. Read any review text the author pasted into the conversation, including separately labeled reports in one message. Preserve each distinct conversation-only report in the corresponding 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.
  3. Merge matching reports from these sources without dropping reviewer-specific details. A forum URL alone is not review text; ask the author to paste the report or enter it in the right-hand review panel.
  4. If neither source contains a review, ask the author to paste one into the conversation or enter it in the review panel.

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.

Show full SKILL.md (196 more words)Show less

Step 2: Review analysis

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

Files

Just SKILL.md in skills/autorebuttal/rebuttal-baseline of Optima-CityU/LLM4AD_Next.

Open the folder on GitHubat commit e3d3f7b

Compare with similar skills

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.

Rebuttal Baseline compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Rebuttal Baseline this skillOptima-CityU/LLM4AD_Next574—~915Automated safety check: PassBSD-3-Clause
Peer Reviewspacering-net/codeg3.9k17 repos~5.9kAutomated safety check: NotesMIT
Scholar Evaluationspacering-net/codeg3.9k11 repos~3.2kAutomated safety check: PassMIT
Academic Paper Writing PipelineImbad0202/academic-research-skills51k—~16kAutomated safety check: PassCustom licence
Academic Paper ReviewerImbad0202/academic-research-skills51k—~11kAutomated safety check: PassCustom licence
Peer ReviewK-Dense-AI/claude-scientific-writer2.4k2 repos~3.1kAutomated safety check: NotesMIT

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Questions about Rebuttal Baseline

What does Rebuttal Baseline do?

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.

When should I use Rebuttal Baseline?

Rebuttal Baseline fits situations like: tasks that involve Peer review.

How do I install Rebuttal Baseline in Claude Code?

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.

How do I install Rebuttal Baseline in Codex?

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.

Can I use Rebuttal Baseline 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 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.

What does Rebuttal Baseline need to run?

SKILL.md names no scripts, command-line tools or credentials: Rebuttal Baseline is instructions for the agent only.

Does Rebuttal Baseline 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 Rebuttal Baseline 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 Rebuttal Baseline use?

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.

How many tokens does Rebuttal Baseline use?

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.

What are the alternatives to Rebuttal Baseline?

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.

Who maintains Rebuttal Baseline?

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.