skills/42-wanshuiyin-ARIS/skills/skills-codex/rebuttal/SKILL.md
Workflow 4: Submission rebuttal pipeline. Parses external reviews, enforces coverage and grounding, drafts a safe text-only rebuttal under venue limits, and manages follow-up rounds.
npx skillsauth add brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research rebuttalInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Prepare and maintain a grounded, venue-compliant rebuttal for: $ARGUMENTS
This skill is optimized for:
This skill does not:
AUTO_EXPERIMENT = trueWorkflow 1: idea-discovery
Workflow 1.5: experiment-bridge
Workflow 2: auto-review-loop (pre-submission)
Workflow 3: paper-writing
Workflow 4: rebuttal (post-submission external reviews)
ICML — Default venueTEXT_ONLY — v1 defaultgpt-5.4 — Used via a secondary Codex agent for internal stress-testingtrue, invoke /experiment-bridge for reviewer concerns that require new evidencetrue, only run Phase 0-3 and stop after strategyrebuttal/Override:
/rebuttal "paper/" — venue: NeurIPS, character limit: 5000
If venue rules or limit are missing, stop and ask before drafting.
Three hard gates. If any fails, do not finalize:
rebuttal/REBUTTAL_STATE.md exists, resume from the recorded phaserebuttal/ and initialize the output documentsrebuttal/REVIEWS_RAW.md verbatimrebuttal/REBUTTAL_STATE.mdCreate rebuttal/ISSUE_BOARD.md.
For each atomic concern, record:
issue_idreviewer, round, raw_anchorissue_typeseverityreviewer_stanceresponse_modestatusCreate rebuttal/STRATEGY_PLAN.md.
QUICK_MODE exit: if QUICK_MODE = true, stop here and present ISSUE_BOARD.md + STRATEGY_PLAN.md.
Skip entirely if AUTO_EXPERIMENT is false.
If the strategy plan identifies issues that require new empirical evidence:
/experiment-bridge "rebuttal/REBUTTAL_EXPERIMENT_PLAN.md"ISSUE_BOARD.mdnarrow_concession or future_work_boundaryrebuttal/REBUTTAL_EXPERIMENTS.mdCreate rebuttal/REBUTTAL_DRAFT_v1.md.
Structure:
Also generate rebuttal/PASTE_READY.txt with exact character count.
Run all lints:
spawn_agent:
model: gpt-5.4
reasoning_effort: xhigh
message: |
Stress-test this rebuttal draft:
[raw reviews + issue board + draft + venue rules]
1. Unanswered or weakly answered concerns?
2. Unsupported factual statements?
3. Risky or unapproved promises?
4. Tone problems?
5. Paragraph most likely to backfire with a meta-reviewer?
6. Minimal grounded fixes only. Do not invent evidence.
Verdict: safe to submit / needs revision
Save the full response to rebuttal/MCP_STRESS_TEST.md. If a hard safety blocker remains, revise before finalizing.
Produce:
rebuttal/PASTE_READY.txt — strict version, ready to pasterebuttal/REBUTTAL_DRAFT_rich.md — extended version with optional sections markedrebuttal/REBUTTAL_STATE.mdWhen new reviewer comments arrive:
rebuttal/FOLLOWUP_LOG.mdsend_inputtools
Autonomous multi-round research review loop using MiniMax API. Use when you want to use MiniMax instead of Codex MCP for external review. Trigger with "auto review loop minimax" or "minimax review".
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Autonomous research review loop using any OpenAI-compatible LLM API. Configure via llm-chat MCP server or environment variables. Trigger with "auto review loop llm" or "llm review".
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Autonomous multi-round research review loop using MiniMax API. Use when you want to use MiniMax instead of Codex MCP for external review. Trigger with "auto review loop minimax" or "minimax review".
tools
Autonomous research review loop using any OpenAI-compatible LLM API. Configure via llm-chat MCP server or environment variables. Trigger with "auto review loop llm" or "llm review".