rebuttal

rebuttal is a skill for Claude Code from wanshuiyin/Auto-claude-code-research-in-sleep. It costs 73 tokens per session (5,863 once invoked), scanned A, original, MIT.

A workflow for answering external reviews of a submitted research paper. It turns reviewer comments into a grounded response that follows the venue's limits.

In plain words
What is it for?
Use it to draft rebuttals for venues such as ICML or OpenReview and manage later reviewer-response rounds.
Why use it?
It helps researchers address every criticism without inventing results or promising unsupported changes.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: mentions Codex.

Good fit Use it to draft rebuttals for venues such as ICML or OpenReview and manage later reviewer-response rounds.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/wanshuiyin/auto-claude-code-research-in-sleep/rebuttal
About the project

ARIS is a collection of Markdown-based skills that define a workflow for autonomous machine-learning research, including idea discovery, experiment automation, and review loops. Researchers and AI coding agents use it across tools such as Claude Code, Codex, Cursor, and OpenClaw without depending on a single framework. The catalogue entries are ARIS workflow skills and agents.

wanshuiyin/Auto-claude-code-research-in-sleep · 16,030 stars · on GitHub

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill rebuttal
Clone the repo
git clone --depth 1 https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for rebuttal

README.md
[![agentmods](https://agentmods.dev/badge/skills/wanshuiyin/auto-claude-code-research-in-sleep/rebuttal/github.svg)](https://agentmods.dev/skills/wanshuiyin/auto-claude-code-research-in-sleep/rebuttal)
Your own site
<a href="https://agentmods.dev/skills/wanshuiyin/auto-claude-code-research-in-sleep/rebuttal"><img src="https://agentmods.dev/badge/skills/wanshuiyin/auto-claude-code-research-in-sleep/rebuttal/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for rebuttal

Your own site · 80×15
<a href="https://agentmods.dev/skills/wanshuiyin/auto-claude-code-research-in-sleep/rebuttal"><img src="https://agentmods.dev/badge/skills/wanshuiyin/auto-claude-code-research-in-sleep/rebuttal.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 73 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 5,863 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Socket pass 18 May 2026
  • Snyk warn 18 May 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00073 $0.05863
Opus 5 $0.00036 $0.02932
Sonnet 5 $0.00015 $0.01173
Haiku 4.5 $0.00007 $0.00586

Measured 5d ago against content hash 36b9f570181c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

rebuttal scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/rebuttal/SKILL.md · 377 lines

How it starts

The opening of the file, as written. The whole thing — 377 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Workflow 4: Rebuttal

Prepare and maintain a grounded, venue-compliant rebuttal for: $ARGUMENTS

Scope

This skill is optimized for:

  • text-only rebuttal under strict character/word limits (e.g. ICML single-document)
  • per-reviewer thread responses where each reviewer renders independently (e.g. OpenReview-style)
  • multiple reviewers with shared and reviewer-specific concerns
  • follow-up rounds after the initial rebuttal
  • safe drafting with no fabrication, no overpromise, and full issue coverage

This skill does not:

  • run new experiments automatically
  • generate new theorem claims automatically
  • edit or upload a revised PDF
  • submit to OpenReview / CMT / HotCRP

If the user already has new results, derivations, or approved commitments, the skill can incorporate them as user-confirmed evidence.

Lifecycle Position

Workflow 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)

Constants

  • VENUE = ICML — Default venue. Override if needed.
  • RESPONSE_MODE = TEXT_ONLY — v1 default.
  • REVIEWER_MODEL = gpt-6-astra — Default model for the Codex backend. Used for internal stress-testing. Manual backend uses a model the user chooses — it must be a recognized model from a different family (OpenAI, Anthropic, Google, DeepSeek, Moonshot/Kimi, Qwen).
  • REVIEWER_BACKEND = codex — Default: Codex MCP (xhigh). Override with — reviewer: oracle-pro for Oracle MCP, or — reviewer: manual for Manual Review MCP. If manual-review MCP is unavailable, stop and print the install command; do not fall back to Codex. See shared-references/reviewer-routing.md.
  • MAX_INTERNAL_DRAFT_ROUNDS = 2 — draft → lint → revise.
  • VENUE_MODE = single_documentsingle_document for one shared author response, or per_reviewer_thread when each reviewer thread renders independently. Confirm the venue/interface before drafting if unclear. Affects Phase 4/7 output shape.
  • STRESS_TEST_ROUNDS_BASE = 1 — One external reviewer critique round on the full response set. Add focused rounds for reviewer_priority: pivotal responses, terminating when the reviewer returns no new substantive issues. Hard cap at 5.
  • MAX_FOLLOWUP_ROUNDS = 3 — per reviewer thread.
  • AUTO_EXPERIMENT = false — When true, automatically invoke /experiment-bridge to run supplementary experiments when the strategy plan identifies reviewer concerns that require new empirical evidence. When false (default), pause and present the evidence gap to the user for manual handling.
  • QUICK_MODE = false — When true, only run Phase 0-3 (parse reviews, atomize concerns, build strategy). Outputs ISSUE_BOARD.md + STRATEGY_PLAN.md and stops — no drafting, no stress test. Useful for quickly understanding what reviewers want before deciding how to respond.
  • REBUTTAL_DIR = rebuttal/
  • RENDER_HTML = true — When true (default), auto-render rebuttal/REBUTTAL_DRAFT_rich.md (the detailed reviewer-facing draft) to HTML after Phase 6 / Phase 8 finalization. Uses full Codex review gate (final pre-submission deliverable — reviewer-facing content, render fidelity matters). The plain-text PASTE_READY.txt is NOT rendered (it's character-counted plain text by design). Set false to skip, or pass — render html: false.

Read the full file on GitHub · 377 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 5d ago Changed 36b9f570181c
  2. 9d ago First seen · 377 lines · 73 tokens per session scan A e8d30a41aa66

Subscribe to this mod's changes

rebuttal is a skill published in the GitHub repository wanshuiyin/Auto-claude-code-research-in-sleep (16,030 stars, last pushed yesterday), licensed MIT. It adds 73 tokens to every session and 5,863 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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