A workflow for preparing written replies to external academic reviews. It organizes reviewer concerns and drafts a response while keeping claims tied to available evidence and submission limits.

Use it to prepare rebuttals for venues such as ICML or review systems such as OpenReview, including replies to multiple reviewers.

It helps ensure every issue is addressed without inventing results or making promises that the evidence cannot support.

rebuttal — Skill for Claude Code by raja21068

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 raja21068/AutoResearch --skill rebuttal

Clone the repo

git clone --depth 1 https://github.com/raja21068/AutoResearch

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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/raja21068/autoresearch/rebuttal/github.svg)](https://agentmods.dev/skills/raja21068/autoresearch/rebuttal)

Your own site

<a href="https://agentmods.dev/skills/raja21068/autoresearch/rebuttal"><img src="https://agentmods.dev/badge/skills/raja21068/autoresearch/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/raja21068/autoresearch/rebuttal"><img src="https://agentmods.dev/badge/skills/raja21068/autoresearch/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 4,953 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.

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.

Model	Per session	Once invoked
Fable 5.1	$0.00073	$0.04953
Opus 5	$0.00036	$0.02476
Sonnet 5	$0.00015	$0.00991
Haiku 4.5	$0.00007	$0.00495

Measured 7d ago against content hash 5ce7fda445eb, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, 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 7d 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/aris/rebuttal/SKILL.md · 327 lines

How it starts

The opening of the file, as written. The whole thing — 327 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-5.4 — Used via Codex MCP for internal stress-testing.
REVIEWER_BACKEND = codex — Default: Codex MCP (xhigh). Override with — reviewer: oracle-pro for GPT-5.4 Pro via Oracle MCP. See shared-references/reviewer-routing.md.
MAX_INTERNAL_DRAFT_ROUNDS = 2 — draft → lint → revise.
VENUE_MODE = single_document — single_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 Codex MCP critique round on the full response set. Add focused rounds for reviewer_priority: pivotal responses, terminating when Codex 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/

Read the full file on GitHub · 327 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.

7d ago First seen · 327 lines · 73 tokens per session scan A 5ce7fda445eb

Subscribe to this mod's changes

rebuttal is a skill published in the GitHub repository raja21068/AutoResearch (2 stars, last pushed 3mo ago), licensed MIT. It adds 73 tokens to every session and 4,953 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.

Claude Code Research Writing and docs agentic-ai anthropic antigravity arvix automated-paper-writing

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paper-orchestra

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section-writing-agent

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outline-agent

Step 1 of the PaperOrchestra pipeline (arXiv:2604.05018). Convert (idea.md, experimentallog.md, template.tex, conferenceguidelines.md) into a strict JSON outline containing a plotting plan, literature search plan (Intro + Related Work), and section-level writing plan with citation hints. TRIGGER when the orchestrator…

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