empiricalwiki: Skill for Claude Code

.claude/skills/rebuttal/SKILL.md

rebuttal is a skill for Claude Code from Lambenthan/empiricalwiki. It costs 38 tokens per session (4,030 once invoked), scanned A, original, MIT.

A workflow for turning peer-review comments into separate concerns, linking them to claims in a research wiki, checking supporting evidence, and drafting a response. A rebuttal is the formal reply authors send to reviewers.

In plain words
What is it for?
Use it to analyse review files, test likely follow-up questions, and produce formal or richly linked rebuttal drafts.
Why use it?
It reduces the chance of missing a reviewer’s point or making a claim that the available experiments do not support.

Skill for Claude Code

Written for Claude Code: argument-hint in frontmatter. Also seen: reads .claude/ paths; mentions Claude Code.

This is Lambenthan/empiricalwiki's own configuration. It tells Claude Code how to work on empiricalwiki itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything empiricalwiki configures →

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is python3 tools/research_wiki.py log wiki/ \.

Reuse

Borrowing it

Nothing to install: this file belongs to Lambenthan/empiricalwiki. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/Lambenthan/empiricalwiki/main/.claude/skills/rebuttal/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/Lambenthan/empiricalwiki

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/lambenthan/empiricalwiki/rebuttal/github.svg)](https://agentmods.dev/skills/lambenthan/empiricalwiki/rebuttal)
Your own site
<a href="https://agentmods.dev/skills/lambenthan/empiricalwiki/rebuttal"><img src="https://agentmods.dev/badge/skills/lambenthan/empiricalwiki/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/lambenthan/empiricalwiki/rebuttal"><img src="https://agentmods.dev/badge/skills/lambenthan/empiricalwiki/rebuttal.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 38 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,030 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00038 $0.04030
Opus 5 $0.00019 $0.02015
Sonnet 5 $0.00008 $0.00806
Haiku 4.5 $0.00004 $0.00403

Measured 11d ago against content hash 5553d59ae337, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, 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 11d 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.

.claude/skills/rebuttal/SKILL.md · 344 lines

How it starts

The opening of the file, as written. The whole thing — 344 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/rebuttal

解析审稿意见,将每条 concern 原子化(Rvx-Cy 编号)并映射到 wiki claim, 检查 evidence 是否充分(追溯到 wiki experiments), 用 Review LLM 模拟审稿人追问(stress-test,评分 1-5),生成正式版(纯文本)和富文本版 rebuttal。 安全检查确保 no fabrication, no overpromise, full coverage。

Inputs

  • review:审稿意见来源,以下之一:
    • 文件路径(如 raw/reviews/reviewer1.txtraw/reviews/meta-review.md
    • 多个文件路径(逗号分隔:raw/reviews/R1.txt,raw/reviews/R2.txt,raw/reviews/R3.txt
    • 直接粘贴的审稿文本
  • --paper-slug(可选):关联论文在 wiki/outputs/ 中的 slug,用于定位 PAPER_PLAN
  • --venue(可选):目标会议/期刊(ICLR / NeurIPS / ICML / ACL / CVPR),影响 rebuttal 格式和字数限制
  • --stress-test(可选,默认开启):Review LLM 模拟审稿人追问,关闭用 --no-stress-test
  • --format(可选,默认 formal):输出格式
    • formal:正式 rebuttal 纯文本版(适合直接粘贴到 submission system)
    • rich:富文本版(含 wiki [[links]]、详细分析、改进计划)

Outputs

  • wiki/outputs/rebuttal-{slug}.md — 富文本版 rebuttal(含 [[wikilinks]]、evidence 追溯、分析表格)
  • wiki/outputs/rebuttal-{slug}.txt — 正式版 rebuttal(plain text,适合 submission system 粘贴)
  • wiki/claims/*.md — 若 concern 暴露 evidence gap,在 ## Open questions 追加建议
  • wiki/log.md — 追加日志

Wiki Interaction

Reads

  • wiki/claims/*.md — 映射 concerns 到 claims,检查 evidence 充分性
  • wiki/experiments/*.md — 查找支持 claim 的实验 result
  • wiki/papers/*.md — 查找引用的论文上下文
  • wiki/concepts/*.md — 理解 method 相关 concerns 的概念背景
  • wiki/ideas/*.md — 查找 idea 的 motivation 和 pilot results
  • wiki/outputs/PAPER_PLAN.md — 了解论文结构(来自 /paper-plan,若有 --paper-slug)
  • wiki/graph/context_brief.md — 全局上下文
  • wiki/graph/edges.jsonl — claim-experiment-paper 关系
  • .claude/skills/shared-references/cross-model-review.md — Review LLM stress-test 独立性

Writes

  • wiki/outputs/rebuttal-{slug}.md — 富文本版
  • wiki/outputs/rebuttal-{slug}.txt — formal 纯文本版
  • wiki/claims/*.md — 在 ## Open questions 追加 reviewer 发现的 gap(不直接修改 confidence/status,仅建议)
  • wiki/log.md — 追加日志

Graph edges created

  • 无新 edges(rebuttal 是查询操作,不修改知识图谱)

Workflow

前置

  1. 确认工作目录为 wiki 项目根(包含 wiki/raw/tools/ 的目录)
  2. 读取 cross-model-review.md 确认 stress-test 独立性原则
  3. 生成 slug:python3 tools/research_wiki.py slug "{paper-slug}-rebuttal"

Read the full file on GitHub · 344 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. 11d ago First seen · 344 lines · 38 tokens per session scan A 5553d59ae337

Subscribe to this mod's changes

rebuttal is a skill published in the GitHub repository Lambenthan/empiricalwiki (83 stars, last pushed 3mo ago), licensed MIT. It adds 38 tokens to every session and 4,030 once invoked, about $0.0002 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 2026-08-30.

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