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- brycewang-stanford/Auto-Empirical-Research-Skills
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- 2026年4月3日 02:07
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安装方式
默认使用会先检查来源的 Prompt;你也可以切换为直接命令,或下载本地副本。
检查来源文件
决定是否安装前,请先阅读 SKILL.md,以及 SkillsMP 当前展示的配套文件。
菜单
默认使用会先检查来源的 Prompt;你也可以切换为直接命令,或下载本地副本。
决定是否安装前,请先阅读 SKILL.md,以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills --skill rebuttal-writing-guide命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
Route empirical-research requests through the Auto-Empirical Research Skills catalog when this whole repository is installed as one skill in Codex, CodeBuddy, Claude Code, or another IDE. Use to choose and load the right vendored AERS skill for causal inference, econometrics, replication, data acquisition, manuscript writing, peer review and referee responses, citation checking, de-AIGC editing, or full empirical-paper workflows without reading the entire repository at once.
中英双语学术降 AIGC / bilingual academic de-AIGC skill. Removes AI-generated writing signatures from empirical papers in economics, management, and the social sciences — in both English and Chinese. Covers Turnitin AI, GPTZero, Originality.ai on the English side and 知网 AMLC, 万方, 维普 on the Chinese side. Uses a six-step loop (intake → audit → claim-evidence check → differentiated rewrite → five-dimension self-score → cold-reader recheck) with two pattern libraries (22 English + 17 Chinese patterns), section-by-section strategies for empirical papers, and hard protections that keep every number, coefficient, and citation intact.
Use when a research task needs reproducible Kaggle discovery, metadata inspection, bounded public-data downloads, competition or kernel discovery, model discovery, or an explicitly approved Kaggle write/delete operation through the official CLI.
基于 SOC 职业分类
正在显示 SKILL.md
| name | rebuttal-writing-guide |
| description | Write effective rebuttals to reviewer comments for journal submissions |
| metadata | {"openclaw":{"emoji":"📝","category":"research","subcategory":"paper-review","keywords":["rebuttal letter","reviewer response","revision","peer review","manuscript revision","author response"],"source":"wentor-research-plugins"}} |
A skill for writing effective, professional responses to reviewer comments during the peer review revision process. Covers response letter structure, strategies for addressing criticism constructively, handling unfair reviews, and organizing major revisions.
Response Letter Template:
Dear Editor and Reviewers,
Thank you for your thoughtful review of our manuscript
"[Title]" (Manuscript ID: [ID]). We appreciate the
constructive feedback and have carefully addressed all
comments. Below, we provide point-by-point responses.
Major changes include:
- [Summary of change 1]
- [Summary of change 2]
- [Summary of change 3]
In the revised manuscript, all changes are highlighted in blue.
---
RESPONSE TO REVIEWER 1
Comment R1.1: [Exact quote of reviewer comment]
Response: [Your response]
Changes made: [Description of what was changed and where]
---
Comment R1.2: [Next comment]
...
RESPONSE TO REVIEWER 2
...
def format_response(reviewer_num: int, comment_num: int,
comment: str, response: str,
changes: str = None) -> str:
"""
Format a single reviewer response entry.
Args:
reviewer_num: Reviewer number (1, 2, 3...)
comment_num: Comment number within this reviewer
comment: The reviewer's original comment (verbatim)
response: Your response
changes: Description of manuscript changes made
"""
entry = (
f"**Comment R{reviewer_num}.{comment_num}:**\n"
f"*{comment}*\n\n"
f"**Response:**\n{response}\n"
)
if changes:
entry += f"\n**Changes made:** {changes}\n"
return entry
Agreement (easiest -- just do it):
Reviewer: "Table 2 should include confidence intervals."
Response: "We agree. We have added 95% confidence intervals to
Table 2 (see revised manuscript, p. 12)."
Partial agreement (do what you can, explain what you cannot):
Reviewer: "The authors should include 5 additional control variables."
Response: "We appreciate this suggestion. We have added controls for
age and income, which are theoretically motivated (p. 15).
We could not include education, occupation, and region
because [specific reason]. However, we now discuss this
limitation in Section 5.2."
Respectful disagreement (provide evidence):
Reviewer: "The sample is too small to draw any conclusions."
Response: "We understand this concern. However, our power analysis
(now included as Supplementary Table S1) shows that our
sample of N=85 provides 80% power to detect a medium
effect (d=0.5) at alpha=0.05. Furthermore, our primary
effect sizes were large (d=0.8-1.2), well above the
detectable threshold. We have added this justification
to Section 3.1 (p. 8)."
DO:
- Thank reviewers (sincerely, not sarcastically)
- Address EVERY comment, even minor ones
- Quote the reviewer's comment verbatim before responding
- Be specific about what changed and where (page/section numbers)
- Provide evidence for disagreements (citations, analyses, data)
- Run additional analyses when requested if feasible
- Use a respectful, professional tone throughout
- Keep responses concise but thorough
DO NOT:
- Ignore any comment (even if trivial)
- Be defensive or dismissive
- Argue from authority ("We are experts in this area")
- Lie about changes you did not actually make
- Attack the reviewer's competence
- Submit essentially the same manuscript with a new cover letter
Situation: The reviewer misunderstood your method.
Strategy: Clarify without blaming the reviewer.
Bad: "The reviewer clearly did not read our paper carefully."
Good: "We appreciate this comment and recognize that our
description of the method may not have been sufficiently
clear. We have rewritten Section 3.2 to clarify that
[explanation]. The key distinction is [point], which we
now make explicit on p. 10."
Situation: The reviewer asks for data you do not have.
Strategy: Acknowledge, explain constraints, offer alternatives.
Response: "This is an excellent suggestion that would strengthen
the study. Unfortunately, our dataset does not include
[variable] because [reason]. As an alternative, we have
[what you did instead]. We have also added this as a
limitation and future direction (Section 5.3, p. 18)."
1. Read ALL reviews completely before making any changes
2. Create a spreadsheet categorizing each comment:
- Reviewer, comment number, category, difficulty, action
3. Address easy changes first (typos, formatting, missing refs)
4. Tackle substantive comments in order of importance
5. Run any new analyses requested by reviewers
6. Revise the manuscript with tracked changes
7. Write the response letter point by point
8. Have a co-author review both the response and revised manuscript
9. Submit within the deadline (ask for extension if needed)
The cover letter to the editor should briefly summarize the major changes, highlight the most significant improvements, and note any disagreements with reviewers that you would like the editor to adjudicate. Keep it to one page. The detailed point-by-point responses belong in the separate response document, not the cover letter.