技能详情(站内镜像,无评论)
作者:AIpoch @AIPOCH-AI
许可证:MIT-0
MIT-0 ·免费使用、修改和重新分发。无需归因。
版本:v1.0.0
统计:⭐ 0 · 250 · 0 current installs · 0 all-time installs
⭐ 0
安装量(当前) 0
🛡 VirusTotal :可疑 · OpenClaw :良性
Package:aipoch-ai/peer-review-response-drafter
安全扫描(ClawHub)
- VirusTotal :可疑
- OpenClaw :良性
OpenClaw 评估
The skill's code, instructions, and requirements align with its stated purpose (drafting peer-review response letters); there are no unexplained permissions, external endpoints, or credential requests.
目的
Name and description (drafting peer-review responses) match the included materials (SKILL.md, templates) and the bundled script (scripts/main.py). No unrelated credentials, binaries, or config paths are requested.
说明范围
SKILL.md describes parsing reviewer comments, drafting responses, and tone adjustments; the instructions and parameters (interactive mode, input-file, tone, format) stay within that scope. The skill expects input text/files from the user but does not instruct reading unrelated system files or accessing external services.
安装机制
No install spec is provided (instruction-only with an included helper script). This is the lowest-risk pattern; the bundled Python script and small requirements.txt are proportional to the task. There are no downloads from remote URLs or archive extraction steps.
证书
The skill requests no environment variables, credentials, or config paths. The requirement list is empty and the code shown contains no network calls or credential access. Input comes from user-provided files/strings, which is appropriate for this purpose.
持久
Flags are default (always:false, disable-model-invocation:false). The skill does not request permanent presence or escalate privileges, nor does it modify other skills or system-wide settings.
综合结论
This skill appears coherent and limited to drafting responses. Before installing or using it, consider: 1) privacy—you will likely paste or upload unpublished manuscript text and reviewer comments, so avoid supplying sensitive or embargoed data to third parties or shared environments; 2) execution context—the included Python script runs locally in the agent environment, so review the script if you run it outside a sandbox; 3) trust—if you inte…
安装(复制给龙虾 AI)
将下方整段复制到龙虾中文库对话中,由龙虾按 SKILL.md 完成安装。
请把本段交给龙虾中文库(龙虾 AI)执行:为本机安装 OpenClaw 技能「Peer Review Response Drafter」。简介:Assist in drafting professional peer review response letters. Trigger when user…。
请 fetch 以下地址读取 SKILL.md 并按文档完成安装:https://raw.githubusercontent.com/openclaw/skills/refs/heads/main/skills/aipoch-ai/peer-review-response-drafter/SKILL.md
(来源:yingzhi8.cn 技能库)
SKILL.md
---
name: peer-review-response-drafter
description: Assist in drafting professional peer review response letters. Trigger
when user mentions "reviewer comments", "response letter", "peer review", "revise
and resubmit", "R&R", "reviewer feedback", or needs help responding to academic
journal reviewers.
version: 1.0.0
category: Research
tags: []
author: AIPOCH
license: MIT
status: Draft
risk_level: Medium
skill_type: Tool/Script
owner: AIPOCH
reviewer: ''
last_updated: '2026-02-06'
---
# Peer Review Response Drafter
Assist researchers in crafting professional, polite, and effective responses to peer reviewer comments for academic journal submissions.
## Overview
This skill parses reviewer comments, drafts structured responses, and adjusts tone to ensure:
- Professional and courteous language
- Clear point-by-point addressing of concerns
- Constructive framing of disagreements
- Consistent academic writing style
## When to Use
- Responding to peer reviewer comments after paper revision
- Preparing author response letters for journal resubmission
- Addressing major/minor revision requirements
- Drafting rebuttal letters for conference submissions
- Converting informal notes into formal response language
## Workflow
### Step 1: Parse Input
Collect and structure the following:
- **Reviewer comments**: Original text from reviewers (often numbered/sectioned)
- **Manuscript context**: Title, journal name, revision round (if applicable)
- **Author changes**: Brief notes on what was modified in response to each comment
- **Tone preference**: Formal academic / diplomatic / assertive (default: diplomatic)
### Step 2: Structure Response Letter
Standard academic response letter format:
```
Dear Editor and Reviewers,
Thank you for your constructive feedback on our manuscript titled
"[Title]" submitted to [Journal]. We have carefully addressed all
comments and revised the manuscript accordingly. Below is our
point-by-point response to each reviewer's comments.
Reviewer #1:
[Numbered responses]
Reviewer #2:
[Numbered responses]
...
Sincerely,
[Authors]
```
### Step 3: Draft Individual Responses
For each reviewer comment, generate a response containing:
1. **Acknowledgment**: Thank the reviewer for the observation
2. **Action taken**: Describe the change made (if applicable)
3. **Location indicator**: Page/line number where change appears
4. **Optional rationale**: Brief explanation if no change was made
#### Response Templates
**Accepting a suggestion:**
```
Comment: The methodology section lacks detail on data preprocessing.
Response: We thank the reviewer for this important observation.
We have expanded the methodology section to include detailed
descriptions of data preprocessing steps, including normalization,
outlier removal, and feature selection procedures (Page 5, Lines 120-135).
```
**Partial acceptance with modification:**
```
Comment: The authors should use Method X instead of Method Y.
Response: We appreciate the reviewer's suggestion. While Method X
is indeed widely used, we found that Method Y is more appropriate
for our specific dataset due to [brief rationale]. However, we have
added a comparative discussion of both methods in the revised
manuscript (Page 8, Lines 200-210) to acknowledge this alternative
approach.
```
**Politely declining:**
```
Comment: The authors should remove Figure 3 as it seems redundant.
Response: We thank the reviewer for this suggestion. Upon careful
consideration, we believe Figure 3 provides essential visual
support for the key finding discussed in Section 4.2. To enhance
clarity, we have revised the figure caption to better emphasize
its unique contribution (Page 10, Figure 3 caption).
```
### Step 4: Tone Adjustment
Adjust language based on context:
| Tone | Use Case | Example Phrasing |
|------|----------|------------------|
| Diplomatic | General revisions | "We thank..." / "We appreciate..." / "We have revised..." |
| Assertive | Defending methodology | "We respectfully note..." / "Our approach is justified because..." |
| Grateful | Major improvements | "We are grateful for..." / "This significantly improved..." |
## Input Format
Accept multiple input formats:
- Copy-pasted reviewer comments
- PDF extracted text
- Structured JSON with comment IDs
- Markdown with sections
## Output Format
Returns a complete response letter with:
- Proper salutation and closing
- Numbered responses matching reviewer comments
- Inline citations to manuscript locations
- Professional academic tone throughout
## Usage Example
```
User: Help me draft a response to these reviewer comments:
Reviewer 1:
1. The introduction should better motivate the problem
2. Figure 2 is unclear
3. Have you considered Smith et al. 2023?
My changes:
1. Added motivation paragraph
2. Redrew Figure 2 with clearer labels
3. Added citation and discussion
Journal: Nature Communications
```
## Parameters
| Parameter | Type | Required | Default | Description |
|-----------|------|----------|---------|-------------|
| `--interactive` | flag | No | - | **Interactive mode**: Guided wizard with prompts (uses `input()`). Recommended for first-time users or complex responses |
| `--input-file` | str | No | - | Path to reviewer comments file (automation mode) |
| `--output` | str | No | - | Output file path for response letter |
| `--tone` | str | No | "diplomatic" | Response tone: "diplomatic", "formal", or "assertive" |
| `--format` | str | No | "markdown" | Output format: "markdown", "plain_text", or "latex" |
| `--include-diff` | bool | No | true | Whether to summarize changes made |
**Usage Modes:**
- **Interactive Mode**: Use `--interactive` for guided setup with prompts (recommended for first-time users)
- **File Mode (Recommended for automation)**: Use `--input-file` with pre-prepared reviewer comments
## Technical Notes
- **Difficulty**: High - Requires understanding of academic norms, context-aware tone adjustment, and nuanced handling of criticism
- **Limitations**: Does not verify factual accuracy of responses; human review required for technical content
- **Safety**: No external API calls; processes text locally
## References
- `references/response_templates.md` - Common response patterns
- `references/tone_guide.md` - Academic tone guidelines
- `references/examples/` - Sample response letters
## Quality Checklist
Before finalizing, verify:
- [ ] Every reviewer comment has a corresponding response
- [ ] Responses are numbered/lettered consistently with comments
- [ ] All changes are referenced with page/line numbers
- [ ] Disagreements are framed constructively
- [ ] No defensive or confrontational language
- [ ] Professional tone maintained throughout
## Risk Assessment
| Risk Indicator | Assessment | Level |
|----------------|------------|-------|
| Code Execution | Python/R scripts executed locally | Medium |
| Network Access | No external API calls | Low |
| File System Access | Read input files, write output files | Medium |
| Instruction Tampering | Standard prompt guidelines | Low |
| Data Exposure | Output files saved to workspace | Low |
## Security Checklist
- [ ] No hardcoded credentials or API keys
- [ ] No unauthorized file system access (../)
- [ ] Output does not expose sensitive information
- [ ] Prompt injection protections in place
- [ ] Input file paths validated (no ../ traversal)
- [ ] Output directory restricted to workspace
- [ ] Script execution in sandboxed environment
- [ ] Error messages sanitized (no stack traces exposed)
- [ ] Dependencies audited
## Prerequisites
```bash
# Python dependencies
pip install -r requirements.txt
```
## Evaluation Criteria
### Success Metrics
- [ ] Successfully executes main functionality
- [ ] Output meets quality standards
- [ ] Handles edge cases gracefully
- [ ] Performance is acceptable
### Test Cases
1. **Basic Functionality**: Standard input → Expected output
2. **Edge Case**: Invalid input → Graceful error handling
3. **Performance**: Large dataset → Acceptable processing time
## Lifecycle Status
- **Current Stage**: Draft
- **Next Review Date**: 2026-03-06
- **Known Issues**: None
- **Planned Improvements**:
- Performance optimization
- Additional feature support