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v1.0.0
GitHub

About this Skill

Perfect for Research Assist Agents needing advanced academic document review capabilities. Proofread is an AI-powered academic review skill that evaluates documents for weaknesses in Methods and Results sections, providing detailed feedback and improvement suggestions.

Features

Evaluates GitHub files and repositories for academic document review
Assesses Methods sections for weaknesses in 5 key areas: Reproducibility, Controls, Sample size/power, Statistical appropriateness, and Validation
Analyzes Results sections for Claim type, Evidence level, and Overclaiming risk
Provides actionable feedback and improvement suggestions for identified weaknesses
References detailed evaluation guides in reports/proofreading_guide.md

# Core Topics

yinijooy yinijooy
[0]
[0]
Updated: 3/7/2026

Quality Score

Top 5%
30
Excellent
Based on code quality & docs
Installation
SYS Universal Install (Auto-Detect)
Cursor IDE Windsurf IDE VS Code IDE
> npx killer-skills add yinijooy/safa/proofread

Agent Capability Analysis

The proofread MCP Server by yinijooy is an open-source Categories.community integration for Claude and other AI agents, enabling seamless task automation and capability expansion. Optimized for how to use proofread for academic papers, what is proofread skill, proofread alternative for researchers.

Ideal Agent Persona

Perfect for Research Assist Agents needing advanced academic document review capabilities.

Core Value

Empowers agents to assess reproducibility, evaluate statistical appropriateness, and identify overclaiming risks in academic documents using methods like controls and validation, while referencing GitHub files and code.

Capabilities Granted for proofread MCP Server

Evaluating Methods sections for reproducibility and statistical appropriateness
Analyzing Results sections for claim types, evidence levels, and overclaiming risks
Generating detailed feedback reports for authors, including specific problems and improvement suggestions

! Prerequisites & Limits

  • Requires access to academic documents, potentially via GitHub links
  • Limited to assessing documents from a Nature reviewer's perspective
Project
SKILL.md
1.8 KB
.cursorrules
1.2 KB
package.json
240 B
Ready
UTF-8

# Tags

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SKILL.md
Readonly

Proofreading Skill

학술 문서를 Nature 리뷰어 관점에서 검토하고 평가합니다.

모든 상세 내용은 reports/proofreading_guide.md 참조


동작 순서

  1. GitHub 파일 참조 (필요시)

    • 사용자가 제공한 GitHub 링크에서 원본 문서 확인
    • 관련 코드/데이터 파일 검토
  2. Methods 섹션 평가

    • 5가지 측면에서 약점 지적: Reproducibility, Controls, Sample size/power, Statistical appropriateness, Validation
    • 각 약점에 대해: 구체적 문제점, 리뷰어 예상 질문, 개선 방안 제시
  3. Results 섹션 평가

    • 각 문장별 Claim type, Evidence level, Overclaiming risk 분석
    • 가장 위험한 overclaim 3개 지적 및 수정 방법 제시
  4. 종합 프루프리딩

    • 평가 결과 통합
    • 수정 사항 도출
    • 최종 권고안 작성

Methods 평가 프롬프트

다음 Methods 섹션을 Nature 리뷰어 관점에서 평가해줘:

[Methods text]

다음 5가지 측면에서 약점을 지적:
1. Reproducibility (재현성)
2. Controls (통제)
3. Sample size/power (샘플/검정력)
4. Statistical appropriateness (통계 적절성)
5. Validation (타당성)

각 약점에 대해:
- 구체적 문제점
- 리뷰어가 제기할 질문
- 개선 방안

Results 평가 프롬프트

다음 Results 문장들을 분석해줘:

[Results text]

각 문장에 대해:
1. Claim type (causal/correlational/mechanistic/general)
2. Evidence level (direct/indirect/suggestive)
3. Overclaiming risk (1-10)
4. Conservative alternative phrasing

그리고:
- 가장 위험한 overclaim 3개 지적
- 각각을 데이터에 맞게 수정하는 방법

참고

평가 기준, 출력 템플릿, 참고 문서 목록은 모두 reports/proofreading_guide.md 참조

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