경제 및 금융에 대한 empirical 연구를위한 맞춤형 Claude Code 기술 컬렉션. 이 기술은 일반적인 학업 연구 과제에 대한 구조화 된 워크플로를 제공합니다.

설치

이 기술을 사용하려면 .md] 파일을 Claude Code 명령 디렉토리에 복사하십시오.

설치 후, /skill-name(e.g., /robustness])를 사용하여 Claude Code의 모든 기술을 호출할 수 있습니다.

skills/ 디렉토리에는 newer agent Skill 형식의 두 번째 세트가 있습니다. 기술, 각각 SKILL.md과 YAML frontmatter). 그들은 다른 위치에 설치:

작업이 기술의 description에 일치 할 때이 자동으로 주장; 당신은 또한 할 수 이름에 의해 호출. 아래 에이전트 스킬 참조.

유효한 기술

##1. 강도 (/robustness)

** 목적:** 금융/economics 종이를 위한 empirical 견고 시험의 포괄적인 검사 명부.

특징:

• 핵심 견고성 범주: 대안 샘플, 사양, 측정
• ID 시험: 위약, 전 종료, IV 진단
• DiD-specific 테스트 (패럴 트렌드, Bacon decomposition, Callaway-Sant’Anna)
• IV-특성 시험 (첫 단계 F, 약한 계기 inference)
• Referee 증거 최소한도 필요조건

Claude Code Skills for Empirical Research

A collection of custom Claude Code skills designed for empirical research in economics and finance. These skills provide structured workflows for common academic research tasks.

Installation

To use these skills, copy the .md files to your Claude Code commands directory:

# Copy all skills to your Claude commands folder
cp *.md ~/.claude/commands/

After installation, you can invoke any skill in Claude Code using /skill-name (e.g., /robustness).

The skills/ directory holds a second set in the newer agent skill format (a folder per skill, each with a SKILL.md and YAML frontmatter). Those install to a different location:

# Copy the agent skills to your Claude skills folder
cp -R skills/* ~/.claude/skills/

Claude invokes these automatically when a task matches the skill’s description; you can also call one by name. See Agent Skills below.

Available Skills

1. Robustness (/robustness)

Purpose: Comprehensive checklist of empirical robustness tests for finance/economics papers.

Features:

• Core robustness categories: alternative samples, specifications, measures
• Identification tests: placebo, pre-trends, IV diagnostics
• DiD-specific tests (parallel trends, Bacon decomposition, Callaway-Sant’Anna)
• IV-specific tests (first-stage F, weak instrument inference)
• Referee-proof minimum requirements
• Reporting templates for robustness tables

Usage:

/robustness
> "robustness checklist"     # Full checklist for current paper
> "DiD robustness"           # DiD-specific tests only
> "referee-proof"            # Most commonly requested tests

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2. Literature Review (/lit-review)

Purpose: Systematically summarize academic papers, extract key findings, and identify research gaps.

Features:

• Structured paper summary template
• Data & methodology extraction
• Comparison tables across multiple papers
• Literature gap analysis framework
• BibTeX generation

Usage:

/lit-review
> "summarize this paper"     # Full template
> "quick summary"            # Citation, question, finding, relevance
> "compare papers"           # Comparison table
> "find gaps"                # Identify research gaps

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3. Coding Guidelines (/coding-guidelines)

Purpose: Standardized Python & Stata coding practices for empirical research projects.

Features:

• Project directory organization
• Python script templates with path management
• Stata script templates with global macros
• Data loading, merging, and validation patterns
• Visualization standards (matplotlib/seaborn)
• Output table conventions (outreg2/esttab)