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Plan and draft academic papers through specialized agent roles covering literature, arguments, citations, and review. Get chapter guidance, revision roadmaps, Traditional Chinese and English abstracts, and documents formatted as LaTeX, DOCX, PDF, or Markdown.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Planning a paper chapter by chapter
• Drafting a paper from research materials
• Turning reviewer comments into a revision roadmap

Review English and Chinese empirical papers for formulaic language and claims that overstate the evidence. Supports revisions that preserve numbers and citations, checks bilingual consistency, and includes tools for inspecting invisible characters and file metadata.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Revising formulaic language in English or Chinese empirical papers
• Checking whether claims match tables and citations
• Aligning claims in Chinese text and an English abstract

Search multiple academic databases, screen studies, assess their quality, and combine findings by theme. Produce a literature review in Markdown and PDF, with checked citations and a documented search and selection process.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Preparing a literature review for a thesis or paper
• Comparing findings across studies on one topic
• Identifying research gaps and future directions

Turn observations or preliminary data into competing scientific hypotheses grounded in literature. It compares explanations, evaluates how they could be tested or disproved, and proposes experiments and measurable predictions in a structured report with diagrams.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Developing hypotheses from preliminary observations
• Comparing competing explanations for a phenomenon
• Planning experiments to distinguish hypotheses

Develop a literature review from a focused research question through search planning, source evaluation, organization, and writing. It helps compare findings across papers, identify disagreements and research gaps, and build an outline with practical writing templates.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Planning a standalone literature review
• Writing a paper's literature review section
• Comparing themes and disagreements across studies

Build reproducible empirical analyses in R, from data cleaning to statistical modeling and publication tables and figures. Covers economics, epidemiology, and machine learning approaches to causal inference, which estimates effects of interventions.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Build a reproducible R or Quarto analysis workflow
• Compare regression models with progressively added controls
• Test robustness across samples and statistical methods

Build a Python workflow for empirical research, from data cleaning and statistical checks to estimation, robustness checks, and paper-ready tables and figures. Economics is the default, with additional modes for epidemiology, public health, and machine learning for causal inference.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Building an end-to-end empirical analysis workflow in Python
• Replicating an applied economics paper
• Producing regression tables and event-study plots

Develop a research question, search and verify literature, combine findings, and produce a structured report. Seven modes cover guided research discussions, briefs, literature reviews, fact-checking, and systematic reviews, with statistical pooling of study results when appropriate.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Clarify a research topic through guided questions
• Build an annotated bibliography and synthesize findings
• Check claims against verified sources

Coordinate AI research from literature review to paper drafting. The skill alternates focused experiments with broader reviews of findings, tracks hypotheses and decisions, and uses specialist skills to carry out research tasks and prepare progress reports.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Starting a research project from a question
• Testing and comparing multiple hypotheses
• Reassessing direction when experiments stall

Build Python code for economic models and policy evaluation, with guidance on choosing libraries, estimating effects, plotting results, and checking robustness. Covers macroeconomic simulation and causal inference, the analysis of cause and effect.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Implementing macroeconomic models in Python
• Estimating policy effects with difference-in-differences
• Checking assumptions and robustness in causal analysis

Edit medical research manuscripts for clearer, more natural academic prose. Address inflated claims, vague wording, inconsistent terminology, and repetitive sentence patterns while preserving scientific meaning, supplied data, appropriate caution, and the author's established writing style.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Revise formulaic wording in an English medical paper
• Clarify comparisons and logical links in dense prose
• Standardize terminology throughout a manuscript

Plan philosophy and interdisciplinary papers by comparing preprint platforms, searching literature, identifying unanswered questions, and assessing originality. Receive a detailed outline with section word counts, key citations, and improvements based on a reviewer-style assessment.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Planning a philosophy or interdisciplinary paper
• Choosing a suitable preprint platform
• Finding research gaps and assessing originality

Turn a detailed outline into a philosophy or interdisciplinary manuscript. Draft chapters with repeated quality reviews, check terminology and arguments across sections, and prepare the manuscript, evaluation reports, abstract, and metadata for submission.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Draft a full paper from a detailed outline
• Review argument and citation quality chapter by chapter
• Check terminology and argument flow across chapters

Build a reproducible Stata analysis from data cleaning through modeling, diagnostic checks, and robustness tests. Generate runnable .do files, regression tables, and figures for empirical papers, with additional workflows for epidemiology and machine learning approaches to causal inference.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Building a reproducible Stata analysis pipeline
• Comparing regression specifications in a paper table
• Checking causal estimates with robustness tests

Build causal inference analyses to estimate intervention effects using templates drawn from Causal Inference: The Mixtape. Adapt code across Python, R, and Stata, with checks for method assumptions and guidance on language-specific packages and limitations.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Implement a difference-in-differences analysis
• Set up an event study and check parallel trends
• Build instrumental variable or discontinuity models

Prepare a PhD application research proposal in English or Chinese, from literature collection and outline approval to a reviewed Markdown draft. Adapt the structure to science, humanities, or social sciences, with methods, a timeline, references, and figure suggestions.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Drafting a research proposal for a PhD application
• Finding gaps in existing research through a literature review
• Planning research methods and a timeline

Draft and check a systematic literature review using PRISMA 2020, a reporting guideline for transparent reviews. Organize methods and findings into a Word manuscript, create a study selection flow diagram, and format references in APA 7th Edition style.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Drafting a first systematic literature review
• Turning a protocol or extraction sheet into a manuscript
• Creating a PRISMA study selection flow diagram

Navigate a structured literature review workflow in Claude Code, from finding and screening papers to extracting results and following citations. Learn which related skills to use and how to organize findings, PDFs, and duplicate tracking.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Find papers containing specific methods or results
• Define relevance criteria before screening many papers
• Follow references and citations to find related studies

Estimate how an intervention affects outcomes using Bayesian causal analysis. The workflow confirms causal assumptions with the user, selects a suitable method, checks whether findings withstand challenges, and reports effects with uncertainty and limitations.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Estimating the effect of a policy or intervention
• Mapping causal relationships before analysis
• Selecting a method for observational data

Evaluate scientific manuscripts and grant proposals for sound methods, statistics, reproducibility, ethics, and clear reporting. Produce a structured review that separates major concerns from minor issues and gives authors specific, constructive suggestions for revision.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Preparing a structured review of a scientific manuscript
• Evaluating methods and statistics in a grant proposal
• Checking reproducibility and reporting guidelines

Write and debug Python regressions with PyFixest using a reference for model formulas, estimation functions, and standard errors. It also covers extracting results, comparing models, and producing regression tables and plots, including models that account for group differences.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Write fixed-effects regression code
• Check clustered standard error settings
• Compare models in tables and plots

Draft ML, AI, and systems conference papers from research code and experimental results. Organize the argument, find and verify references, and prepare final submissions with LaTeX templates and reviewer guidance, refining drafts through researcher feedback.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Drafting a paper from research code and results
• Structuring the argument and explaining the contribution
• Finding references and verifying citation details

Evaluate papers, research proposals, and literature reviews using structured criteria. Produces evidence-based feedback on research questions, methods, data, analysis, and writing, with optional scores and prioritized recommendations tailored to the work's stage and purpose.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reviewing a paper before submission
• Assessing a research proposal's methods and feasibility
• Checking the coverage and synthesis of a literature review

Turn academic papers or written content into slide images, then combine them into PowerPoint and PDF files. The workflow extracts figures from PDFs and offers outline choices, visual styles, audience settings, and output languages.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Create slides from an academic paper
• Reuse paper figures and tables in slides
• Prepare research slides for reading and sharing