Edit English academic papers for international journal submission through three passes covering grammar, readability, and academic precision. Receive polished text and explanations of major changes while preserving the author's substantive arguments and conclusions.
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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.
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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.
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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.
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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.
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Draft research funding proposals for NSF, NIH, DOE, and DARPA using agency-specific structures and review criteria. Develop research aims, significance, innovation, methods, milestones, and budget justifications into a proposal aligned with the funding opportunity.
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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.
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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.
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Find STATA code examples for empirical accounting research from published replication files. Adapt regression, matching, event study, and table export syntax to your variables, with citations to the papers behind each example.
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Evaluate research papers and scientific claims by examining study design, statistics, bias, and evidence quality. Receive a structured critique of strengths, weaknesses, supported conclusions, and practical improvements, with uncertainty and limitations made explicit.
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Audit writing for repetitive phrases, vague praise, excessive formatting, and other patterns associated with AI text. Get a revised version with reasons for changes, or use detection mode to review flagged passages without altering the original.
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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.
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Coordinate research, drafting, citation and data verification, AI review, revision, and final formatting through connected skills. Start from a research topic, an existing manuscript, or reviewer comments, with progress tracking and user checkpoints.
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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.
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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.
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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.
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Proofread applied microeconomics manuscripts across prose, equations, tables, notes, and references. The workflow combines specialized reviews into a prioritized report with exact locations, suggested corrections, consistency checks, and items requiring author verification.
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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.
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Edit prose to remove formulaic AI phrasing, vague claims, inflated language, and repetitive structures. Apply context-appropriate tone to scientific papers, blog posts, and workplace documents, with review scores covering directness, rhythm, authenticity, and concision.
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Build and evaluate Bayesian models with PyMC and ArviZ, from choosing initial assumptions to checking predictions. The workflow covers sampling diagnostics, model comparison, and reports that explain results with uncertainty intervals.
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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.
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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.
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Create resumes, reports, papers, and other documents with LaTeX, a document typesetting system, then produce PDFs and page previews. Also convert document formats and handle PDF tasks such as merging files and filling forms.
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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.
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