Analyze datasets in R or Python, from exploring distributions and missing values to fitting regressions. Produce tables and figures for publication, save scripts and model results, and review the analysis for common problems.
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Build and check research replication packages so a project's results can be reproduced. Routes checks to a dedicated agent that examines seeds, versions, file paths, workflow integrity, data documentation, execution environments, and matching outputs.
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Review econometric code, proofs, data workflows, and outputs with multiple specialist agents. Assess identification—the assumptions that let data establish an effect—alongside estimation, numerical stability, and reproducibility, then consolidate findings into prioritized tasks.
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Proofread academic papers and manuscripts for grammar, typos, layout problems, and inconsistent terminology or notation. Receive a report for each file with issue locations, suggested corrections, categories, and severity, while source files remain unchanged.
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Coordinate collaborative academic and policy writing, from author roles and timelines to draft revision, reviewer responses, and submission materials. Improve clarity and reproducibility while preserving authorial voice and flagging changes to claims or interpretations.
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Plan, run, and interpret linear regression with guidance on model choices, diagnostic checks, and reporting. Python, R, and Stata examples help examine coefficients, assess assumptions, and choose standard errors that account for different error patterns.
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Build and test scoring criteria for selecting relevant research papers. Refine the rules against your judgments, screen large sets of abstracts, and reassess saved papers when criteria change, with records of scores and revisions.
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Choose and implement methods for estimating causal effects from observational data or policy changes. Guidance covers method assumptions, estimation, diagnostic checks, and robustness tests that examine whether findings hold under alternative analysis choices.
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Adapt an academic paper’s title and section structure to a target journal. The skill proposes heading, numbering, and organizational changes, then updates main.tex while preserving the paper’s arguments, results, tables, and citations.
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Route structural estimation tasks into a staged workflow, from data validation and identification, checking whether model parameters can be determined, through estimation, standard errors, robustness checks, and results. Each phase must meet its conditions before the next begins.
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Convert Markdown files into Word documents with headings, tables, images, and code formatting. Supports batch conversion, optional contents pages, custom templates, and Chinese document styling, including automatic superscript formatting for eligible citation numbers.
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Proofread academic papers in LaTeX through 19 sequential checks. Compare prose with table values, inspect citations and argument consistency, and suggest clearer wording. Review each proposed change individually before it is applied.
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Analyze strategic interactions in markets, including firm entry, pricing, auctions, and bargaining. Guides equilibrium selection and computation, explains how to handle multiple possible outcomes, and helps assess whether data can identify the model's parameters.
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Choose methods for causal research in applied microeconomics by examining how treatment varies. Compare assumptions, plan diagnostic checks, assess statistical power—the ability to detect effects—and organize a defensible empirical strategy.
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Develop Bayesian models for quantitative social science, from choosing priors to reporting posterior results. Guide MCMC, a sampling method for estimating distributions, check convergence, and assess sensitivity for hierarchical models and small datasets.
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Find related research by following a paper's references and the later papers that cite it through Semantic Scholar. Filters prioritize relevant candidates, avoid duplicate reviews, and record citation relationships for a focused literature search.
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Find NBER working papers, research papers shared before formal publication, by keyword or research program. Retrieve recent papers, authors, dates, and citation details, and access US business cycle dates and links to economic datasets.
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Coordinate multiple helper agents to screen large paper collections, extract detailed findings, and explore citations. Consolidate structured results into review records and summaries, while checking coverage, duplicate entries, and consistency in relevance scoring.
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Find scientific papers in PubMed by turning a research question into targeted search terms and synonyms. Collect titles, authors, abstracts, and identifiers into a structured paper list ready for relevance evaluation.
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Choose and interpret models for panel data, which tracks the same firms, people, or countries over time. Use Python, R, or Stata examples to compare fixed and random effects, check assumptions, and select standard errors.
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Screen search results by scoring paper abstracts, then examine promising papers for specific measurements, methods, or datasets. Record findings and review history so you can identify useful evidence and avoid checking the same papers again.
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Check whether medicinal chemistry papers are indexed in ChEMBL, a curated database of biological activity measurements. Look up papers by DOI, report available data counts, and retrieve structured measurements before extracting tables from PDFs.
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Investigate research questions by searching PubMed, assessing paper relevance, and following references and citing papers. Extract specific data and findings into an organized summary, with search methods, citation links, and screening records for later review.
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Search Kaggle datasets, competitions, notebooks, and models through its official command-line tool. Download public data into a chosen directory and preserve audit records and file hashes, identifiers used to check downloaded files.
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