Check citations in LaTeX and Quarto manuscripts against a bibliography file. Find missing references, unused entries, and likely citation key typos, then flag incomplete fields, author formatting problems, and character encoding issues.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
- Investigating undefined citation errors
- Checking bibliography completeness after adding references
- Finding unused bibliography entries
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7천2026년 10월 20일 업데이트
Compare research methods before planning implementation. The skill examines project context, data constraints, required assumptions, computational costs, and available software, then documents two or three approaches with a recommendation and reasons for choosing it.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
- Choose an estimation method before implementation
- Compare methods under data and computing constraints
- Document assumptions and reasons for a methodological choice
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7천2026년 10월 20일 업데이트
Turn social science papers into structured Markdown reading notes covering contributions, key findings, methods, data, and limitations. Summaries include quantitative results, references to relevant tables or pages, keywords, and a BibTeX citation for later reference.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
- Creating reading notes from a paper PDF
- Summarizing a directory of papers
- Reviewing key estimates and research methods
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7천2026년 10월 20일 업데이트
Generate 15–20 research directions from a question, topic, or data opportunity, then narrow them to 5–7 candidates. Receive ranked ideas with feasibility assessments, key risks, confidence scores, and reasons for rejecting the others.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
- Explore research directions from a broad topic
- Find research uses for newly available data
- Compare ideas by feasibility and contribution
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7천2026년 10월 20일 업데이트
Turn a research task or estimation problem into a saved implementation plan grounded in project code, prior decisions, and relevant methods. Adjust the detail to the task and document dependencies, risks, diagnostics, and acceptance criteria.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
- Planning implementation of a new estimation method
- Planning fixes for convergence or data problems
- Organizing robustness checks and replication steps
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7천2026년 10월 20일 업데이트
Set up a research project with separate folders for code, source data, cleaned datasets, results, and documents. Create a research rules file from a template, a project README, and an initial progress log.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
- Starting a new research project
- Standardizing folders across research projects
- Separating source data from cleaned datasets
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7천2026년 10월 20일 업데이트
Review a pre-analysis plan before registration or submission using six specialized agents. Combine checks of clarity, consistency, causal design, statistics, and feasibility into a prioritized report with revision recommendations tailored to the selected registry or journal.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
- Reviewing a pre-analysis plan before registration
- Checking alignment between hypotheses, outcomes, and analysis
- Assessing statistical power and multiple testing plans
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7천2026년 10월 20일 업데이트
Run a research task through five ordered stages: brainstorming, planning, implementation, review, and documentation. The workflow checks that brainstorming and planning files exist before proceeding, then reviews and documents what the implementation stage produced.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
- Taking a research task from initial ideas to documentation
- Planning and implementing an estimation problem
- Working through a methodological improvement
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7천2026년 10월 20일 업데이트
Turn regression results, summary statistics, and simulation output into tables and figures for academic papers. Apply consistent number formatting, labels, and accessible visual styles, then produce files ready to include in LaTeX documents.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
- Format regression results as LaTeX tables
- Compare simulation results in a table
- Plot estimates before and after an intervention
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7천2026년 10월 20일 업데이트
Review a grant proposal before submission through six specialized perspectives. Receive a consolidated report covering funder fit, research methods, feasibility, budget, consistency, and writing, with prioritized revisions and questions a review panel might ask.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
- Reviewing a grant proposal before submission
- Checking alignment with a target funder
- Finding gaps across methods, budget, and timeline
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7천2026년 10월 20일 업데이트
Configure the social-science-research plugin through guided questions about your field, institution, journals, and datasets. Save research preferences, researcher details, and R figure colors in project files for use in your research context.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
- Set up a newly installed research plugin
- Register journals and datasets for a research field
- Save key researchers for literature searches
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7천2026년 10월 20일 업데이트
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.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
- Preparing a research replication package
- Checking seeds, versions, and file paths
- Verifying reproduced outputs against expected results
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7천2026년 10월 20일 업데이트
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.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
- Checking estimation code and standard errors
- Examining assumptions behind identification arguments
- Reviewing proofs and derivations before submission
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7천2026년 10월 20일 업데이트
Find datasets for a research question and compare whether they support the planned study. Receive ranked candidates with feasibility grades, coverage, access requirements, methodological limitations, and recommended next steps for obtaining the most suitable data.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
- Find datasets for a research question
- Check whether data supports the planned research method
- Compare access requirements and waiting times
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7천2026년 10월 20일 업데이트
Review academic manuscripts for argument quality, causal evidence, statistical methods, citations, and presentation. Receive a structured report with strengths, major concerns, suggested improvements, and likely referee objections tied to specific parts of the paper.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
- Reviewing a manuscript before submission
- Checking the assumptions behind causal claims
- Anticipating referee objections and possible responses
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7천2026년 10월 20일 업데이트
Review an economics paper before submission using six specialized agents. Check prose, consistency, claims, mathematics, table and figure documentation, and research contribution, then consolidate findings into a structured report informed by the target journal.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
- Reviewing an economics paper before journal submission
- Checking consistency across text, equations, and tables
- Finding causal claims that exceed the evidence
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7천2026년 10월 20일 업데이트
Carry a research task from brainstorming and planning through code implementation, review, and documentation. Multiple agents handle independent implementation tasks in parallel, then report the resulting files, changes, and findings.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
- Take a research task from initial ideas through implementation
- Split independent implementation tasks among multiple agents
- Run review and knowledge documentation after implementation
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7천2026년 10월 20일 업데이트
Check a paper's numerical claims against saved analysis outputs before submission. Receive a report identifying verified figures, unsupported claims, missing files, unreferenced outputs, and citation keys absent from the bibliography, without changing the manuscript.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
- Check manuscript numbers before submission
- Verify table and figure references against output files
- Find analysis outputs not referenced in the paper
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7천2026년 10월 20일 업데이트
Examine figures, tables, and empirical results before interpreting them. The skill reviews every visible feature, explores possible explanations, checks sample sizes and patterns across estimates, and records unresolved questions in a structured report.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
- Reviewing a figure before publication
- Investigating unexpected spikes or dips
- Checking sample sizes across tables
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7천2026년 10월 20일 업데이트
Turn research ideas into a coordinated program with clear questions, data needs, methods, team roles, and publication plans. Connect academic papers with policy and public-facing outputs while considering feasibility, data availability, and long-term institutional activities.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
- Design a multi-year research program
- Turn research ideas into defined projects
- Plan roles for student research teams
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7천2026년 10월 20일 업데이트
Download and read academic PDFs in small batches, splitting them into four-page files. Build structured notes covering research questions, methods, data, findings, and replication feasibility, with progress saved after each batch.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
- Read a long academic paper in manageable batches
- Extract data sources and statistical methods
- Assess whether a study can be replicated
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7천2026년 10월 20일 업데이트
Survey academic research on a topic by searching journals, working papers, and citation links. Combine findings into a structured report covering key papers, competing results, research gaps, and verified bibliography entries.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
- Survey prior research on a new topic
- Find related studies through a key paper's citations
- Compare conflicting findings across studies
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7천2026년 10월 20일 업데이트
Review a research paper alongside its Stata, R, or Python code to check reproducibility, code quality, and agreement with the main findings. Receive a Markdown report with supporting evidence, uncertainties, strengths, and prioritized next steps.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
- Checking reproducibility before sharing research code
- Matching main tables and figures to analysis scripts
- Reviewing dependencies, file paths, and execution order
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7천2026년 10월 20일 업데이트
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.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
- Define relevance criteria before a large literature search
- Investigate papers incorrectly included or excluded
- Reassess saved abstracts after changing screening criteria
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7천2026년 10월 20일 업데이트