Co-write proposals, technical specifications, and decision documents through context gathering, section-by-section drafting, and revision. A fresh AI reader then tests the document to reveal unclear explanations, missing context, and contradictions before it is shared.
- Drafting a proposal through discussion
- Organizing the structure of a technical specification
- Writing a document that explains a decision
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7KUpdated Oct 20, 2026
Assess study quality and risk of bias, meaning systematic distortions in research results. Choose assessment tools suited to the study and review purpose, document judgment rationales, and summarize evidence certainty and recommendations for use in further analysis.
- Appraising studies included in a systematic review
- Checking study quality before a meta-analysis
- Assessing evidence certainty with GRADE
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7KUpdated Oct 20, 2026
Review academic drafts for exaggerated claims, vague attribution, repetitive wording, and other style issues. Produces prioritized findings, section-level assessments, and revision recommendations, with additional checks for LaTeX syntax problems that can disrupt document export.
- Reviewing manuscript style before journal submission
- Checking AI-assisted drafts for formulaic wording
- Assessing abstracts and reviewer response letters
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7KUpdated Oct 20, 2026
Clean up hard-wrapped Markdown and .qmd files by joining mid-sentence line breaks and placing each sentence on its own line. Preserve headings, code blocks, lists, quotes, and YAML metadata while adjusting paragraph whitespace.
- Removing mid-sentence line breaks from a README
- Putting each sentence of a .qmd paper on its own line
- Reformatting text while preserving Markdown structure
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7KUpdated Oct 20, 2026
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.
- 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☆ 4.7KUpdated Oct 20, 2026
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.
- 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☆ 4.7KUpdated Oct 20, 2026
Carry out research implementation plans from environment setup through code, tests, and pull requests. The workflow checks estimation convergence, standard errors, diagnostics, and reproducibility while tracking completed tasks in the original plan.
- Implement an estimation method from a research plan
- Build and verify a research data pipeline
- Run robustness checks and document results
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7KUpdated Oct 20, 2026
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.
- 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☆ 4.7KUpdated Oct 20, 2026
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.
- Reviewing a manuscript before submission
- Checking the assumptions behind causal claims
- Anticipating referee objections and possible responses
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7KUpdated Oct 20, 2026
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.
- 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☆ 4.7KUpdated Oct 20, 2026
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.
- 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☆ 4.7KUpdated Oct 20, 2026
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.
- Design a multi-year research program
- Turn research ideas into defined projects
- Plan roles for student research teams
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7KUpdated Oct 20, 2026
Turn completed analyses, research plans, and literature reviews into an academic manuscript. The skill proposes an outline for approval, drafts sections around existing tables and figures, and arranges a review of arguments and supporting evidence.
- Drafting a paper from completed analyses
- Writing an introduction or abstract from existing results
- Planning sections around available tables and figures
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7KUpdated Oct 20, 2026
Assess a social science paper outline in a .qmd file for missing research questions, contributions, hypotheses, data, and analysis plans. Receive criterion ratings and concrete suggestions in a separate report, with causal assumptions assessed when relevant.
- Check whether a paper outline covers essential research elements
- Clarify contributions relative to previous studies
- Review causal assumptions in a research outline
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7KUpdated Oct 20, 2026
Review academic slide decks or audit empirical analysis pipelines. It checks slide arguments, layout, and compilation, or reproduces numerical results in R, Stata, and Python to diagnose discrepancies and produce a formal report with prioritized recommendations.
- Reviewing academic slide arguments and layout
- Checking LaTeX compilation warnings
- Comparing empirical results across R, Stata, and Python
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7KUpdated Oct 20, 2026
Turn an initial research idea into a project specification through a structured interview. Develop testable questions, hypotheses, methods for identifying causal effects, and data requirements, then rank options by feasibility and contribution and save the plan.
- Turn a broad topic into research questions
- Compare approaches for identifying causal effects
- Prioritize questions by feasibility and contribution
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7KUpdated Oct 20, 2026
Prepare academic papers for journal submission by checking manuscripts and figures, adapting journal formatting, drafting cover letters and responses to reviewers, and tracking revisions through resubmission with a structured response table.
- Checking a manuscript before its first journal submission
- Adapting paper formatting for a specific journal
- Drafting point-by-point responses to reviewers
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7KUpdated Oct 20, 2026
Audit an entire repository with four parallel agents checking documentation, hook scripts, skills, and rules. Identify broken references, incorrect counts, code issues, and conflicting information, then apply fixes and repeat verification for up to five rounds.
- Check repository consistency after broad changes
- Find broken paths and outdated feature counts
- Review hook scripts and rule consistency
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7KUpdated Oct 20, 2026
Review existing R scripts for code quality, reproducibility, domain correctness, and coding standards. Produce a separate report for each script, plus a severity-based summary of findings and the three most critical issues, without changing source files.
- Checking whether an analysis script is reproducible
- Reviewing R code against coding conventions
- Auditing several related R scripts
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7KUpdated Oct 20, 2026
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.
- Creating reading notes from a paper PDF
- Summarizing a directory of papers
- Reviewing key estimates and research methods
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7KUpdated Oct 20, 2026
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.
- 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☆ 4.7KUpdated Oct 20, 2026
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.
- 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☆ 4.7KUpdated Oct 20, 2026
Convert LaTeX article manuscripts into Quarto documents for publishing as HTML, PDF, or Word. Preserve mathematical content while adapting document settings, citations, figures, tables, and cross-references, and receive a report of items needing manual review.
- Migrate a LaTeX paper to Quarto
- Prepare a manuscript for HTML, PDF, and Word
- Convert citations and cross-references
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7KUpdated Oct 20, 2026
Turn a recently solved research problem into searchable Markdown documentation. Capture symptoms, failed attempts, root causes, working code, and prevention checks, then organize the solution by category and link it to related records.
- Recording a fix for estimation convergence failures
- Documenting causes and fixes for data processing errors
- Preserving solutions to reproducibility problems
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7KUpdated Oct 20, 2026