brycewang-stanford/Auto-Empirical-Research-Skills - 8페이지

check-citations

Verify academic citations against CrossRef, Semantic Scholar, and OpenAlex. Detects AI-hallucinated references, chimeric citations, and suspicious patterns.

원문 언어: 영어

lifelines

Complete survival analysis library in Python. Handles right-censored data, Kaplan-Meier curves, and Cox regression. Standard for clinical trial analysis and epidemiology.

원문 언어: 영어

computational-inference

Computational methods for statistical inference and optimization

원문 언어: 영어

statistical-software-qa

Quality assurance and testing protocols for statistical software

원문 언어: 영어

mathematical-foundations

Core mathematical concepts and theoretical frameworks for statistics

원문 언어: 영어

mediation-meta-analyst

Meta-analysis frameworks and methods for mediation studies

원문 언어: 영어

sensitivity-analyst

Sensitivity analysis frameworks and assumption-testing methods

원문 언어: 영어

methods-communicator

Effective communication strategies for statistical methods

원문 언어: 영어

publication-strategist

Strategic publication planning and venue selection for research

원문 언어: 영어

event-study

Use this skill whenever the user wants to conduct an event study, create event study plots, test for parallel trends, implement difference-in-differences designs, or work with any panel data estimation that involves pre/post treatment comparisons. Trigger on…

원문 언어: 영어

humanize-chinese

Detect and humanize AI-generated Chinese text. 20+ rule detection categories plus statistical features (sentence-length CV, short-sentence fraction, comma density, perplexity, GLTR, DivEye) plus scene-aware LR fusion (rule × 0.2 + LR × 0.8) trained on three…

원문 언어: 중국어

literature-review

Conduct comprehensive, systematic literature reviews using multiple academic databases (PubMed, arXiv, bioRxiv, Semantic Scholar, etc.). This skill should be used when conducting systematic literature reviews, meta-analyses, research synthesis, or…

원문 언어: 영어

ml-paper-writing

Write publication-ready ML/AI/Systems papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM, OSDI, NSDI, ASPLOS, SOSP. Use when drafting papers from research repos, structuring arguments, verifying citations, or preparing camera-ready submissions. Includes LaTeX…

원문 언어: 영어

latex-document

Universal LaTeX document skill: create, compile, and convert any document to professional PDF with PNG previews. Supports resumes, reports, cover letters, invoices, academic papers, theses/dissertations, academic CVs, presentations (Beamer), scientific…

원문 언어: 영어

causal-inference-mixtape

This skill should be used when the user asks to "implement a DiD regression", "write a causal inference pipeline", "set up an event study", "implement instrumental variables", "run a regression discontinuity design", "build a synthetic control model",…

원문 언어: 영어

avoid-ai-writing

Audit and rewrite content to remove AI writing patterns ("AI-isms"). Use this skill when asked to "remove AI-isms," "clean up AI writing," "edit writing for AI patterns," "audit writing for AI tells," or "make this sound less like AI." Supports a…

원문 언어: 영어

humanizer-academic

Remove signs of AI-generated writing from academic medical papers. Use when editing or reviewing manuscripts to make them sound more natural and professionally written. Based on Wikipedia's "Signs of AI writing" guide, adapted for medical literature. Detects…

원문 언어: 영어

deslop

Remove AI writing patterns from prose. Use this skill when writing, drafting, editing, reviewing, or revising any text to eliminate predictable AI tells, slop, and formulaic patterns. Trigger this skill whenever the user asks to "deslop", "de-AI", "make it…

원문 언어: 영어

stop-slop

Remove AI writing patterns from prose. Use when drafting, editing, or reviewing text to eliminate predictable AI tells.

원문 언어: 영어

python-panel-data

Panel data analysis with Python using linearmodels and pandas.

원문 언어: 영어

r-econometrics

Run IV, DiD, and RDD analyses in R with proper diagnostics

원문 언어: 영어

stata-regression

Run regression analyses in Stata with publication-ready output tables.

원문 언어: 영어

beamer-presentation

Create academic presentations in Beamer with professional themes

원문 언어: 영어

econ-visualization

Create publication-quality charts and graphs for economics papers.

원문 언어: 영어

api-data-fetcher

Fetch economic data from FRED, World Bank, and other APIs

원문 언어: 영어

stata-data-cleaning

Clean and transform messy data in Stata with reproducible workflows

원문 언어: 영어

code-simplifier

Simplify and clean up code after changes are complete. Reduces complexity, improves readability, and ensures consistency.

원문 언어: 영어

commit-push-pr

Commit changes, push to remote, and create a pull request. Use for completing features or fixes ready for review.

원문 언어: 영어

sdd

Implements the Spec-Driven Development lifecycle (Intent, Requirements, Design, Tasks, Build) for structured feature development. Use when the user wants to scaffold a new feature spec, generate EARS requirements, create a technical design, break work into…

원문 언어: 영어

techdebt

Find and fix technical debt including duplicated code, dead code, outdated patterns, and code smells. Run at the end of sessions to clean up.

원문 언어: 영어

research-ideation

Generate research questions from economic phenomena

원문 언어: 영어

lit-review-assistant

Search, summarize, and synthesize economics literature

원문 언어: 영어

general-equilibrium-model-builder

Build and solve Walrasian general equilibrium models with theory derivations and Julia computation

원문 언어: 영어

latex-econ-model

Write and typeset economic models in LaTeX with proper notation

원문 언어: 영어

academic-paper-writer

Draft economics papers with proper structure and academic style

원문 언어: 영어

latex-tables

Generate publication-ready regression tables in LaTeX.

원문 언어: 영어

bayesian-estimation

This skill covers Bayesian estimation and inference in quantitative social science. Use when the user is specifying priors, running MCMC, diagnosing chain convergence, or reporting posterior summaries — including hierarchical models, Bayesian structural…

원문 언어: 영어

causal-inference

This skill covers causal inference methods in observational and quasi-experimental settings. Use when the user is implementing, choosing between, or debugging causal identification strategies — including instrumental variables, difference-in-differences,…

원문 언어: 영어

causal-ml

This skill covers causal machine learning methods in applied economics and quantitative social science. Use when implementing or choosing between modern ML-based causal estimators — including double machine learning, DML, partially linear models, interactive…

원문 언어: 영어

empirical-playbook

This skill covers applied microeconomic empirical methods and research design. Use when the user is selecting an identification strategy, comparing estimators, running diagnostics, designing a research study, or evaluating an empirical strategy. Triggers on…

원문 언어: 영어