3395 skills.
Showing 2497–2520 of 3,395 · Page 105 of 142
brycewang-stanford/Auto-Empirical-Research-Skills
This skill should be used when the user asks to "create a slash command", "add a command", "write a custom command", "define command arguments", "use command frontmatter", "organize commands", "create command with file references", "interactive command", "use AskUserQuestion in command", or needs guidance on slash command structure, YAML frontmatter fields, dynamic arguments, bash execution in commands, user interaction patterns, or command development best practices for Claude Code.
This skill should be used when the user asks to review a diff or pull request, write review comments, audit code quality, establish review standards, or improve how a team performs code review.
This skill provides reference guidance for citation verification in academic writing. Use when the user asks about "citation verification best practices", "how to verify references", "preventing fake citations", or needs guidance on citation accuracy. This skill supports ml-paper-writing by providing detailed verification principles and common error patterns.
This skill should be used when the user asks to "debug this", "fix this error", "investigate this bug", "troubleshoot this issue", "find the problem", "something is broken", "this isn't working", "why is this failing", or reports errors/exceptions/bugs. Provides systematic debugging workflow and common error patterns.
Use only when creating new registrable ML components that require Factory or Registry patterns.
Use when creating or configuring Claude Code agents and their frontmatter.
Comprehensive Stata reference for writing correct .do files, data management, econometrics, causal inference, graphics, Mata programming, and 20 community packages (reghdfe, estout, did, rdrobust, etc.). Covers syntax, options, gotchas, and idiomatic patterns. Use this skill whenever the user asks you to write, debug, or explain Stata code.
Guide for contributing to the stata-skill project. Use when the user wants to run the eval pipeline, analyze test results, improve reference docs, add new package documentation, or work on roadmap items. Covers the testing infrastructure, multi-agent analysis workflow, cost estimates, and links to prior eval results and improvement history.
Develop high-performance C/C++ plugins for Stata using the stplugin.h SDK. Use when the user asks to create a Stata plugin, write C/C++ code for Stata, accelerate a Stata command with C, build cross-platform Stata plugins, or translate/port a Python or R package into Stata. Covers the full lifecycle: SDK setup, data flow, memory safety, .ado wrappers with preserve/merge, cross-platform compilation, performance optimization (pthreads, pre-sorted indices, XorShift RNG), debugging, and distribution via net install. Also includes a translation workflow for porting Python/R packages to Stata — wrapping existing C++ backends when available, or writing C from scratch when not.
Generate publication-ready regression tables in LaTeX.
Draft economics papers with proper structure and academic style
Write and typeset economic models in LaTeX with proper notation
Build and solve Walrasian general equilibrium models with theory derivations and Julia computation
Search, summarize, and synthesize economics literature
Generate research questions from economic phenomena
Clean and transform messy data in Stata with reproducible workflows
Fetch economic data from FRED, World Bank, and other APIs
Create publication-quality charts and graphs for economics papers.
Create academic presentations in Beamer with professional themes
Run regression analyses in Stata with publication-ready output tables.
Run IV, DiD, and RDD analyses in R with proper diagnostics
Panel data analysis with Python using linearmodels and pandas.
Checklist of empirical robustness tests for finance/economics papers
Structure responses to referee reports for R&R submissions
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