hchulkim

Fetch structured data from external APIs for research workflows. Use when Codex needs to query a documented API, save raw responses reproducibly, transform them into project-ready tables, or document authentication and rate-limit constraints for later reruns.

Compile LaTeX papers or slide decks reproducibly. Use when Codex needs to build a paper or Beamer deck, summarize warnings, rerun bibliography steps, or verify that a manuscript target compiles cleanly before review or submission.

Summarize current session state and preserved project context. Use when Codex needs to report what files and plans capture the current state, identify what will survive a long session boundary, or point the user to the latest durable artifacts on disk.

Prepare data and code materials for deposit or archival handoff. Use when Codex needs to check repository contents against deposit requirements, organize metadata, verify provenance notes, or prepare deposit-facing documentation without changing the scientific content.

Deploy or publish project artifacts safely. Use when Codex needs to prepare a site, service, documentation artifact, or generated output for release, confirm prerequisites, and outline the reproducible deployment steps without skipping verification.

Implement or review econometrics workflows in Julia. Use when Codex needs to write Julia estimation code, check design-to-code alignment, structure reproducible Julia scripts, or adapt an empirical workflow into Julia while preserving the project's numbered analysis conventions.

Implement or review econometrics workflows in R. Use when Codex needs to write R estimation scripts, translate an empirical design into R code, enforce reproducible R execution through `nix-shell`, or review R analysis output against project conventions.

Find and assess datasets for a research question. Use when Codex needs to identify candidate data sources, compare coverage and access constraints, evaluate whether data can support an empirical design, or turn a project idea into a concrete data-sourcing memo.

Initialize new economics research projects with standardized structure. Use when starting a new research project to create folder structure, configuration files, and boilerplate code. Sets up git, rix environment, Makefile, and connects to Dropbox/Overleaf.

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

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

R-based econometric analysis for academic research. Use when writing R code for panel data, difference-in-differences, instrumental variables, spatial econometrics, or regression analysis. Covers data.table, fixest, sf, modelsummary, and publication-ready outputs.