skills/22-christopherkenny-skills/skills/redistricting-analysis/SKILL.md
Redistricting analysis in R using the redistverse ecosystem. Use whenever the user is working with redist, redistmetrics, ggredist, geomander, adj, alarmdata, PL94171, censable, easycensus, tinytiger, baf, rict, or redistio. Covers the complete pipeline: Census and spatial data loading, adjacency graph construction, SMC/MCMC simulation, constraints (population balance, county splits, VRA compliance), convergence diagnostics, plan metrics (compactness, partisan fairness, splits), visualization, summary tables, and interactive plan drawing. Invoke whenever the user mentions redistricting, gerrymandering, district plans, simulation ensembles, or any redistverse package by name.
npx skillsauth add brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research redistricting-analysisInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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A comprehensive reference for redistricting analysis in R using the redistverse ecosystem (library(redistverse) loads redist, redistmetrics, ggredist, geomander, sf, and adj).
alarmdata, or assemble your own sf object and build a redist_map. → 12-alarmdata.mdredist_smc() (recommended) or MCMC to generate an ensemble of valid plans. → 01-redist-simulation.mdsummary()), R-hat, effective sample size, and plan diversity. → 01-redist-simulation.md| Package / Topic | Reference |
|----------------|-----------|
| redist_map, redist_smc, redist_mergesplit, redist_flip, redist_plans, diagnostics | 01-redist-simulation.md |
| redist_constr, add_constr_splits, add_constr_grp_hinge, all soft constraints | 02-redist-constraints.md |
| redist_enumpart, redist_shortburst, redist_cyclewalk, init_particles | 03-redist-advanced.md |
| redistmetrics — Polsby-Popper, Reock, spanning tree, prep_perims, comp_* functions | 04-redistmetrics-compactness.md |
| redistmetrics — efficiency gap, mean-median, bias, declination, part_* functions | 05-redistmetrics-partisan.md |
| redistmetrics — county splits, segregation, competitiveness, incumbents, plan_parity, group_frac | 06-redistmetrics-other.md |
| ggredist — geom_district, party color scales, cartographic palettes, theme_map | 07-ggredist.md |
| adj — adjacency graph construction, edge operations, coloring, Laplacian | 08-adj.md |
| geomander — adjacency construction, contiguity checks, seam_rip, edge editing | 09-geomander-adjacency.md |
| geomander — geo_match, estimate_down/up, block2prec, spatial estimation | 10-geomander-spatial.md |
| geomander — downloading VEST, ALARM, DRA, HEDA, get_lewis election data | 11-geomander-data.md |
| alarmdata — alarm_50state_map, pre-built datasets, caching, alarm_add_plan | 12-alarmdata.md |
| PL94171 — Census P.L. 94-171 decennial data ingestion | 13-pl94171.md |
| censable (data + state IDs), easycensus (ACS), tinytiger (TIGER shapefiles) | 14-census-utilities.md |
| baf — download official Census Bureau block assignment files | 15-baf.md |
| rict — gt summary tables: population, demographics, elections, compactness, splits | 16-rict.md |
| redistio — interactive Shiny plan drawing (draw()) and adjacency editor (adj_editor()) | 17-redistio.md |
redist_map — an sf tibble with one row per precinct. Stores the adjacency graph, population column, number of districts, and population tolerance. Created by redist_map() or downloaded via alarm_50state_map(). Standard columns include pop, pop_black, pop_hisp, pop_asian, pop_white, pop_vap, pop_bvap, ndv (Democratic votes), nrv (Republican votes), and geometry.
redist_plans — a tibble with one row per district per plan (so nsims × ndists rows, plus reference plans). Stores district assignments in a hidden integer matrix; metrics are added as columns via mutate(). Access the plan matrix with get_plans_matrix().
adj — an S3 vector class representing an adjacency list. Each element is a zero-indexed integer vector of neighbors. Stored as the adj column in redist_map.
| Map type | Typical pop_tol | Legal basis |
|----------|----------|-------------|
| Congressional | 0.005 (±0.5%) | Wesberry v. Sanders |
| State legislative | 0.05 (±10%) | Reynolds v. Sims |
| Local | Varies by state | State law |
tools
Show mcp-stata identity, connected tools, and status. Use when the user asks if mcp-stata is available, asks about access to the toolkit, or asks what Stata tools are connected.
tools
Activate when users mention Stata commands, .do files, regressions, econometrics, stored results, graphs, dataset inspection, replication, or Stata errors. Route the task through mcp-stata tools and the specialized research skills instead of treating it as plain text coding.
development
Build and review paper-ready regression, balance, and summary tables from Stata outputs. Use when the user needs a clean table for a draft, appendix, or coauthor share-out.
tools
Install, configure, update, or verify mcp-stata across Claude Code, Codex, Gemini CLI, Cursor, Windsurf, and VS Code. Activate when users ask to set up the Stata toolkit or troubleshoot the installation.