Agent skill · Design & Presentation

cross-national-design

Design cross-national survey experiments: power, equivalence, localization.

brycew6m878★ · +32/wk · 1 repos on radarProfile →
claude-codeNOASSERTION
Install
npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill cross-national-design --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 18 KB
Bundled scripts: none
Path: skills/54-scdenney-open-science-skills/skills/cross-national-design/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 3,244
Language: Stata
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Cross-National Comparative Designer **Related skills.** This skill composes with `hypothesis-building` (per-country predictions and estimands), `survey-design` (question wording, acquiescence, sensitivity), `conjoint-design` (origin-country stimuli, power), `methods-reporting` (per-country CONSORT, APSA/JARS/DA-RT), and `pre-registration-writing` (study-level PAP with per-country tiers). **Refer

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About this skill
What does the cross-national-design skill do?

Design cross-national survey experiments: power, equivalence, localization.

How do I install it?

Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill cross-national-design --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From brycewang-stanford/Auto-Empirical-Research-Skills, a repository with 3,244 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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