Agent skill · Data & Analytics

apsr-transparency-and-data-policy

Use when preparing the reproducibility / replication materials for an American Political Science Review (APSR) manuscript. APSR requires conditionally accepted authors to deposit a reproducibility package in the APSR Dataverse (Harvard Dataverse), which the editorial office verifies before publication. Covers quantitative and qualitative transparency and exemptions. Prepares the package; it does not waive requirements.

brycew6m878★ · +32/wk · 1 repos on radarProfile →
claude-codeMIT
Install
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill apsr-transparency-and-data-policy --agent claude-code

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

Facts
Files in the skill folder: 1
SKILL.md size: 6 KB
Bundled scripts: none
Path: American-Political-Science-Review-Skills/skills/apsr-transparency-and-data-policy/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 909 · +31 this week
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

# Transparency & Data Policy (apsr-transparency-and-data-policy) APSR does not just ask for data — it **verifies** that the deposited materials reproduce the manuscript's tables and figures **before** publication. Build the package as you go so conditional acceptance does not stall. ## When to trigger - Building the reproducibility/replication package - A manuscript reached **conditional acceptance** and the editorial office requested materials - Data cannot be fully shared (privacy, ethics, legal/provider restrictions) and you need the exemption path - A **Replications and Reappraisals** submission (materials expectations are central) ## What APSR requires (verify current wording on the policy page) 1. **Deposit to the APSR Dataverse.** Authors of **conditionally accepted** manuscripts submit a **reproducibility package** to the **APSR Dataverse on Harvard Dataverse** — the journal's dedicated repository with permanent identifiers and preservation. Not a personal website or generic cloud link. 2. **Editorial verification.** The office reviews the package to confirm it can **reproduce the manuscript's tables and figures** and that the research process is documented well enough. Tre

What's inside
Steps it walks through
  1. When to trigger
  2. What APSR requires (verify current wording on the policy page)
  3. When data cannot be shared (exemption path)
  4. Package skeleton (what the verifiers should find)
  5. Verification dry run (before conditional acceptance, not after)
  6. Preregistration discipline (APSR-specific)
  7. Build-as-you-go checklist
  8. Anti-patterns
  9. Output format
  10. Supplementary resources
More from Awesome-Journal-Skills
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About this skill
What does the apsr-transparency-and-data-policy skill do?

Use when preparing the reproducibility / replication materials for an American Political Science Review (APSR) manuscript. APSR requires conditionally accepted authors to deposit a reproducibility package in the APSR Dataverse (Harvard Dataverse), which the editorial office verifies before publication. Covers quantitative and qualitative transparency and exemptions. Prepares the package; it does not waive requirements.

How do I install it?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill apsr-transparency-and-data-policy --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/Awesome-Journal-Skills, a repository with 909 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.

Keep going