Agent skill · Code Review & Quality

pubar-tables-figures

Use when building tables and figures for a Public Administration Review (PAR) manuscript so exhibits are self-contained, accessible, and communicate effect magnitude to scholars and practitioners alike. PAR excludes tables/figures/appendices from the 8,000-word count, but exhibits still must earn their space. Designs exhibits; it does not run the analysis.

brycew6m878★ · +32/wk · 1 repos on radarProfile →
claude-codeMIT
Install
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill pubar-tables-figures --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: Public-Administration-Review-Skills/skills/pubar-tables-figures/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

# Tables & Figures (pubar-tables-figures) Exhibits are where an expert reviewer checks whether the result is real — and where a practitioner reads the magnitude that drives your **Evidence for Practice**. At PAR the word count *excludes* tables, figures, charts, and appendices (检索于 2026-06;以官网为准), so the constraint is clarity, not word budget: every exhibit must communicate a magnitude with its uncertainty, fast. ## When to trigger - Designing the main results table/figure or a key descriptive exhibit - Deciding what belongs in the article vs. an online appendix/supplement - A reviewer found an exhibit unclear, mislabeled, or non-self-contained - Translating a coefficient into something a public manager can read ## Principles 1. **Self-contained.** A reader should understand each exhibit from its title, axis/column labels, and note alone. State units, sample, N, the estimator, and what the estimate is. 2. **Figures over dense tables for effects.** Coefficient/forest plots, marginal-effects and predicted-probability plots, event-study and RD plots communicate magnitude and uncertainty better than a wall of coefficients. Show intervals — a practitioner needs the effect size, not star

What's inside
Steps it walks through
  1. When to trigger
  2. Principles
  3. PA-specific exhibits
  4. Execution bridge (StatsPAI / Stata MCP)
  5. Anti-patterns
  6. Output format
  7. Referee-pushback patterns and the PAR fix
  8. Calibration anchors (hedged)
  9. Supplementary resources
More from Awesome-Journal-Skills
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About this skill
What does the pubar-tables-figures skill do?

Use when building tables and figures for a Public Administration Review (PAR) manuscript so exhibits are self-contained, accessible, and communicate effect magnitude to scholars and practitioners alike. PAR excludes tables/figures/appendices from the 8,000-word count, but exhibits still must earn their space. Designs exhibits; it does not run the analysis.

How do I install it?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill pubar-tables-figures --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