Agent skill · Code Review & Quality

jedpsych-tables-figures

Use when building tables and figures for a Journal of Educational Psychology manuscript. JEP uses APA 7th-edition style and expects exhibits that report multilevel/SEM model results, effect sizes with uncertainty, and growth trajectories clearly, and that are anonymized for masked review. 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 jedpsych-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: 7 KB
Bundled scripts: none
Path: Journal-of-Educational-Psychology-Skills/skills/jedpsych-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 (jedpsych-tables-figures) In the Journal of Educational Psychology, exhibits must carry the quantitative argument for **nested, model-based** results: multilevel/SEM estimates, **effect sizes with confidence intervals**, mediation paths, and growth trajectories. They follow **APA 7th-edition** conventions and — because review is **masked** — must not reveal author identity (school names, project sites, identifying acknowledgments). A good JEP figure makes the learning effect, its uncertainty, and its mechanism legible at a glance. ## When to trigger - Designing the main results table/figure (model results, mediation, growth) - Deciding what goes in the article vs. online supplemental material - A reviewer found an exhibit unclear, non-APA, or identity-revealing - Visualizing trajectories, variance components, and uncertainty (not just means) ## Principles 1. **Show model results, effect sizes, and uncertainty.** Tables report estimates with standard errors and **confidence intervals**, variance components/ICC for multilevel models, and fit indices for SEM — not just stars. Figures display trajectories or effects with CIs, not bare bar-of-means. 2. **Self-containe

What's inside
Steps it walks through
  1. When to trigger
  2. Principles
  3. Worked micro-example — the main results exhibits (illustrative)
  4. Exhibit triage — article vs. online supplemental material
  5. Exhibit-stage reviewer pushback and the venue fix
  6. Exhibit calibration anchors
  7. Execution bridge (StatsPAI / Stata MCP)
  8. Anti-patterns
  9. Output format
  10. Supplementary resources
More from Awesome-Journal-Skills
All skills →
About this skill
What does the jedpsych-tables-figures skill do?

Use when building tables and figures for a Journal of Educational Psychology manuscript. JEP uses APA 7th-edition style and expects exhibits that report multilevel/SEM model results, effect sizes with uncertainty, and growth trajectories clearly, and that are anonymized for masked review. Designs exhibits; it does not run the analysis.

How do I install it?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jedpsych-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