A skill your agent uses when building or revising the exhibits of an American Economic Journal: Applied Economics (AEJ: Applied) manuscript so the main causal result is legible in one table or…

MITAuto-check passedResearch & Science

Install Aeja Tables Figures

skills CLI
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aeja-tables-figures -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install brycewang-stanford/Awesome-Journal-Skills aeja-tables-figures --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/AEJ-Applied-Economics-Skills/skills/aeja-tables-figures .claude/skills/aeja-tables-figures && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
aeja-tables-figures
GitHub stars
1.2k
Token cost
~1.6k tokens
SKILL.md length
758 words
Files
1
Skills in repo
2,387
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when building or revising the exhibits of an American Economic Journal: Applied Economics (AEJ: Applied) manuscript so the main causal result is legible in one table or…

  • Works in 5 steps: One table for the headline. Table 1 (or… → Standard errors always, stars optional.… → Self-contained notes. Each exhibit's… → …
  • Figure and respects AEA house presentation norms
  • SKILL.md covers When to trigger, The AEJ: Applied exhibit bar, Exhibit craft and Execution bridge (StatsPAI /…, plus 5 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Aeja Tables Figures is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when building or revising the exhibits of an American Economic Journal: Applied Economics (AEJ: Applied) manuscript so the main causal result is legible in one table or figure and respects AEA house presentation norms. Formats exhibits; it does not establish the result (aeja-identification / aeja-robustness) or write the surrounding prose.

Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Research & Science, covering Econometrics and empirical research. The repository describes itself as: Journal-specific Claude Code/Codex skill packs covering mainstream journals — AER, QJE, Nature, Cell, 管理世界, 经济研究 & 200+ more — your fast track to getting published. | 覆盖主流期刊的… The licence is MIT.

When your agent uses it

  • Figure and respects AEA house presentation norms
  • Tasks that involve Econometrics and empirical research

Example prompts

  • “/aeja-tables-figures”

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. One table for the headline. Table 1 (or 2) should let a referee read the main causal estimate, its SE, and N without flipping pages.
  2. Standard errors always, stars optional. AEA permits stars, but SEs in parentheses are the load-bearing object; report the…
  3. Self-contained notes. Each exhibit's note states sample, units, clustering level, controls, and what an asterisk (if used) means — a…
  4. Figures carry identification. Event-study leads, RD continuity, and balance are more convincing as figures than as prose; make them…
  5. Right precision. Two to three significant figures; do not report coefficients to five decimals.

What it can do on your machine

Read from SKILL.md and the folder at commit 932eb23. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Aeja Tables Figures loads about 1.6k tokens when it runs. Until then it costs about 91 tokens; SKILL.md has 758 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~91
When it runs · the whole SKILL.md, loaded when a task matches
~1.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from brycewang-stanford/Awesome-Journal-Skills at commit 932eb23, republished under its MIT licence (© brycewang-stanford). 758 words, ~1,606 tokens.

Download SKILL.mdSave it as .claude/skills/aeja-tables-figures/SKILL.md (or your agent's skills folder).
name
aeja-tables-figures
description
Use when building or revising the exhibits of an American Economic Journal: Applied Economics (AEJ: Applied) manuscript so the main causal result is legible in one table or figure and respects AEA house presentation norms. Formats exhibits; it does not establish the result (aeja-identification / aeja-robustness) or write the surrounding prose.

Tables & Figures (aeja-tables-figures)

When to trigger

  • The main result is settled and must be made readable at a glance
  • Tables are dense, over-decimaled, or bury the headline coefficient
  • An event-study / RD / first-stage plot needs to carry the identification visually
  • You are preparing exhibits for submission and want them AEA-house-style compliant

The AEJ: Applied exhibit bar

At AEJ: Applied the main causal estimate should be findable in seconds and every exhibit should earn its place. AEA house style permits significance stars but expects standard errors in parentheses, clear notes that make each exhibit self-contained, and clean figures over chartjunk. Lead with the design's signature visual — the event-study plot, the RD scatter, or the balance table — because at this journal the picture of the identification is half the persuasion.

ExhibitWhat it must showCommon failure
Main results tableheadline coefficient, SE in parentheses, N, controls indicated, dependent-var meantoo many columns; no SEs; over-precision
Balance table (RCT)baseline means by arm, differences, joint testmissing joint test; no attrition row
Event-study figureleads + lags, CIs, reference period, flat pre-trends visibleno CIs; ambiguous reference period
RD figurebinned scatter + fitted lines, bandwidth, densityoverfit polynomial; no density panel
First-stage / IV tablefirst-stage F, exclusion logic in notesweak first stage hidden
Robustness exhibitpoint-estimate stability across checksa starred wall with no map

Exhibit craft

  1. One table for the headline. Table 1 (or 2) should let a referee read the main causal estimate, its SE, and N without flipping pages.
  2. Standard errors always, stars optional. AEA permits stars, but SEs in parentheses are the load-bearing object; report the dependent-variable mean so magnitudes are interpretable.
  3. Self-contained notes. Each exhibit's note states sample, units, clustering level, controls, and what an asterisk (if used) means — a referee should not need the text to read the table.
  4. Figures carry identification. Event-study leads, RD continuity, and balance are more convincing as figures than as prose; make them publication-clean (vector output, readable fonts, CIs shown).
  5. Right precision. Two to three significant figures; do not report coefficients to five decimals.

Execution bridge (StatsPAI / Stata MCP)

Generate exhibits from the fitted result, not by retyping numbers (the usual source of body-vs-appendix drift). Full map: execution-with-mcp.

  • Tables: etable (multi-model columns) or did_summary_to_latex straight from the result_id — one variable definition, one set of numbers, body and appendix in sync.
  • Figures: plot_from_result / enhanced_event_study_plot / event_study_table — axis units and the SE/clustering note baked in.
  • Every note names the estimator + clustering (from the result's diagnostics) and states the magnitude in interpretable units.

See a full fitted-result → exhibit chain in the JF execution walkthrough.

Show full SKILL.md (325 more words)Show less

Checklist

  • Main causal estimate readable in one table: coefficient, SE in parentheses, N, dep-var mean, controls flagged
  • Standard errors reported everywhere; clustering level stated in notes; stars (if used) defined
  • Identification figure present (event-study with CIs / RD with density / balance with joint test)
  • Notes make every exhibit self-contained (sample, units, clustering, controls)
  • Figures are clean vector output, legible, no chartjunk, consistent scales
  • Precision sensible (2–3 sig figs); no redundant exhibits

Anti-patterns

  • A main results table with 12 columns where the headline coefficient is hard to find
  • Reporting stars or t-stats but omitting standard errors / clustering level
  • Over-precision (coefficients to 5 decimals) implying false accuracy
  • An event-study plot with no confidence intervals or unclear reference period
  • An RD figure with a high-order global polynomial that manufactures a jump
  • Exhibit notes that force the reader back to the text to interpret the table

Worked vignette (illustrative)

A draft's Table 4 has 12 columns sweeping every control combination, and the headline coefficient is buried in column 9 with only t-statistics shown. The AEJ: Applied fix: promote the preferred specification to a two-panel Table 2 — Panel A the main estimate (coefficient 3.1, s.e. 0.9 in parentheses, N, dependent-var mean 0.44), Panel B the same with the full controls — and move the sweep to the online appendix. Add Figure 1, the event-study with confidence intervals and a clearly marked reference period, so the identification is visible before the reader reaches the table. The result is now findable in seconds.

Referee pushback mapped to the exhibit fix

  • "I cannot find your main estimate." → One headline table with the coefficient, SE, N, and dep-var mean; everything else demoted to the appendix.
  • "Where are the standard errors / what is the clustering?" → SEs in parentheses everywhere; clustering level and (if used) star meaning stated in the self-contained note.
  • "This RD jump looks like an artifact of the polynomial." → Replace the global high-order fit with a local-linear binned scatter plus a density panel.

Output format

【Headline exhibit】one table/figure carrying the main estimate? [Y/N]
【Inference shown】SEs in parentheses + clustering level in notes? [Y/N]; stars defined if used
【Identification figure】event-study / RD / balance present with CIs? [Y/N]
【Self-contained notes】sample/units/clustering/controls in every note? [Y/N]
【Figure quality】vector, legible, no chartjunk? [Y/N]
【Next step】aeja-writing-style

© brycewang-stanford, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in AEJ-Applied-Economics-Skills/skills/aeja-tables-figures of brycewang-stanford/Awesome-Journal-Skills.

Open the folder on GitHubat commit 932eb23

Compare with similar skills

Aeja Tables Figures next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Aeja Tables Figures compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Aeja Tables Figures this skillbrycewang-stanford/Awesome-Journal-Skills1.2k—~1.6kAutomated safety check: PassMIT
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Stata C Pluginsdylantmoore/stata-skill2911 repos~5.8kAutomated safety check: PassCustom licence
Example Datasetspymc-labs/CausalPy1.2k—~587Automated safety check: PassApache-2.0
Stata AuditSepineTam/mcp-for-stata264—~1.2kAutomated safety check: PassAGPL-3.0
Stata Skill Contributordylantmoore/stata-skill2911 repos~2.4kAutomated safety check: PassCustom licence

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Questions about Aeja Tables Figures

What does Aeja Tables Figures do?

A skill your agent uses when building or revising the exhibits of an American Economic Journal: Applied Economics (AEJ: Applied) manuscript so the main causal result is legible in one table or…. Aeja Tables Figures is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when building or revising the exhibits of an American Economic Journal: Applied Economics (AEJ: Applied) manuscript so the main causal result is legible in one table or figure and respects AEA house presentation norms.

When should I use Aeja Tables Figures?

Aeja Tables Figures fits situations like: figure and respects AEA house presentation norms; tasks that involve Econometrics and empirical research.

How do I install Aeja Tables Figures in Claude Code?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aeja-tables-figures -a claude-code`. Or copy the skill folder (AEJ-Applied-Economics-Skills/skills/aeja-tables-figures in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/aeja-tables-figures in your project. Claude Code loads it when a task matches its description.

How do I install Aeja Tables Figures in Codex?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aeja-tables-figures -a codex`. Or copy the skill folder (AEJ-Applied-Economics-Skills/skills/aeja-tables-figures in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/aeja-tables-figures in your project. Codex loads it when a task matches its description.

Can I use Aeja Tables Figures in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aeja-tables-figures -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/aeja-tables-figures, .gemini/skills/aeja-tables-figures, .github/skills/aeja-tables-figures and .opencode/skills/aeja-tables-figures in your project.

What does Aeja Tables Figures need to run?

SKILL.md names no scripts, command-line tools or credentials: Aeja Tables Figures is instructions for the agent only.

Does Aeja Tables Figures access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Aeja Tables Figures safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Aeja Tables Figures use?

Aeja Tables Figures is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Aeja Tables Figures use?

About 1.6k tokens (SKILL.md is roughly 6.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Aeja Tables Figures?

Skills that share tags, products or a category with Aeja Tables Figures: Stata (dylantmoore/stata-skill, 291 stars), Stata C Plugins (dylantmoore/stata-skill, 291 stars), Example Datasets (pymc-labs/CausalPy, 1.2k stars) and Stata Audit (SepineTam/mcp-for-stata, 264 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Aeja Tables Figures?

brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,231 GitHub stars. The repository holds 2,387 skills in this directory. The repository was last updated on September 27, 2026.

Source: brycewang-stanford/Awesome-Journal-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.