aejmic-tables-figures
Use when presenting results for an American Economic Journal: Microeconomics (AEJ: Micro) manuscript — propositions, numerical examples, schematic theory figures, and empirical/experimental tables. Builds exhibits to AEA house norms; it does not derive the results (see aejmic-theory-model).
Install / Use
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aejmic-tables-figuresInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
Development & EngineeringSupported Platforms
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Our assessment of aejmic-tables-figures
aejmic-tables-figures scores 85/100 on our quality scale, 2240th of 4,610 Development & Engineering skills we index (top 49%).
Its SKILL.md is 5.6 KB long, well organised into 13 sections with 1 code example: a solid amount of guidance for an agent.
With 1,158 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated 18 days ago, so aejmic-tables-figures is actively maintained.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
aejmic-tables-figures compared with similar skills
All 4 of these similar skills score higher than aejmic-tables-figures; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| aejmic-tables-figures (this skill)by brycewang-stanford | 85 | 1.2k | 18d ago | SKILL.md |
| ai-job-searchby MadsLorentzen | 100 | 44.8k | today | CLAUDE.md |
| claude-howtoby luongnv89 | 100 | 41.7k | 3d ago | CLAUDE.md |
| algorithmic-artby anthropics | 100 | 177.9k | 10d ago | SKILL.md |
| pptxby anthropics | 100 | 177.9k | 10d ago | SKILL.md |
Frequently asked questions
- How do I install aejmic-tables-figures?
- Run
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aejmic-tables-figures. The install tabs above show the steps for each supported agent. - Which AI agents does aejmic-tables-figures work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is aejmic-tables-figures safe to use?
- It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is aejmic-tables-figures still maintained?
- The repository was last updated 18 days ago, so aejmic-tables-figures is actively maintained.
Skill content
View source on GitHubname: aejmic-tables-figures description: Use when presenting results for an American Economic Journal: Microeconomics (AEJ: Micro) manuscript — propositions, numerical examples, schematic theory figures, and empirical/experimental tables. Builds exhibits to AEA house norms; it does not derive the results (see aejmic-theory-model).
Result Presentation: Propositions, Examples & Exhibits (aejmic-tables-figures)
When to trigger
- Propositions are buried in prose or stated imprecisely
- A numerical example would make an abstract result concrete but is missing or cluttered
- A schematic figure (timeline, type space, equilibrium region) would help but is not drawn
- (Applied/experimental) tables are dense or carry significance asterisks
Presenting a theory-first result
AEJ: Micro results are mostly propositions, characterizations, and numerical examples, not regression tables. The exhibit job is to make a formal result legible and concrete.
Propositions and theorems
- State each as a numbered, self-contained Proposition/Theorem/Lemma: a reader should grasp it without re-reading the model.
- Put the economic content first in surrounding prose ("Higher search costs raise equilibrium prices because…"), then the formal statement.
- Define every symbol at first use; keep notation consistent across statements; minimize ad-hoc subscripts.
Numerical examples (the AEJ: Micro workhorse)
- Use a small, transparent parameterization to illustrate the mechanism, not to "test" it — say which proposition it instantiates.
- Show the moving part: a table or plot of the key object (optimal mechanism, equilibrium strategy, welfare) as a primitive varies.
- Report enough to reproduce (parameter values, grid) — these go in the replication package.
Schematic theory figures
- Timelines for extensive-form games; type-space / signal partitions for information design; equilibrium-region plots in parameter space; best-response diagrams.
- Vector output; readable labels; no chartjunk. A figure should carry one idea.
Applied / experimental tables
- Three-line tables; report standard errors and confidence sets, not significance asterisks (AEA house norm for inference presentation).
- Place exhibits near their discussion; self-contained notes (sample, units, what each column is).
Choosing the right exhibit for the result
| What you want to convey | Best exhibit | |---|---| | A characterization holds | A numbered Proposition + an intuition sentence; rarely a table | | How an optimum moves with a primitive | A numerical-example plot (object vs. primitive) | | The structure of an equilibrium | A schematic (timeline, partition, region plot) | | A magnitude from estimation/experiment | A three-line table with SEs / coverage sets | | Model fit (structural) | Data vs. model overlay, not a fit statistic alone |
Pick one exhibit per idea. If a sentence does the job, do not add a figure; an AEJ: Micro theory paper can be exhibit-light without penalty.
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) ordid_summary_to_latexstraight from theresult_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.
Checklist
- [ ] Every formal result is a numbered, self-contained Proposition/Theorem/Lemma
- [ ] Economic content precedes the formal statement in prose
- [ ] Notation defined at first use and consistent across exhibits
- [ ] Numerical example states which proposition it illustrates and is reproducible
- [ ] Schematic figures carry one idea each; vector output; clean labels
- [ ] (Applied) tables report SEs / coverage sets, no significance asterisks
- [ ] Exhibits placed near discussion; notes self-contained
Anti-patterns
- A proposition stated only inside a paragraph, un-numbered and un-restated
- A numerical example with a dozen parameters and no statement of what it shows
- Overloaded figures (multiple unrelated panels, dense legends, chartjunk)
- Inconsistent or ad-hoc notation across statements
- Significance asterisks in an empirical/experimental table
Worked vignette (illustrative)
An information-design paper proves the sender-optimal signal is a two-message partition. The presentation: state Proposition 2 cleanly ("The sender-optimal signal partitions the state into {low, high} with cutoff x*"), precede it with the intuition (pooling above x* maximizes the receiver's action while preserving credibility), then a schematic figure of the state line with the cutoff and a small numerical example showing how x* moves with the sender's bias. No regression table, no asterisks — the exhibits make the mechanism visible.
Output format
【Formal results】numbered propositions/theorems, each self-contained? [Y/N]
【Economic-content-first prose】present for each? [Y/N]
【Numerical example】illustrates which proposition; reproducible? [Y/N]
【Schematic figures】one idea each; vector; clean labels? [Y/N]
【Applied tables】SEs/coverage, no asterisks? [Y/N or N/A]
【Next step】aejmic-writing-style
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Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
