Awesome Journal Skills is a collection of agent skill packs tailored to hundreds of academic journals across fields including economics, social science, medicine, science, and engineering. Researchers use the packs for tasks such as choosing topics, designing empirical strategies, preparing tables and figures, submitting papers, and responding to reviewers. The catalogue entries are the project's journal-specific skills and related plugins.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aejpol-tables-figuresgit clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-SkillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/brycewang-stanford/awesome-journal-skills/aejpol-tables-figures)<a href="https://agentmods.dev/skills/brycewang-stanford/awesome-journal-skills/aejpol-tables-figures"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/aejpol-tables-figures/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/brycewang-stanford/awesome-journal-skills/aejpol-tables-figures"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/aejpol-tables-figures.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00075 | $0.01397 |
| Opus 5 | $0.00037 | $0.00698 |
| Sonnet 5 | $0.00015 | $0.00279 |
| Haiku 4.5 | $0.00007 | $0.00140 |
Grade A, and why
aejpol-tables-figures scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tables & Figures — Exhibits that Carry the Policy Message (aejpol-tables-figures)
When to trigger
- Tables are dense, over-decorated with significance stars, or hard to read
- The paper lacks one exhibit a reader could take away as the policy result
- Figures show coefficients but not the policy-relevant magnitude or its uncertainty
- You are preparing the final exhibit set for an AEA submission
AEA / AEJ: Policy exhibit norms
- Report standard errors (or confidence intervals), not significance asterisks/boldface. Put SEs in parentheses below estimates; the reader judges significance from the SE/CI. This is the house convention to follow.
- Self-contained. Title and notes let an exhibit be read without the text: sample, units, estimator, clustering level, what is controlled, and what the number means in policy terms.
- Self-contained, not anonymized. Review is single-blind, so exhibits need not hide authorship; keep notes clean and neutral (avoid stray local file paths) for readability, not for blinding.
- Figures are the workhorse for policy communication: event-study plots with CIs, RDD plots with binned means and the fitted discontinuity, dose-response or cost-benefit curves with uncertainty bands. Vector output; ≥300 dpi raster only if unavoidable; readable greyscale.
The headline exhibit (AEJ: Policy-specific)
Every AEJ: Policy paper should have one exhibit a policymaker could screenshot: the policy effect in interpretable units with its welfare/cost-benefit reading where possible. Examples (illustrative formats):
- An event-study figure of the outcome around the reform, with the long-run effect annotated in policy units.
- A cost-benefit / MVPF figure: net cost per unit of outcome across policy variants, with bands.
- An incidence figure: who gains and who pays, by income/region group.
Table craft
- Three-line tables (
esttab/booktabs), no vertical rules; align decimals; consistent digits. - Lead column = the policy-relevant specification, not a kitchen-sink spec.
- Put the policy-relevant magnitude (elasticity, cost-per-X, MVPF) in the paper's units, not only a raw coefficient; add a row translating the coefficient into the policy number where natural.
- Sample size, mean of the dependent variable, and clustering level on every table.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 88 lines · 0 tokens per session scan A 404e243f3d97
aejpol-tables-figures is a skill published in the GitHub repository brycewang-stanford/Awesome-Journal-Skills (1,142 stars, last pushed 7d ago), licensed MIT. It adds 75 tokens to every session and 1,397 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-15.
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