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 aejmac-replication-packagegit 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/aejmac-replication-package)<a href="https://agentmods.dev/skills/brycewang-stanford/awesome-journal-skills/aejmac-replication-package"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/aejmac-replication-package/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/aejmac-replication-package"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/aejmac-replication-package.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 | $0.00000 | $0.01191 |
| Opus 5.5 | $0.00000 | $0.00476 |
| Sonnet 5.5 | $0.00000 | $0.00238 |
| Haiku 4.5 | $0.00000 | $0.00119 |
Grade A, and why
aejmac-replication-package 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 1mo 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 — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Replication Package (aejmac-replication-package)
When to trigger
- A paper is heading toward conditional acceptance and the AEA Data Editor check is next
- You have simulation/calibration code but have never packaged it for a reviewer to run
- The data include a restricted/proprietary source (confidential micro data, licensed series)
- You want to build the package as you go rather than scrambling at acceptance
The AEA reproducibility regime (verified 2026-06; re-confirm on the official AEA pages)
- Governed by the AEA Data and Code Availability Policy. Conditionally accepted papers undergo a review by the AEA Data Editor (Lars Vilhuber) before publication, including reproducibility checks and verification of the information provided.
- Deposit in the AEA Data and Code Repository on openICPSR (use is strongly encouraged; other trusted repositories may be allowed with Data Editor approval). Materials are posted with the article.
- Code scope is broad — and this is the macro-critical point: the policy covers data cleaning and "estimation, simulation, model solution, and visualization" code. For AEJ: Macro, the DSGE/HANK solver, the calibration/estimation routines, and the simulation code must all be in the package, not only the regression scripts.
- Restricted-access data: exceptions exist for confidential / copyrighted / agreement-restricted data; authors must preserve materials 5+ years, provide reasonable replication assistance, make the code public even when the data cannot be, and disclose data sources. State any such request to the Data Editor.
- Field experiments must be registered in the AEA RCT Registry.
Building a macro-grade package
Directory & master script
- A clear tree:
/data(raw + analysis),/code,/output(tables + figures),/docs. - One master script (
run_all) that regenerates every table and figure from raw inputs in order, including the model solution and simulation steps. - A README following the AEA template: data sources and access, software + versions, hardware, expected runtime, and a map from each exhibit to the script that makes it.
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.
- 1mo ago First seen · 72 lines · 0 tokens per session scan A 0e89fceeed4f
aejmac-replication-package is a skill published in the GitHub repository brycewang-stanford/Awesome-Journal-Skills (1,264 stars, last pushed 19d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,191 tokens. 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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