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-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/aejpol-replication-package)<a href="https://agentmods.dev/skills/brycewang-stanford/awesome-journal-skills/aejpol-replication-package"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/aejpol-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/aejpol-replication-package"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/aejpol-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 | $0.00075 | $0.01291 |
| Opus 5 | $0.00037 | $0.00646 |
| Sonnet 5 | $0.00015 | $0.00258 |
| Haiku 4.5 | $0.00007 | $0.00129 |
Grade A, and why
aejpol-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 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 — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Replication Package — AEA Data Editor Compliance (aejpol-replication-package)
When to trigger
- A conditional acceptance / R&R asks for the data and code deposit
- You want to build the replication package as you go (recommended — the check is before publication)
- Some data are proprietary or restricted and you need a compliant access path
- The AEA Data Editor returned the package with required changes
The AEA reproducibility regime (检索于 2026-06；以官网为准)
AEJ: Policy is an AEA journal and follows the AEA Data and Code Availability Policy. For accepted papers, authors deposit data, code, and documentation in the AEA Data and Code Repository at openICPSR, and the AEA Data Editor (Lars Vilhuber) runs a reproducibility check before the paper is published, not after. A Data and Code Availability Statement is required. Build the deposit to pass on the first pass.
What the deposit must contain
- All code that produces every table, figure, and in-text number, organized so a single master script (
run_all) regenerates the results from the analysis data. - Data that can be shared, in the repository; for data that cannot, the exact provenance and access instructions (see restricted-data path below).
- A README following the AEA Data Editor's template: data sources and citations, data-availability statement, computational requirements (software + versions + packages), runtime, the map from code files to exhibits, and instructions to reproduce.
- Dependencies pinned: Stata
.adoversions, Rrenv.lock, Pythonrequirements.txt/condaenv; seeds set and reported for any simulation/bootstrap/randomization inference.
Restricted / proprietary data path
- State the Data Availability Statement clearly: which data are public, which are restricted, and how a replicator obtains the restricted parts (provider, application process, cost, approximate wait).
- Provide everything that can be shared (cleaning and analysis code, derived public extracts, synthetic or example data) so the Data Editor can verify the pipeline even without the raw restricted file.
- Confirm the access path is real and current — the Data Editor verifies it.
- Note any partial-reproducibility scope (e.g., one table from confidential data) in the README.
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 · 79 lines · 0 tokens per session scan A 45f6c6ecb534
aejpol-replication-package 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 1,291 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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