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-submissiongit 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-submission)<a href="https://agentmods.dev/skills/brycewang-stanford/awesome-journal-skills/aejmac-submission"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/aejmac-submission/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-submission"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/aejmac-submission.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 | $0.01149 |
| Opus 5.5 | $0.00000 | $0.00460 |
| Sonnet 5.5 | $0.00000 | $0.00230 |
| Haiku 4.5 | $0.00000 | $0.00115 |
Grade A, and why
aejmac-submission 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 — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Submission Preflight (aejmac-submission)
When to trigger
- "Submitting tomorrow" — last check before pressing submit on the AEA system
- Unsure which files, fees, and statements the AEA submission expects
- Confirming the format rules (PDF, length, abstract, JEL) are AEJ: Macro-compliant
- Confirming disclosure statements and data/code readiness are in order
Process facts (verified 2026-06; editor + fees re-verified 2026-06-22; re-confirm on the official AEA pages)
- AEJ: Macro is one of the AEA's four American Economic Journals (founded 2009; quarterly). Print ISSN 1945-7707 / Online ISSN 1945-7715. Submission is through the AEA submission system as PDF. Editor (re-verified 2026-06-22): Ayşegül Şahin (Princeton); coeditors Bianchi (Johns Hopkins), Kalemli-Özcan (Brown), Quadrini (USC) — re-verify the masthead on the AEA editors page before submission.
- Submission fee (membership- and income-scaled; 检索于 2026-06-22；以官网为准): AEA members US$200 (high-income country) / US$100 (middle-income) / US$0 (low-income); nonmembers US$300 / US$200 / US$0. Paid by credit card at submission. Papers rejected without review receive a 50% refund.
- Publication fee: US$15 per typeset page, assessed at page proofs (applies to papers submitted after Feb 1, 2024; 检索于 2026-06-22；以官网为准).
- Review: single-blind (author known to referee). JEL codes required. AI cannot be listed as an author.
- Data & code: governed by the AEA Data and Code Availability Policy; the AEA Data Editor runs a pre-publication reproducibility check; deposit at the AEA Data and Code Repository on openICPSR (see
aejmac-replication-package). Field experiments register in the AEA RCT Registry.
Preflight checklist
Format & length
- One PDF; first page has title, byline, and complete affiliations
- Abstract ≤100 words
- JEL codes and keywords included
- Within length guidance: ~40 pages (11pt, 1.5 spacing) / ~45 pages (12pt, 1.5 spacing), including figures, tables, references, and appendices (检索于 2026-06；以官网为准)
- Figures/tables legible after AEA two-column typesetting; IRFs have stated confidence bands
- Online appendix prepared for material beyond the page limit
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 69 lines · 0 tokens per session scan A 839e5c484bb8
aejmac-submission 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 1,149 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.
Other skills, from other repositories
alterlab-imaging-data-commons
Query and download public cancer imaging data from the NCI Imaging Data Commons (IDC) using the idc-index Python package, filtering by metadata, visualizing in-browser, and checking licenses, with no authentication required. Use when obtaining large-scale radiology (CT, MR, PET) or digital pathology DICOM datasets for…
alterlab-pyhealth
Develops, tests, and validates clinical machine learning models with the PyHealth 2.x healthcare AI toolkit. Use when working with electronic health records (EHR), clinical prediction tasks (mortality, readmission, length of stay, drug recommendation), medical coding systems (ICD, NDC, ATC, CCS), physiological signals…
alterlab-anndata
Build, slice, concatenate, read, and write AnnData annotated data matrices (obs, var, X, layers, obsm, uns) — the scverse data STRUCTURE, not an analysis pipeline. Use when creating or wrangling .h5ad/zarr files, managing cell and gene annotations, concatenating batches, or handling layers/obsm/backed-mode; for the…
alterlab-tiledbvcf
Store and query genomic variant data at scale with TileDB-VCF — ingest VCF/BCF into compressed TileDB arrays, add samples incrementally, run fast parallel region/sample queries, and export back to VCF. Use when managing population-genomics variant datasets that are too large for flat VCF, building joint variant…
alterlab-datamol
Wraps RDKit in a high-level, pandas-friendly datamol interface with sensible defaults for everyday drug discovery — SMILES/SDF loading into DataFrames, molecule standardization, descriptors, fingerprints, Butina clustering, 3D conformer generation, scaffold analysis, and parallel batch processing, returning native…
alterlab-eda
Exploratory data analysis (EDA) on a scientific data file — auto-detects the format, runs structure/quality/statistics checks, and writes a markdown EDA report with downstream recommendations. Use when asked to "explore", "analyze", "summarize", "profile", or "QC" a data file, or to understand its…