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-writing-stylegit 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-writing-style)<a href="https://agentmods.dev/skills/brycewang-stanford/awesome-journal-skills/aejpol-writing-style"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/aejpol-writing-style/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-writing-style"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/aejpol-writing-style.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 | $0.00063 | $0.01185 |
| Opus 5 | $0.00032 | $0.00593 |
| Sonnet 5 | $0.00013 | $0.00237 |
| Haiku 4.5 | $0.00006 | $0.00119 |
Grade A, and why
aejpol-writing-style 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 — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Writing Style — From Estimate to Policy Takeaway (aejpol-writing-style)
When to trigger
- The intro buries the policy question under data or method
- The abstract reports a coefficient but no policy lesson
- The paper has a clean estimate but no sentence a policymaker could act on — or it overclaims
- You are polishing for submission and need AEA house tone
Late-stage polish: do not rewrite the intro until identification (
aejpol-identification), the welfare bridge (aejpol-theory-model), and robustness (aejpol-robustness) have settled.
The AEJ: Policy introduction arc
Policy question → why credible identification is hard → the design that delivers it → headline causal estimate (with SE/CI) → welfare / cost-benefit / distributional reading → concrete, calibrated policy lesson → brief roadmap.
The distinctive moves vs. a general applied-micro intro:
- Open with the policy question, not the dataset or estimator. A non-specialist AEA reader should know within two sentences what policy is at stake and why the answer matters.
- Put the headline estimate, with its uncertainty, on page one — in policy-interpretable units (a percentage-point effect, a cost-per-outcome), never an asterisk.
- Translate into a policy takeaway — the cost-benefit / MVPF / incidence reading — and state it as the contribution.
- Calibrate the claim. Say exactly what the estimand is, for whom, and the conditions under which the lesson holds. The credibility of an AEJ: Policy paper rests as much on not overclaiming as on the estimate.
Translating estimates into policy language without overclaiming
- Convert coefficients into decision-relevant quantities ("a $1,000 expansion raises take-up by X and costs $Y per additional recipient") rather than leaving them as elasticities.
- Tie magnitude to a benchmark a policymaker recognizes (the program's budget, the status-quo level, a comparable policy).
- Hedge precisely, not vaguely: state the population the estimate applies to, the time horizon, and the assumptions the welfare reading needs. Replace "this shows policy X is good" with "for this population and horizon, the marginal dollar of X returns $Z, assuming [stated condition]."
- Separate what the data show (the causal estimate) from what the framework adds (the welfare reading) so a referee can grant one without the other.
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 · 71 lines · 0 tokens per session scan A eb858455c4cc
aejpol-writing-style is a skill published in the GitHub repository brycewang-stanford/Awesome-Journal-Skills (1,142 stars, last pushed 7d ago), licensed MIT. It adds 63 tokens to every session and 1,185 once invoked, about $0.0003 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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