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-identificationgit 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-identification)<a href="https://agentmods.dev/skills/brycewang-stanford/awesome-journal-skills/aejpol-identification"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/aejpol-identification/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-identification"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/aejpol-identification.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 | $0.01579 |
| Opus 5.5 | $0.00000 | $0.00632 |
| Sonnet 5.5 | $0.00000 | $0.00316 |
| Haiku 4.5 | $0.00000 | $0.00158 |
Grade A, and why
aejpol-identification 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 — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Identification — Credible Policy Evaluation (aejpol-identification)
When to trigger
- The causal effect of a policy rests on OLS + controls, or TWFE on staggered policy adoption
- A reform / threshold / experiment exists but the design's assumptions are not pinned down
- A referee questions whether the estimated effect is really caused by the policy
- You are unsure the design clears AEJ: Policy's credible-causal-evidence bar
The AEJ: Policy identification bar
AEJ: Policy is an empirical policy journal: the effect attributed to the policy must be credibly causal, the estimand must be the policy-relevant one, and the design must survive the obvious confound that the policy was not random. The policy variation is the research design — name it explicitly (a reform date, an eligibility cutoff, a formula kink, a randomized rollout) and defend the assumption that makes it causal. Report standard errors (no significance asterisks; see aejpol-tables-figures) and make the design reproducible for the AEA Data Editor.
Design paths
Path A: DID / event study (reforms, staggered policy adoption)
- With staggered adoption move beyond TWFE (Callaway–Sant'Anna, Sun–Abraham, Borusyak–Jaravel–Spiess, de Chaisemartin–D'Haultfœuille); report a Goodman-Bacon decomposition to show the bias TWFE would induce.
- Show a clean event study with pre-period leads flat around zero; do not assert parallel trends, demonstrate it (and probe with Rambachan–Roth honest-DID where pre-trends are imperfect).
- Define the policy-relevant estimand (ATT on treated jurisdictions; weight by population/exposure if the policy lesson requires it).
- Cluster at the policy-assignment level (often state/jurisdiction); address few-cluster issues (wild-cluster bootstrap).
Path B: IV / instrumented policy exposure
- Strong first stage; with weak instruments use Anderson–Rubin / weak-IV-robust sets and report the effective F.
- Defend the exclusion restriction in institutions and theory, not just statistically; argue the instrument affects outcomes only through the policy channel.
- State the LATE complier population and whether it is the policy-relevant margin.
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 · 95 lines · 0 tokens per session scan A 17a9bf26712c
aejpol-identification is a skill published in the GitHub repository brycewang-stanford/Awesome-Journal-Skills (1,372 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,579 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.
aejpol-identification compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| aejpol-identificationbrycewang-stanford/Awesome-Journal-Skills | Skill | 1.4k | 1mo ago | MIT | A | 0 | Claude Code |
| alterlab-pyhealthAlterLab-IEU/AlterLab-Academic-Skills | Skill | 85 | yesterday | MIT | A | 132 | Claude Code |
| alterlab-imaging-data-commonsAlterLab-IEU/AlterLab-Academic-Skills | Skill | 85 | yesterday | MIT | A | 90 | Claude Code |
| alterlab-datamolAlterLab-IEU/AlterLab-Academic-Skills | Skill | 85 | yesterday | MIT | A | 120 | Claude Code |
| alterlab-edaAlterLab-IEU/AlterLab-Academic-Skills | Skill | 85 | yesterday | MIT | A | 258 | Claude Code |
| alterlab-biorxivAlterLab-IEU/AlterLab-Academic-Skills | Skill | 85 | yesterday | MIT | A | 69 | Claude Code |
| alterlab-clinicaltrialsAlterLab-IEU/AlterLab-Academic-Skills | Skill | 85 | yesterday | MIT | A | 76 | Claude Code |