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 amann-evidence-standardsgit 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/amann-evidence-standards)<a href="https://agentmods.dev/skills/brycewang-stanford/awesome-journal-skills/amann-evidence-standards"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/amann-evidence-standards/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/amann-evidence-standards"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/amann-evidence-standards.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 | $0.00085 | $0.01482 |
| Opus 5.5 | $0.00034 | $0.00593 |
| Sonnet 5.5 | $0.00017 | $0.00296 |
| Haiku 4.5 | $0.00009 | $0.00148 |
Grade A, and why
amann-evidence-standards 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 — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Evidence Standards — Appraisal & Balance (amann-evidence-standards)
When to trigger
- The framework is set and you are filling cells with the literature
- The field has rival schools, a live controversy, or conflicting empirical results
- You must decide whether to cite everything or curate, and how to weigh disagreeing studies
- You are a contributor to this literature and worry the review tilts toward your own work
At Annals you are the field's reviewer-of-record
An Annals review carries no estimates of its own — but it is not therefore neutral. The "attitude" is disciplined critical appraisal: you judge how good the cumulative evidence is, reconcile conflicts by credibility, and state where the field's confidence is and is not warranted. This is the review-craft replacement for primary-research robustness checks: you are appraising other people's designs, not defending your own.
Completeness vs. selectivity: the Annals contract
A review must be comprehensive in coverage yet selective in emphasis — long (~50 pages) but not an inventory. Resolve the tension by tiering the corpus:
| Tier | Treatment |
|---|---|
| Foundational / field-defining | discussed in text — what it established and its limits |
| Important contributions | grouped and weighed within the framework's cells; cited with their finding |
| Confirmatory / incremental | cited in clusters ("see also …") to show coverage without bloating prose |
| Tangential | cited only where it bears on a specific claim |
Comprehensiveness is proven by the citation set (the saturation log from amann-literature-synthesis); selectivity is exercised in the prose. Equal-length summaries of every paper abdicate the editorial judgment that is the review's value.
Weighing conflicting evidence (not vote-counting)
Management findings conflict constantly. Reconcile them by why they differ, never by tally:
- Weigh by credibility. Design strength (causal vs. correlational), sample, measurement validity, replication, and publication-bias risk — not "9 studies positive, 4 negative."
- Separate by construct and context. Studies often disagree because they measure different constructs or run in different settings; surface that rather than forcing a false consensus.
- Flag the cumulative-evidence quality. State plainly where the evidence is strong, mixed, or thin — and where apparent consensus rests on a few non-independent studies.
- Name what would settle it. For a live debate, specify the study design that would resolve it (this seeds the agenda).
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 · 87 lines · 85 tokens per session scan A 00c44873f563
amann-evidence-standards is a skill published in the GitHub repository brycewang-stanford/Awesome-Journal-Skills (1,289 stars, last pushed 26d ago), licensed MIT. It adds 85 tokens to every session and 1,482 once invoked, about $0.0003 per session on Opus 5.5. 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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