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-literature-synthesisgit 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-literature-synthesis)<a href="https://agentmods.dev/skills/brycewang-stanford/awesome-journal-skills/amann-literature-synthesis"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/amann-literature-synthesis/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-literature-synthesis"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/amann-literature-synthesis.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 | $0.00080 | $0.01377 |
| Opus 5.5 | $0.00032 | $0.00551 |
| Sonnet 5.5 | $0.00016 | $0.00275 |
| Haiku 4.5 | $0.00008 | $0.00138 |
Grade A, and why
amann-literature-synthesis 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 — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Literature Synthesis Methodology (amann-literature-synthesis)
When to trigger
- The proposal was invited and it is time to read the field thoroughly and transparently
- Reading feels unsystematic; you fear missing streams a referee could name
- You have many papers but no way to code, compare, or reconcile them
- You must decide whether this review is narrative, systematic, or bibliometric in method
At Annals you synthesize — you do not run primary research
The folder name says "data analysis," but an Annals review reports no data of its own. Your "analysis" is the systematic appraisal and integration of a literature. The credibility of the whole review rests on the reader's belief that you read everything that matters and coded it consistently. Build coverage as a transparent process, not from memory.
Choose the integration method first
| Method | What it does | Best when |
|---|---|---|
| Narrative / integrative review | reads, interprets, and reorganizes the literature into a new framework | the contribution is conceptual integration (Annals' core mode) |
| Systematic review | a pre-specified, reproducible search-and-screen protocol; transparent inclusion | the field is large and you must prove comprehensive, unbiased coverage |
| Bibliometric / meta-analytic | co-citation, co-word, or quantitative effect-size synthesis | the contribution is structural (intellectual map) or a cumulative magnitude estimate |
Most Annals reviews are integrative narrative with a systematic backbone: a transparent search establishes coverage, and the narrative does the reorganizing. Bibliometrics can support the framework but rarely replaces the interpretive contribution.
Building coverage to saturation
- Seed set. Start from the proposal's key references and the field's canonical pieces.
- Transparent search. Search the major databases (Web of Science, Scopus, EBSCO/Business Source, Google Scholar) by topic keywords; record terms, databases, dates, and counts so the "Review scope and process" claims are auditable.
- Forward + backward snowball. Backward: each paper's reference list. Forward: who cites the seeds. Iterate until new searches stop turning up unseen important work (saturation).
- Inclusion / exclusion logic, stated. Define what is in and out (time window, journal tier, theoretical vs. empirical, allied fields) and apply it consistently — referees ask "why did you omit X?"
- Working papers + adjacent literatures. A current review must reach recent work and the bordering fields (organizational psychology, sociology) the literature draws on, or it reads stale or siloed.
- Saturation log. Record when each search stopped yielding new must-cite work — this is your evidence of comprehensiveness for
amann-evidence-standardsand the referees.
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 · 89 lines · 80 tokens per session scan A 1cd8df13bb3c
amann-literature-synthesis is a skill published in the GitHub repository brycewang-stanford/Awesome-Journal-Skills (1,289 stars, last pushed 26d ago), licensed MIT. It adds 80 tokens to every session and 1,377 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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