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 aejmic-literature-positioninggit 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/aejmic-literature-positioning)<a href="https://agentmods.dev/skills/brycewang-stanford/awesome-journal-skills/aejmic-literature-positioning"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/aejmic-literature-positioning/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/aejmic-literature-positioning"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/aejmic-literature-positioning.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 | $0.01151 |
| 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
aejmic-literature-positioning 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 — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Literature Positioning (aejmic-literature-positioning)
When to trigger
- The literature review lists papers but never says what is new here
- The contribution is stated relative to "the literature" in the abstract rather than to a specific closest result
- A referee may ask "how is this different from [Author, Year]?" and you do not have a crisp answer
- The claim of novelty is broader than the result actually supports
Positioning a theory result
For a theory-first journal, positioning is theorem-relative: identify the closest existing result and state precisely the delta — what your model relaxes, generalizes, characterizes, or overturns. Vague "we contribute to the literature on X" framing is the most common avoidable weakness. AEJ: Micro referees are subject-matter experts; they know the nearest theorem and will measure your delta against it.
How to find and state the delta
- Name the closest result, not a vague body of work: "Closest is [Author, Year], who shows P under assumptions A. We…"
- Classify the delta: a weaker assumption (more general), a new environment (broader scope), a full characterization where prior work had a special case, an impossibility where prior work conjectured possibility, or a mechanism prior work missed.
- Right-size the claim: state what you do not improve on, so the genuine advance is credible.
- Map the neighborhood: 3–6 anchor results, each with one clause saying how you relate. Avoid citation padding.
Sibling-literature discipline
Position against the theory frontier (mechanism design, IO theory, information economics, decision theory…), not against empirical applied-micro papers — that signals an AEJ: Applied framing. If your result has an empirical or experimental companion literature, cite it as motivation, not as the bar your contribution clears.
The delta taxonomy (which kind do you have?)
| Delta type | What it looks like | What the reader must see |
|---|---|---|
| Weaker assumption | Same conclusion, fewer/looser hypotheses | The dropped assumption named; that the old proof breaks without your argument |
| New environment | Old mechanism, richer setting (search, networks, dynamics) | What the new setting adds that the old result could not capture |
| Full characterization | Prior work had a special case or sufficiency only | Both directions; the boundary of the characterization |
| Impossibility / no-go | Prior work conjectured or assumed possibility | The exact obstruction and which primitive causes it |
| New mechanism | Same phenomenon, different economic force | Why the new force is the right explanation |
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 · 74 lines · 0 tokens per session scan A 307a7fa84dbc
aejmic-literature-positioning is a skill published in the GitHub repository brycewang-stanford/Awesome-Journal-Skills (1,289 stars, last pushed 26d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,151 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.
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