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 PangenomeAI/academic-skills-food-nutrition --skill annu-rev-foodgit clone --depth 1 https://github.com/PangenomeAI/academic-skills-food-nutritionWrote 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/pangenomeai/academic-skills-food-nutrition/annu-rev-food)<a href="https://agentmods.dev/skills/pangenomeai/academic-skills-food-nutrition/annu-rev-food"><img src="https://agentmods.dev/badge/skills/pangenomeai/academic-skills-food-nutrition/annu-rev-food/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/pangenomeai/academic-skills-food-nutrition/annu-rev-food"><img src="https://agentmods.dev/badge/skills/pangenomeai/academic-skills-food-nutrition/annu-rev-food.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00105 | $0.00766 |
| Opus 5 | $0.00053 | $0.00383 |
| Sonnet 5 | $0.00021 | $0.00153 |
| Haiku 4.5 | $0.00011 | $0.00077 |
Grade A, and why
annu-rev-food 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 8d 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 — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Annual Review of Food Science and Technology — Author Guideline Skill
Publisher: Annual Reviews · ISSN: 1941-1413 · Source: Journal page · Verified: 2026-07 (confirm at source).
Aims & scope
Authoritative, invited critical reviews across food science and technology: food chemistry, microbiology, engineering, safety, nutrition, and emerging technologies. Articles are commissioned by the Editorial Committee — unsolicited submissions are generally not accepted; propose topics to the editors first.
Article type
Review articles only (comprehensive, synthesis-driven, forward-looking). Typical length is substantial (often ~8,000–10,000 words); confirm the assigned length with the production editor.
Manuscript structure
Title → Authors & affiliations → Abstract → Keywords → Introduction → thematic sections with descriptive headings → Summary Points / Future Issues (Annual Reviews signature elements) → Disclosure Statement → Acknowledgments → Literature Cited. Provide "Summary Points" and "Future Issues" bullet lists.
- Abstract: ~150–250 words.
- Keywords: ~6–8.
- Disclosure statement: required (funding, affiliations, potential bias).
Reference style
Author–date (name–year), Annual Reviews style. In-text (Author & Author 2023); "Literature Cited" list alphabetical. Article titles included.
Example:
Author AB, Author CD. 2023. Title of the review article. Annu. Rev. Food Sci. Technol. 14:123–45
Figures & tables
Figures ≥300 dpi (line art higher); Annual Reviews uses professional redraw — supply clear, editable source files and permissions for any reused figures; RGB/CMYK per production; editable tables; cite in order.
Submission checklist
- Topic pre-agreed/invited by the Editorial Committee · [ ] Summary Points + Future Issues lists
- Abstract ~150–250 words · [ ] 6–8 keywords · [ ] Disclosure statement
- Author–date (Annual Reviews) Literature Cited · [ ] Permissions for reused figures
- Figures ≥300 dpi, editable source provided
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.
- 8d ago First seen · 59 lines · 105 tokens per session scan A a65413e15de3
annu-rev-food is a skill published in the GitHub repository PangenomeAI/academic-skills-food-nutrition (31 stars, last pushed 12d ago), licensed MIT. It adds 105 tokens to every session and 766 once invoked, about $0.0005 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 2026-09-04.
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