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 food-papergit 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/food-paper)<a href="https://agentmods.dev/skills/pangenomeai/academic-skills-food-nutrition/food-paper"><img src="https://agentmods.dev/badge/skills/pangenomeai/academic-skills-food-nutrition/food-paper/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/food-paper"><img src="https://agentmods.dev/badge/skills/pangenomeai/academic-skills-food-nutrition/food-paper.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 | $0.00180 | $0.02417 |
| Opus 5 | $0.00090 | $0.01208 |
| Sonnet 5 | $0.00036 | $0.00483 |
| Haiku 4.5 | $0.00018 | $0.00242 |
Grade A, and why
food-paper 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 12d 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 — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Food-Paper — Whole-Process Manuscript System for Food & Nutrition Science
Take a food/nutrition study from data and idea to a submission-ready, journal- formatted manuscript, using a team of subagents for each stage of the research and writing process. Original work; architecture informed by open community paper-writing and Nature-style skills (see the repo README Acknowledgements).
First move — resolve the target journal (once)
Before drafting, load journal-selector/SKILL.md (a shared procedure, not an
installed skill) and follow it — it asks the author which journal
they are targeting (they may answer 'generic' for APA 7.0 defaults). Do this
once: record the resolved journal and its constraints and reuse them for every
subagent and stage — do not ask again. Re-run journal-selector only if the
author asks to switch journals, or reuse the choice already resolved by
food-pipeline/an earlier turn. The constraints govern structure, word/abstract
limits, reference style, and the figure spec passed to food-figure.
Modes
- full (default) — the whole pipeline: field → questions → data/stats → figures → argument → draft → polish → self-review.
- plan — Socratic planning of the paper chapter by chapter (no full draft).
- outline — detailed outline + evidence map only.
- section — draft or rewrite one section (intro/methods/results/discussion/abstract).
- stats — statistical analysis plan/execution guidance only.
- revise — revise against an existing review (a
food-reviewreport and/or margin comments on a Word file). Edit the original.docxwith Tracked Changes (do not start a fresh copy), resolving each comment. Insidefood-pipeline: update the existing Review & Response Report (.docx) in place with each item's response — no separate response letter. Standalone (real journal reviewers): produce a point-by-point response letter as a new Word document. All deliverables are.docx, never Markdown. Seereferences/revision-response.md. - format-convert — convert a draft to the target journal's structure + reference style; output Markdown, LaTeX (.tex), or DOCX, and build a PDF via Pandoc or
latexmk(seereferences/latex-guide.md). Yes — this skill can prepare and edit LaTeX drafts. When the source is a Word file, preserve EndNote/Zotero/Mendeley citation fields (references/word-field-codes.md) — don't flatten field codes into text. - polish — language editing to publication-quality English and removal of AI writing tells (
polisherrunsreferences/human-writing.md): inflated significance, "-ing" tack-ons, vague attribution ("studies have shown" → a real citation), stock AI vocabulary, "serves as" → "is", filler, hedge stacking, generic upbeat endings — then the two-pass check "what still reads as machine-written?". Keeps calibrated hedging, passive Methods, and journal-mandated form; never changes a number, claim scope, or citation. Good for non-native-English drafts and for anything AI helped write.
What ships with it
24 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- agents/argument_builder.md 1.3 KB
- agents/citation_manager.md 1.3 KB
- agents/data_curator.md 1.6 KB
- agents/draft_writer.md 3.8 KB
- agents/intake.md 2.0 KB
- agents/internal_reviewer.md 1.4 KB
- agents/literature_lead.md 1.2 KB
- agents/polisher.md 2.2 KB
- agents/question_framer.md 1.2 KB
- agents/statistician.md 2.0 KB
- agents/structure_architect.md 1.3 KB
- agents/viz_designer.md 1.5 KB
- references/apa7-quickref.md 1.7 KB
- references/declarations-guide.md 5.6 KB
- references/faithfulness-and-citation.md 3.6 KB
- references/human-writing.md 14 KB
- references/latex-guide.md 2.9 KB
- references/paper-structure.md 1.7 KB
- references/privacy-and-confidentiality.md 2.1 KB
- references/revision-response.md 6.4 KB
- references/statistics-reporting.md 1.7 KB
- references/word-field-codes.md 2.7 KB
- references/writing-quality-check.md 2.7 KB
- references/writing-style.md 3.4 KB
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.
- 12d ago First seen · 121 lines · 180 tokens per session scan A ef52cd88e1cd
food-paper is a skill published in the GitHub repository PangenomeAI/academic-skills-food-nutrition (31 stars, last pushed 12d ago), licensed MIT. It adds 180 tokens to every session and 2,417 once invoked, about $0.0009 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 2026-08-30.
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