food-paper

food-paper is a skill for Claude Code from PangenomeAI/academic-skills-food-nutrition. It costs 180 tokens per session (2,417 once invoked), scanned A, original, MIT.

A multi-step manuscript workflow for food and nutrition research, from understanding the field and analyzing data to writing, formatting, and reviewing a paper for a journal.

In plain words
What is it for?
Framing research questions, curating data, running statistics, creating figures and tables, drafting discussion sections, polishing text, and self-reviewing.
Why use it?
It organizes the many research and writing tasks involved in turning a study into a submission-ready manuscript.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: mentions subagents.

Part of the academic-skills-food-nutrition plugin — 41 skills shipped together

Good fit Framing research questions, curating data, running statistics, creating figures and tables, drafting discussion sections, polishing text, and self-reviewing.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/pangenomeai/academic-skills-food-nutrition/food-paper
Install

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.

Any agent
npx skills add PangenomeAI/academic-skills-food-nutrition --skill food-paper
Clone the repo
git clone --depth 1 https://github.com/PangenomeAI/academic-skills-food-nutrition

Made for: Claude Code.

Or install academic-skills-food-nutrition, the plugin that ships this one along with the rest of its 41 skills.

Wrote 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.

agentmods badge for food-paper

README.md
[![agentmods](https://agentmods.dev/badge/skills/pangenomeai/academic-skills-food-nutrition/food-paper/github.svg)](https://agentmods.dev/skills/pangenomeai/academic-skills-food-nutrition/food-paper)
Your own site
<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.

agentmods 80×15 button for food-paper

Your own site · 80×15
<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>
Per session 180 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,417 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00180 $0.02417
Opus 5.5 $0.00072 $0.00967
Sonnet 5.5 $0.00036 $0.00483
Haiku 4.5 $0.00018 $0.00242

Measured 1mo ago against content hash ef52cd88e1cd, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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 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.

food-paper/SKILL.md · 121 lines

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-review report and/or margin comments on a Word file). Edit the original .docx with Tracked Changes (do not start a fresh copy), resolving each comment. Inside food-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. See references/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 (see references/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 (polisher runs references/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.

Read the full file on GitHub · 121 lines

Changes

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.

  1. 1mo ago First seen · 121 lines · 180 tokens per session scan A ef52cd88e1cd

Subscribe to this mod's changes

food-paper is a skill published in the GitHub repository PangenomeAI/academic-skills-food-nutrition (38 stars, last pushed 1mo ago), licensed MIT. It adds 180 tokens to every session and 2,417 once invoked, about $0.0007 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 2026-08-30.

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