Food paper
Multi-subagent manuscript system for food & nutrition science covering the whole research process: understand the field, frame research questions, curate and analyze data, run statistics, build figures and tables, construct the discussion, draft, polish, and self-review — journal-aware throughout. Includes a format-convert mode that reformats an already-finished manuscript to another journal's structure and reference style without touching the science. Use to write, outline, revise, polish, or reformat a food-science paper or any section. Triggers: write my paper, draft a manuscript, food science paper, outline my paper, revise my manuscript, analyze my data and write it up, statistics for my paper, polish my manuscript, format for a journal, reformat my manuscript for a different journal, change the journal format, convert to another journal style, my paper is finished I just need the formatting.From its SKILL.md
npx -y skills add PangenomeAI/academic-skills-food-nutrition --skill food-paperAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
2 things to look at
- 28 days oldThe repository was created 28 days ago. New is not bad, but a brand new repository carrying a familiar-sounding name is the shape a typosquat arrives in, and there has been no time for anyone else to find a problem with it.
- 24 stars24 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
SKILL.md
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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.
Subagent team (dispatch via the Agent tool; independent stages run in parallel)
| # | Subagent | Stage of the research process |
|---|---|---|
| 1 | intake | Capture paper type, target journal, data/materials, and goals; set the plan. |
| 2 | literature_lead | Understand the field — calls the food-research skill for the evidence base. |
| 3 | question_framer | Research questions / hypotheses / objectives + the contribution. |
| 4 | data_curator | Curate the dataset: integrity, units, missing data, metadata, provenance. |
| 5 | statistician | Statistical plan + analysis appropriate to the food/nutrition design. |
| 6 | viz_designer | Figures & tables — calls the food-figure skill at the journal spec. |
| 7 | structure_architect | Outline mapped to the target journal's structure + evidence map. |
| 8 | argument_builder | Claim–evidence–reasoning chains; results→discussion logic. |
| 9 | draft_writer | Draft each section with food-science reporting conventions. |
| 10 | polisher | Edit to clear, publication-quality scientific English. |
| 11 | citation_manager | References + in-text citations in the journal's style (APA 7.0 default). |
| 12 | internal_reviewer | Pre-submission self-review — calls the food-review panel. |
Workflow
flowchart TD
A[intake<br/>type, journal, data, goals] --> JS[journal-selector<br/>load journal constraints]
A --> L[literature_lead<br/>-> food-research evidence base]
L --> Q[question_framer<br/>RQs / hypotheses / contribution]
A --> D[data_curator<br/>curate + check dataset]
D --> S[statistician<br/>analysis plan + results]
S --> V[viz_designer<br/>-> food-figure figures & tables]
Q --> ST[structure_architect<br/>journal-mapped outline + evidence map]
S --> ST
V --> ST
ST --> AR[argument_builder<br/>CER chains, results->discussion]
AR --> W[draft_writer<br/>section drafts]
W --> P[polisher<br/>publication English]
P --> C[citation_manager<br/>journal reference style]
C --> IR[internal_reviewer<br/>-> food-review panel]
IR -- revise --> W
IR -- ready --> OUT[Submission-ready manuscript]
Food & nutrition reporting defaults (enforced by draft_writer / data_curator / statistician)
Composition as g/100 g (basis + AOAC method); sensory panel type/size/scale + ethics; microbial counts log CFU/g with LOD; TPA/rheology parameters + settings; HPLC/GC/LC-MS conditions, LOD/LOQ, recovery, identification by standards/MS-MS; mean ± SD/SEM with n; the statistical model, test, post-hoc, and threshold, with significance shown consistently. Reproducible Methods (cultivar/breed/batch, prep, storage). Ethics/food-safety statements where relevant.
References (load as needed)
references/paper-structure.md—structure_architect: IMRaD/review patterns + abstract types.references/writing-style.md—draft_writer/polisher: scientific style, title/intro rhetoric.references/human-writing.md— write like a scientist, not a chatbot: the AI writing tells to remove (inflated significance, vague attribution, stock vocabulary, hedge stacking), the academic exceptions to keep (calibrated hedging, passive Methods, journal-mandated form), and the two-pass check. Canonical for the suite; used byfood-research,food-deep-research, andfood-reviewtoo.references/writing-quality-check.md— self-check beforeinternal_reviewer.references/statistics-reporting.md—statistician: what to report and which test.references/declarations-guide.md— CRediT, funding, COI, data availability, ethics.references/apa7-quickref.md— default citation style forcitation_manager(canonical APA 7.0 for the suite).references/faithfulness-and-citation.md— grounding rules + four-gate citation check; the suite's no-fabrication contract. Runscripts/verify_citations.pyon the reference set.references/latex-guide.md— prepare/edit LaTeX drafts and build the PDF (Pandoc / latexmk).references/revision-response.md— revise mode: tracked changes (original Word opt-in underfood-pipeline) + either updating the one Review & Response Report in place (pipeline) or a point-by-point response letter (standalone). All.docx.references/word-field-codes.md— preserve EndNote/Zotero/Mendeley citation fields when editing a.docx(don't flatten field codes into visible text); verify withscripts/check_docx_fields.py.references/privacy-and-confidentiality.md— privacy check before delivery (no local paths/secrets); runscripts/privacy_scan.py.
Grounding (non-negotiable)
Write only from the user's data and verified literature. Never invent
references, DOIs, numbers, or results; unsupported content is marked
[UNVERIFIED]/[EVIDENCE GAP], never filled from memory. citation_manager and
draft_writer enforce the four-gate citation check in
references/faithfulness-and-citation.md.
Handoffs
food-research (evidence in) → food-paper → food-review (external panel) →
food-paper revise. Orchestrated by food-pipeline.
What ships with it: 24 files
69.8 KB alongside SKILL.md
agents/
- argument_builder.md1.3 KB
- citation_manager.md1.3 KB
- data_curator.md1.6 KB
- draft_writer.md3.8 KB
- intake.md2.0 KB
- internal_reviewer.md1.4 KB
- literature_lead.md1.2 KB
- polisher.md2.2 KB
- question_framer.md1.2 KB
- statistician.md2.0 KB
- structure_architect.md1.3 KB
- viz_designer.md1.5 KB
references/
- apa7-quickref.md1.7 KB
- declarations-guide.md5.6 KB
- faithfulness-and-citation.md3.6 KB
- human-writing.md14.5 KB
- latex-guide.md2.9 KB
- paper-structure.md1.7 KB
- privacy-and-confidentiality.md2.1 KB
- revision-response.md6.4 KB
- statistics-reporting.md1.7 KB
- word-field-codes.md2.7 KB
- writing-quality-check.md2.7 KB
- writing-style.md3.4 KB