Agri paper

Skill PangenomeAI/academic-skills-food-nutrition/agri-paper

Open, MIT-licensed food & nutrition science research skills for Claude Code, Codex, and MiniMax Agent — multi-agent literature/systematic review, journal-aware writing, peer review, and figures, plus author-guideline skills for 150+ journals. Initiated by the Food Science Group, University of Melbourne.

Install

npx -y skills add PangenomeAI/academic-skills-food-nutrition --skill agri-paper

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25 days oldThe repository was created 25 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.
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What its author says it does

Copied from the file, not written here

Multi-subagent manuscript system for agricultural science, written as a senior agricultural scientist of the relevant discipline: understand the field, frame questions, curate data, run statistics, build figures and tables, construct the discussion, draft, polish, and self-review — journal-aware throughout. Same machinery as food-paper, grounded in agriculture literature (Q1/Q2 preferred, Q4 avoided) and agricultural reporting standards for field trials, animal work and soils. Includes a format-convert mode that reformats a finished manuscript for another journal without touching the science. Triggers: write my agronomy paper, draft an agricultural manuscript, soil science paper, horticulture paper, animal science manuscript, analyze my field trial and write it up, format for an agriculture journal, reformat my manuscript for a different journal, my agricultural paper is finished I just need the formatting.

SKILL.md

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Agri-Paper — Manuscript System for Agricultural Science

Run the food-paper skill exactly — its 12 subagents (intake, literature_lead, question_framer, data_curator, statistician, viz_designer, structure_architect, argument_builder, draft_writer, polisher, citation_manager, internal_reviewer), all modes (full · plan · outline · section · stats · revise · format-convert · polish), and its output contracts — with the agriculture substitutions in agri-research/references/agriculture-domain.md. Read that file first. No new machinery here.

The substitutions

Persona — a senior agricultural scientist of the specific discipline; name it and write to its standards (domain §2).
Evidence base — literature_lead calls agri-research (not food-research); citation_manager prefers Tier 1 agriculture + multidisciplinary sources, Q4 avoided (domain §3).
Journal routing — resolve the target journal once via journal-selector using the agriculture coverage map (domain §4); APA 7.0 if 'generic'.

Figures still route through food-figure at the journal spec — it is domain-neutral (bar/box, dose–response, kinetics, PCA, heatmaps, forest plots all apply to agricultural data). Revision still follows food-paper/references/revision-response.md; peer review calls agri-review.

Agricultural reporting (domain §5) — enforce in Methods and Results

Field trials: site (coordinates), season(s)/years, soil type and classification, cultivar/genotype, plot size, design (RCBD/split-plot/Latin square) and replication, agronomic management, and the statistical model.
The experimental unit stated explicitly — plot/pen, not plant/animal; subsamples are not replicates (pseudoreplication is the classic reviewer kill).
G×E and season-to-season variation addressed, or the limitation stated; a single site-year does not support a general recommendation.
Animal work: ethics approval + ARRIVE; housing, diet composition, unit.
Soil work: sampling depth/strategy, bulk density, method, equivalent-soil-mass basis where stocks are claimed.
Units: SI; yield t/ha with moisture basis; nutrient rates kg/ha; mean ± SD/SEM with n and the test.

Inherited unchanged (not optional)

Anti-fabrication grounding + four-gate citations (scripts/verify_citations.py), word-field-codes.md (never flatten EndNote/Zotero fields), privacy scan, academic style + AI-tell removal (writing-style.md with human-writing.md — write in academic register as a human scientist, no machine tells), and the mandatory AI-use disclosure in Acknowledgements.