Jeden Skill in Manus ausführen
mit einem Klick

Jeden Skill in Manus mit einem Klick ausführen

agri-paper

Sterne17

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Aktualisiert23. Juli 2026 um 07:23

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.

Installation

Mit Codex oder Claude installieren Kopieren Sie diesen Prompt, fügen Sie ihn in Codex, Claude oder einen anderen Assistant ein und lassen Sie die Skill-Seite prüfen und installieren.

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Quelle

PangenomeAI

PangenomeAI/academic-skills-food-nutrition

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Verwandte BerufeSOC

Basierend auf der SOC-Berufsklassifikation

TierwissenschaftlerNatur- und Sozialwissenschaften·SOC 19-1011

SKILL.md

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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.

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PangenomeAI/academic-skills-food-nutrition

Run a comprehensive, multi-source literature and evidence-synthesis workflow for food & nutrition science. Use when the user wants to research a food/nutrition topic in depth, do a literature review, build an evidence brief, screen and synthesize many sources, verify citations, or scope a systematic review. Coordinates food-science databases, preprints, semantic search, and food-safety/regulatory sources; runs a four-layer search, two-phase screening, and cross-source synthesis via subagents; grades evidence and maps gaps. Triggers: research this topic, deep literature review, comprehensive review, evidence synthesis, systematic review, scope a review, find all the literature, what does the evidence say, food science research, nutrition evidence, survey the field.

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agri-deep-research

PangenomeAI/academic-skills-food-nutrition

Deep research producing a fully written, source-validated literature review on an agricultural question, as a senior agricultural scientist of the relevant discipline: scope, design the method, discover and screen by journal ranking, validate every source, extract and verify evidence, synthesize, stress-test, then write and format the review through an editorial and integrity loop. Same 12-subagent machinery as food-deep-research, grounded in agriculture and multidisciplinary literature (Q1/Q2 preferred, Q4 avoided). Use standalone for an agricultural deep dive, or as the engine called by agri-research. Triggers: deep research agriculture, investigate this agronomy question, agricultural literature review, state of the evidence in soil science, deep dive crop research.

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PangenomeAI/academic-skills-food-nutrition

Run a comprehensive, multi-source literature and evidence-synthesis workflow for agricultural science, as a senior agricultural scientist of the relevant discipline (agronomy, soil science, horticulture, dairy and animal science, agricultural engineering, or agricultural economics). Same machinery as food-research, but the evidence base is agriculture and multidisciplinary literature ranked by journal quartile: Q1/Q2 agriculture journals plus the Nature, Science, Cell and PNAS families first, Q3 only for gaps, Q4 avoided. Use to research an agricultural topic in depth, do a literature review, build an evidence brief, or scope a systematic review. Triggers: research this agricultural topic, agronomy literature review, soil science evidence synthesis, horticulture review, animal science evidence, crop research, farming systems review, what does the agricultural evidence say.

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PangenomeAI/academic-skills-food-nutrition

Lawfully acquire the full text of academic articles so the research and review skills can read papers, not just abstracts. Routes each article through legal open access (Unpaywall/OpenAlex/PMC/arXiv), the user's own reference-manager library (EndNote/Zotero/Mendeley PDFs), and — only with the user's own logged-in institutional browser session — their library's entitled full text, then extracts the text and writes a manifest of what was and was not obtained. Open-access articles are always downloaded and read, never left at abstract-level. Never bypasses paywalls, DRM, or logins. Use to fetch PDFs for a reference list or DOIs, get full text behind a subscription the user is entitled to, or build a full-text corpus. Triggers: download these papers, get the full text, fetch the PDFs for these DOIs, retrieve full text for my reference list, access the article through my library, build a full-text corpus.

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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.