Agri-Research — Evidence Synthesis for Agricultural Science
SkillDev toolsRun 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.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Agri-Research — Evidence Synthesis for Agricultural Science skill
What this skill tells your AI
The instructions your AI receives, as published by pangenomeai/academic-skills-food-nutrition in agri-research/SKILL.md and read by ahel’s review.
Run the food-research skill exactly — its streams, subagents
(search_strategist, source_scout, screener_appraiser, journal_ranker,
synthesis, writer, reviewer, and the full systematic_reviewer PRISMA/OHAT
pipeline), gates, and output contracts — with the agriculture substitutions in
references/agriculture-domain.md. Read that
file first. This skill adds no new machinery; it changes who is working, on what
evidence, for which journal.
The substitutions
- Persona — a senior agricultural scientist of the specific discipline (agronomy · soil science · horticulture · dairy & animal science · agricultural engineering · agricultural economics & policy · agriculture multidisciplinary). Name the discipline and apply its standards (domain §2).
- Evidence base — agriculture + multidisciplinary literature, ranked by
journal_ranker: Tier 1 = Q1/Q2 of the seven agriculture categories (journals/_coverage_agriculture.md, 230 journals) + Nature/Science/Cell/PNAS + Q1/Q2 of adjacent disciplines; Tier 2 = Q3 for gaps only; Q4 avoided. Authoritative non-journal sources (FAO, USDA, CGIAR, EFSA, extension services) count as evidence with a source and date (domain §3). - Journal routing — via
journal-selector, using the agriculture coverage map (domain §4).
Streams (as food-research)
- quick brief — fast orientation; Tier 1 only.
- full review — the default: four-layer search → two-phase screening → synthesis
→ manuscript →
reviewerloop → Word.docx. - deep research — calls
agri-deep-research(notfood-deep-research). - systematic — full PRISMA + OHAT pipeline; inclusion by pre-specified eligibility, never journal ranking.
Agricultural rigour
Apply domain §5 throughout — field-trial reporting (site, season/years, soil, cultivar, design, replication), the experimental unit (plot/pen, not plant/animal — pseudoreplication is the classic error), G×E and season-to-season variation, ARRIVE for animal work, and no extrapolation from pot to field or region to region.
Inherited unchanged (not optional)
Anti-fabrication grounding and the four-gate citation check
(scripts/verify_citations.py), the privacy scan, journal-selector's ask-once
contract, academic style + AI-tell removal (food-paper/references/writing-style.md with human-writing.md), and the mandatory AI-use
disclosure in every written output. Also the full-text-access first move —
food-research's highlighted, one-time request for the user's EndNote .Data folder
/ reference PDFs, and full-text extraction via the ladder before synthesis
(food-research/references/full-text-access.md).
Signals
- GitHub stars
- 31
- Forks
- 3
- Last commit
- Aug 2026
Advanced
- Catalog kind
- skill
- Gateway key
agri-research- Source
- github.com/pangenomeai/academic-skills-food-nutrition