food-research
SolidRun 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.
Install
Quality Score: 84/100
Skill Content
Details
- Author
- PangenomeAI
- Repository
- PangenomeAI/academic-skills-food-nutrition
- Created
- 2 weeks ago
- Last Updated
- 4 days ago
- Language
- Python
- License
- MIT
Integrates with
Similar Skills
Semantically similar based on skill content — not just same category
food-deep-research
General-purpose deep research that produces a fully written, source-validated literature review on any question: scope it, design the method, discover and screen sources by journal ranking, validate every source, extract and verify evidence, synthesize, stress-test, then write and format the review (APA 7.0 by default, or a target journal's style) and polish it through an editorial + integrity review loop. Use standalone for a deep dive or literature review, or as the deep-dive engine called by food-research. Runs a 12-subagent team with iterate-to-saturation and compile↔review loops. Triggers: deep research, research this in depth, write a literature review, investigate thoroughly, comprehensive review, state of the evidence, briefing on, dig into, deep dive.
agri-research
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.
agri-deep-research
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.