---
name: Agri Deep Research
slug: agri-deep-research
category: AI Engineering
description: Performs deep, source-validated literature reviews on agricultural questions using a 12-subagent AI system with rigorous source screening and academic integrity checks.
github: "https://github.com/PangenomeAI/academic-skills-food-nutrition/tree/main/agri-deep-research"
language: Python
stars: 16
forks: 1
install: "git clone https://github.com/PangenomeAI/academic-skills-food-nutrition"
added: 2026-07-17T07:09:58.146Z
last_synced: 2026-07-17T07:09:58.146Z
canonical_url: "https://dirskills.com/skills/agri-deep-research"
---

# Agri Deep Research

Performs deep, source-validated literature reviews on agricultural questions using a 12-subagent AI system with rigorous source screening and academic integrity checks.

**Install:** `git clone https://github.com/PangenomeAI/academic-skills-food-nutrition`

## README

# Agri-Deep-Research — Source-Validated Reviews for Agricultural Science

**Run the `food-deep-research` skill exactly** — its 12-subagent team
(`research_scope`, `research_architect`, `investigator`, `source_screener`,
`source_verifier`, `bibliography`, `claim_verifier`, `synthesizer`, `critic`,
`compiler`, `editor`, `ethics_reviewer`), both loops (evidence loop and
compile↔review loop), and its source discipline — with the agriculture
substitutions in
[`agri-research/references/agriculture-domain.md`](../agri-research/references/agriculture-domain.md).
Read that file first. No new machinery here.

## The substitutions
1. **Persona** — a **senior agricultural scientist of the specific discipline**;
   name it and apply its standards (domain §2). `research_architect` designs the
   method to that discipline's conventions.
2. **Evidence base** — `source_screener` ranks agriculture + multidisciplinary
   literature: **Tier 1** = Q1/Q2 of the seven agriculture categories
   ([`journals/_coverage_agriculture.md`](../journals/_coverage_agriculture.md)) +
   Nature/Science/Cell/PNAS + Q1/Q2 adjacent disciplines; **Tier 2** = Q3 for gaps;
   **Q4 avoided**. FAO/USDA/CGIAR/EFSA and extension sources are evidence with a
   source and date (domain §3).
3. **Journal routing** — `bibliography` and `compiler` format via `journal-selector`
   using the agriculture coverage map (domain §4); APA 7.0 by default.

## Source discipline (inherited, non-negotiable)
Investigation and claim-checking operate **only on validated sources** — those that
passed `source_screener` (ranking) **and** `source_verifier` (existence, venue
legitimacy, retraction, predatory check). Every claim carries a source and locator;
inference is labelled as inference; `[EVIDENCE GAP]` rather than filling from memory.

## Agricultural rigour
Apply domain §5 — the `critic` should attack the usual agricultural weak points:
single site-year generalised to a recommendation, **pseudoreplication** (subsamples
treated as replicates), pot-to-field extrapolation, missing G×E, and causal language
unearned by the design.

## Inherited unchanged (not optional)
Four-gate citation verification (`scripts/verify_citations.py`), privacy scan,
`food-paper/references/human-writing.md`, and the **mandatory AI-use disclosure**.