Food Research

Food-Research — Comprehensive Evidence Synthesis for Food & Nutrition Science

Build a broad, defensible understanding of a topic by searching many sources, screening them consistently, and synthesizing across them. Original work; no third-party research text is reused. Architecture informed by open community literature-search skills (see Acknowledgements in the repo README).

Streams — pick one and when to use it

Four streams share the same search/screening machinery but differ in depth. Three of them (quick brief, full review, deep research) prioritize sources by journal ranking via journal_ranker; the systematic stream does not (inclusion is by pre-specified eligibility, not prestige).

| Stream | Use it when… | Depth | Journal-ranking filter | |---|---|---|---| | quick brief | You need fast orientation on a topic — "what's known about X", a starting point, a scoping glance. | One search pass; top sources; key open questions. May run inline without subagents. | Yes — Tier 1 only, usually | | full review | You want a thorough narrative review manuscript (the default). | Four-layer search + two-phase screening + synthesis → write manuscript (writer) → review loop (reviewer) → Word (.docx). | Yes — Tier 1 preferred, Tier 2 to fill gaps | | deep research | The question extends beyond the literature — regulatory landscape, market/technology state, an open-ended "investigate this" — or you want an iterative, verified deep dive on a subtopic. | Calls the deep-research skill (scope → plan → investigate → verify → synthesize → critique loop); its literature portion still passes through journal ranking. | Yes — for the literature portion | | systematic | You need a reproducible, auditable PRISMA review / meta-analysis with a protocol, ≥3 databases, dual independent screening, and risk-of-bias (OHAT) — i.e. a defensible, publishable systematic review. | Full systematic_reviewer pipeline (protocol → sr_search → dual 3-step sr_screener + sr_moderator → PRISMA → data_extractor results table → risk_of_bias OHAT → sr_synthesis → reviewer loop → writer Word .docx). | No — eligibility-based inclusion |

Overall flow

flowchart TD
    Q[Research question] --> M{Which stream?}
    M -- quick / full --> S1[search_strategist]
    M -- deep research --> DR[deep-research skillscope, plan, investigate,verify, critique loop]
    M -- systematic --> SR[systematic_reviewerPRISMA pipeline]
    S1 --> S2[source_scoutfour-layer search + dedup]
    S2 --> S3[screener_appraisertwo-phase screening + quality tags]
    S3 --> JR[journal_rankerTier 1 preferred; Tier 2 to fill gaps;avoid Tier 4]
    DR --> JR
    JR --> SY[synthesisevidence matrix, grading, gaps, coverage advisory]
    SY --> WR[writermanuscript, APA7 / target journal]
    WR --> RV[reviewereditorial + integrity]
    RV -- revise --> SY
    RV -- accept --> DOCX[Final review manuscript .docx]
    SR --> SROUT[Systematic-review manuscript .docxPRISMA + OHAT bias + per-RQ synthesis]

Both the full review and systematic streams finish by writing a manuscript, passing it through the reviewer loop, and delivering a Word document (writer). The quick brief and deep research streams do not (quick brief returns a short brief; deep research is handled by the deep-research skill).

Stream detail — invocation & subagent call sequence

Quick brief

• When it wakes: the user wants fast orientation, not an exhaustive review. Phrases like "give me a quick brief on…", "what's known about…", "quick overview of…", "brief me on…", "orient me on…", "TL;DR of the research on…". Also the default when the user asks a scoped factual research question and signals speed ("quickly", "just the highlights").
• How it runs (lightweight — may be inline, no subagents required):

1. Frame the question in one line (concepts + scope).
2. One search pass over 2–3 high-yield sources (PubMed/Consensus/CrossRef via MCP, else web search) — no four-layer expansion.
3. Apply journal_ranker Tier 1 only — keep Q1/Q2 food-science & nutrition, Nature/Science/Cell, and Q1/Q2 other-discipline hits; ignore the rest unless nothing Tier 1 exists.
4. Skim-appraise (relevance + obvious rigor red flags) — no full rubric.
5. Write a short brief: 3–6 key findings with citations, the consensus vs open questions, and 2–3 sources to read next.

• Subagents: optional. Run inline for speed; only spin up source_scout if the topic is broad. journal_ranker is applied as a filter step, not necessarily a separate dispatch.

Full review (default)

• When it wakes: the user wants a thorough, citable review/evidence brief — "do a literature review on…", "comprehensive review of…", "survey the field of…", "build an evidence brief on…", "review the evidence for…" — or asks to research a topic without signalling that speed matters.
• How it runs (full subagent pipeline): dispatch subagents in this order (independent retrieval runs in parallel):

1. search_strategist → search plan (concepts, controlled vocabulary, Boolean strings, source list).
2. source_scout → four-layer search + dedup → candidate set (parallel per source).
3. screener_appraiser → two-phase screening + quality rubric → included set with High/Medium/Low tags.
4. journal_ranker → prioritize by tier (Tier 1 preferred; Tier 2 only to fill gaps; avoid Tier 4).
5. synthesis → evidence matrix, grading, contradiction resolution, coverage advisory, gaps.
6. writer → write the review manuscript (APA 7.0 default, or target journal via journal-selector).
7. reviewer → editorial + integrity review; if not Accept, loop back to synthesis/writer to revise, then re-review (cap ~2–3).
8. writer → export the accepted manuscript to Word (.docx).

• Output: a finished review manuscript (.docx) + annotated bibliography + .bib/.ris.

Deep research

• When it wakes: "deep research on…", "investigate … thoroughly", "I need a deep dive / full briefing on…", or a question extending beyond the literature (regulatory, market, technology landscape). Calls the deep-research skill; its literature portion still passes through journal_ranker.

Systematic

• When it wakes — use the systematic stream when the user needs a defensible, reproducible, publishable systematic review, signalled by any of:
• Explicit terms: "systematic review", "systematic literature review", "PRISMA", "meta-analysis".
• A methodological requirement: "follow a protocol / PROSPERO", "two independent reviewers / dual screening", "with risk of bias", "OHAT", "PRISMA flow diagram".
• A rigor/audit intent: the user wants the review to be reproducible and auditable (every search string, screening decision, and exclusion reason recorded), not just a narrative overview.
• If the user only wants a broad narrative overview, use full review instead; if unsure which they want, ask one question ("narrative review or a full PRISMA systematic review with risk-of-bias?").
• How it runs: the systematic_reviewer orchestrator drives protocol → sr_search (≥3 databases) → dual independent three-step screening (sr_screener ×2 + sr_moderator) → PRISMA flow → data_extractor results table → risk_of_bias (OHAT) → sr_synthesis → reviewer loop → writer Word .docx. Journal ranking is not applied (eligibility-based inclusion).

Subagents (dispatch, don't inline)

Run these as subagents (via the Agent tool). Layers that are independent — e.g. per-source retrieval — run in parallel.

1. search_strategist — turns the question into a search plan: concepts, synonyms/controlled vocabulary (MeSH, FSTA/CAB thesaurus terms), Boolean strings per database, filters, and the source list.
2. source_scout — executes the four-layer retrieval across sources, records hit counts, and deduplicates into one candidate set.
3. screener_appraiser — two-phase screening + the food-science quality rubric; outputs the included set with quality tags.
4. journal_ranker — prioritizes the screened sources by journal ranking (Q1/Q2 food-science & nutrition, plus Nature/Science/Cell families and Q1/Q2 in any other discipline = highest; Q3 second; Q4 avoided). Used by quick brief, full review, and deep research only — never inside a systematic review.
5. synthesis — evidence matrix, contradiction resolution, evidence grading, gap analysis, and the coverage advisory.
6. writer — writes the review manuscript and exports Word (.docx) (APA 7.0 default, or target journal via journal-selector). Full review + systematic.
7. reviewer — combined editorial + integrity review with a revision loop. Full review + systematic.

Systematic-review subagents (systematic stream only):

1. systematic_reviewer — PRISMA orchestrator (protocol → search → dual screening → PRISMA → extraction → risk of bias → synthesis → review → Word).
2. sr_search — ≥3 databases (Web of Science, Scopus, PubMed preferred); combine + deduplicate; log all strings/counts.
3. sr_screener — run as two independent instances; three steps (title → abstract → full text) with per-record include/exclude + reasons.
4. sr_moderator — after each step, compares the two screeners, resolves conflicts, keeps PRISMA counts.
5. data_extractor — pulls the results table (by research question) from the final shortlist.
6. risk_of_bias — OHAT risk-of-bias assessment (in vitro / human / animal) by default.
7. sr_synthesis — PRISMA description → risk-of-bias results → per-RQ synthesis; formats APA 7.0 or target journal.

For a quick brief you may run the workflow inline without subagents.

Step 1 — Frame the question (search_strategist)

• Interventions/nutrition: PICO (Population, Intervention/Exposure, Comparator, Outcome).
• Composition/process/safety: define the food matrix, factor/treatment, and measured response.
• State scope, timeframe, languages, and exclusions. Break the question into concepts and list synonyms + controlled-vocabulary terms per concept.

Step 2 — Plan the sources

Cover several source classes so the picture isn't skewed by one index:

• Bibliographic: FSTA (Food Science & Technology Abstracts — the core food index), PubMed/MEDLINE, Web of Science, Scopus, CAB Abstracts, AGRICOLA, AGRIS (FAO).
• Preprints: bioRxiv, ChemRxiv, agriRxiv.
• Semantic / aggregators: CrossRef, Semantic Scholar, Consensus, Dimensions, Lens.org.
• Safety & regulatory / grey: EFSA, US FDA, USDA (incl. FoodData Central), Codex Alimentarius, WHO, EU/national food-standards bodies.
• Chemistry / bioactives: PubChem, ChEMBL, FooDB, Phenol-Explorer.
• Methods / standards: AOAC, ISO.

Tooling: use whatever literature MCP tools are connected (e.g. PubMed, Consensus, bioRxiv, CrossRef, Scopus/ScienceDirect) for live retrieval; fall back to web search for any source without a tool. Record which tool/source produced each result so the search is reproducible.

Step 3 — Four-layer search (source_scout)

1. Layer 1 — structured search: Boolean/keyword + controlled vocabulary across the bibliographic databases (target 100–500 raw hits). Apply date/language filters.
2. Layer 2 — backward chaining: mine the reference lists of the key reviews and seminal papers for older frequently-cited work.
3. Layer 3 — forward chaining: "cited by" from seminal works to catch the latest research.
4. Layer 4 — semantic / cross-disciplinary: related-article and semantic tools to catch methodologically or disciplinarily adjacent work (chemistry, engineering, nutrition, microbiology) that keyword search misses.

• Deduplicate by DOI/title across sources. Record the hit count at each layer.
• Stop when the search saturates — e.g. ≥3 of: no new themes appearing, citation loops closing, timeframe covered, key authors/venues all seen, new hits 70% of sources share one publication year, region, food matrix, method, or venue family — a bias risk.
• Gaps: under-powered areas, missing methods, population/geographic voids; propose the next study.

Deliverables

An evidence brief containing: question & scope; reproducible search strategy (sources, Boolean strings, filters, dates); screening funnel with counts; annotated bibliography (per source: design, findings, relevance, quality tag, intended paper section); literature/evidence matrix; graded conclusions; coverage advisory; and a gap list. Export references as .bib/.ris (deduplicated) for reuse.

Deep dives

For a subtopic that needs open-ended investigation beyond the literature (e.g. regulatory landscape, market/technology state), call the deep-research skill and fold its sourced synthesis back into the evidence brief.

References (load as needed)

• references/literature-sources.md — databases + APIs (FSTA/PubMed/WoS/Scopus/CrossRef/OpenAlex + EFSA/FDA/USDA) for search_strategist/source_scout/sr_search.
• references/source-quality-hierarchy.md — evidence grading for screener_appraiser/synthesis.
• references/reporting-guidelines.md — EQUATOR/PRISMA/CONSORT/STROBE for the systematic stream and appraisal.

Handoff

Sources tagged and assigned by section feed food-paper (Introduction and Discussion evidence, reference list) and are orchestrated by food-pipeline.

Food & nutrition rigor notes

Watch for pseudo-replication (analytical replicates as biological n); matrix effects and single-cultivar/single-batch over-generalization; unvalidated assays; and undisclosed funding/conflicts, which are common and material here.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: PangenomeAI
• Source: PangenomeAI/academic-skills-food-nutrition
• License: MIT

Install and usage instructions live in the source repository linked above.