Skip to main content

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.

Zur Installation springen

Quellinformationen

Repository
PangenomeAI/academic-skills-food-nutrition
Letzte Quellaktivität
23. Juli 2026 um 11:56
Erkannte Sprache von SKILL.md
Englisch
Sterne
32
Forks
3

Installationsoptionen

Standardmäßig ist der Prompt ausgewählt, der zuerst die Quelle prüft. Sie können zu einem direkten Befehl wechseln oder eine lokale Kopie herunterladen.

Quelldateien prüfen

Lesen Sie SKILL.md und alle von SkillsMP angezeigten Begleitdateien, bevor Sie sich für eine Installation entscheiden.

Datei-Explorer
14 Dateien

SKILL.md wird angezeigt

SKILL.md
Quellanweisungen · Schreibgeschützte Vorschau
name
food-deep-research
description
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.
metadata
{"version":"2.1.0","verified":"2026-07","related_skills":["food-research","journal-selector","food-paper","food-pipeline"],"subagents":["research_scope","research_architect","investigator","source_screener","source_verifier","bibliography","claim_verifier","synthesizer","critic","compiler","editor","ethics_reviewer"],"references":["references/reasoning-and-fallacies.md"]}
# Deep-Research — Source-Validated Literature Review Engine Answer a hard question properly and hand back a **written, formatted, integrity- checked literature review** — not just notes. Scope → design → discover → screen by journal ranking → validate sources → extract & verify evidence → synthesize → stress-test → write → review-loop → final report. Original work; architecture informed by open community food-deep-research skills (see the repo README Acknowledgements). Usable standalone, or as the deep-dive engine called by `food-research`. ## Modes - **quick brief** — scope → discover → screen (Tier 1) → light synthesis → short sourced answer. Skips the full validation/compile/review loop. - **full** — the default: the complete 12-subagent pipeline below with the iterate-to-saturation and compile↔review loops, ending in a finished review. ## Subagent team (dispatch via the Agent tool) | # | Subagent | Job | |---|---|---| | 1 | `research_scope` | Comprehensive scope brief: background, problem, significance, central + sub-questions, concepts, boundaries, success criteria. | | 2 | `research_architect` | Methodology blueprint: review type, search strategy, inclusion criteria, analytical framework, reporting standard, stopping criteria. | | 3 | `investigator` | Pass 1 discover candidate sources; Pass 2 extract evidence **from validated sources only** (parallel per sub-question). | | 4 | `source_screener` | Prioritize candidates by **journal ranking** (Tier 1 Q1/Q2 + Nature/Science/Cell + other-discipline Q1/Q2; Tier 2 Q3; avoid Tier 4). | | 5 | `source_verifier` | Validate each prioritized source (existence/DOI, venue legitimacy, retraction, predatory, methodology, COI) → Source Quality Matrix. | | 6 | `bibliography` | Deduplicate + format references (APA 7.0 default, or target-journal style via `journal-selector`); build the citation map + `.bib/.ris`. | | 7 | `claim_verifier` | Verify each load-bearing claim against its validated source; classify fact/hypothesis/contested/speculation. | | 8 | `synthesizer` | Evidence matrix, thematic synthesis, conflict reconciliation, evidence grading, coverage advisory, gap agenda, narrative arc. | | 9 | `critic` | Devil's advocate on the **synthesis**; loop back to investigate if gaps. | | 10 | `compiler` | Write & format the **literature-review draft** (APA 7.0 / target journal); cite by key only; no fabrication. | | 11 | `editor` | Editorial review of the draft (5 weighted dimensions, verdict + prioritized feedback). | | 12 | `ethics_reviewer` | Integrity/ethics review of the draft (citation integrity, faithful representation, bias, COI, disclosure). | ## Workflow ```mermaid flowchart TD A[research_scope<br/>scope brief] --> B[research_architect<br/>methodology blueprint] B --> C[investigator Pass 1<br/>discover candidate sources] C --> D[source_screener<br/>journal-ranking tiers] D --> E[source_verifier<br/>validate → Source Quality Matrix] E --> F[bibliography<br/>dedupe + format + citation map] E --> G[investigator Pass 2<br/>extract evidence from validated sources] G --> H[claim_verifier<br/>verify claims vs validated sources] H --> I[synthesizer<br/>matrix, themes, conflicts, grading, gaps] I --> J[critic<br/>stress-test synthesis] J -- gaps --> C J -- sound --> K[compiler<br/>write + format review<br/>APA 7.0 / target journal] F --> K K --> L[editor + ethics_reviewer<br/>editorial + integrity review] L -- minor/major revision --> K L -- accept --> M[Final literature review] ``` **Two loops:** (1) *evidence loop* — `critic` sends gaps back to `investigator` (cap ~2–3); (2) *writing loop* — `editor`/`ethics_reviewer` send revisions back to `compiler` until Accept (cap ~2–3), then deliver. ## First move — set up full-text access (once) The evidence loop reads **actual articles**, not abstracts. At the start, run the **`food-fetch` first-run setup** (`python3 scripts/food_fetch_setup.py status`): if the user hasn't set up access, surface the one-time highlighted request to provide their **EndNote `.Data` folder** (or Zotero/Mendeley / a PDF folder) or **institutional access**, warning that **without non-open-access access the accuracy is substantially limited**; save the choice so it isn't re-asked. If they chose "open-access only", **remind** briefly of that accuracy limit each run. Don't block — proceed at open-access + abstract level and flag paywalled sources. Full rules: `food-fetch/SKILL.md` and `food-research/references/full-text-access.md`. ## Source discipline (non-negotiable) - **Investigation and claim-checking operate only on validated sources** — those that passed `source_screener` (ranking) **and** `source_verifier` (validity). Retracted/unresolvable sources are excluded and logged. - **Journal ranking** favors Tier 1 (Q1/Q2 food-science & nutrition, Nature/Science/Cell families, Q1/Q2 in any other discipline); Tier 2 (Q3) only to fill gaps; Tier 4 avoided. - Every claim carries a source and locator; inference is labelled as inference. ## Formatting — resolve the target journal once At the start, load **`journal-selector/SKILL.md`** (a shared procedure, not an installed skill), which **asks which journal the review targets** (they may answer 'generic' → **APA 7.0**). Ask **once**: record the choice and reuse it in `bibliography` and `compiler` to format the review to that journal's structure, limits, and reference style — don't ask again. Reuse a journal already resolved by `food-research`/`food-pipeline`; re-resolve only if the user asks to switch journals. ## Principles Every claim sourced; fact separated from interpretation; disagreement shown, not averaged; uncertainty surfaced. Upstream evidence beats parametric knowledge — mark missing evidence `[EVIDENCE GAP]`, never fabricate. ## References (load as needed) - `references/reasoning-and-fallacies.md` — `synthesizer`/`critic`: sound argument + fallacies. - `food-research/references/literature-sources.md` — databases/APIs for `investigator`. - `food-research/references/full-text-access.md` — reading the **actual full text** for `investigator`/`source_verifier` (open access → connected tool → user PDFs → library session, legitimate access only); mark anything unread rather than summarizing. - `food-research/references/source-quality-hierarchy.md` — evidence grading for `source_verifier`/`synthesizer`. - `food-research/references/reporting-guidelines.md` — EQUATOR/PRISMA/CONSORT/STROBE. - `food-paper/references/apa7-quickref.md` — APA 7.0 for `bibliography`/`compiler` (default style). - `food-paper/references/writing-style.md` + `food-paper/references/human-writing.md` — **`compiler`: academic style + remove AI tells, applied together** — academic register as a human scientist, machine tells stripped, calibrated hedging and journal form kept. - `food-review/references/ethics-integrity-checklist.md` — for `ethics_reviewer`. - `food-paper/references/faithfulness-and-citation.md` — **grounding + four-gate citation check** for `bibliography`, `source_verifier`, `claim_verifier`, `compiler`. Never invent sources/data; run `scripts/verify_citations.py`. - `food-paper/references/privacy-and-confidentiality.md` — **privacy scan before delivering the report** (no local paths/secrets); `scripts/privacy_scan.py`. ## Handoff Standalone → deliver the final review. Called by `food-research` → return the validated synthesis (or the finished review) to fold into the evidence brief.
Auf GitHub ansehen