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πŸ“
WritingPython

Agri-Paper

by PangenomeAI

Assists in writing, revising, and formatting agricultural science manuscripts using a multi-agent system that handles literature, statistics, figures, and journal-specific reporting standards.

16 stars1 forksAdded 2026/07/17
academic-writingai-agentsanthropicclaude-codeclaude-skillscodexfoodfood-sciencefood-science-innovationfood-technologyliterature-reviewllmmeta-analysisnutritionnutrition-sciencepeer-reviewresearch-toolsscholarly-publishingscientific-figuressystematic-review

Documentation

README

Agri-Paper β€” Manuscript System for Agricultural Science

Run the food-paper skill exactly β€” its 12 subagents (intake, literature_lead, question_framer, data_curator, statistician, viz_designer, structure_architect, argument_builder, draft_writer, polisher, citation_manager, internal_reviewer), all modes (full Β· plan Β· outline Β· section Β· stats Β· revise Β· format-convert Β· polish), and its output contracts β€” with the agriculture substitutions in agri-research/references/agriculture-domain.md. Read that file first. No new machinery here.

The substitutions

  1. Persona β€” a senior agricultural scientist of the specific discipline; name it and write to its standards (domain Β§2).
  2. Evidence base β€” literature_lead calls agri-research (not food-research); citation_manager prefers Tier 1 agriculture + multidisciplinary sources, Q4 avoided (domain Β§3).
  3. Journal routing β€” resolve the target journal once via journal-selector using the agriculture coverage map (domain Β§4); APA 7.0 if 'generic'.

Figures still route through food-figure at the journal spec β€” it is domain-neutral (bar/box, dose–response, kinetics, PCA, heatmaps, forest plots all apply to agricultural data). Revision still follows food-paper/references/revision-response.md; peer review calls agri-review.

Agricultural reporting (domain Β§5) β€” enforce in Methods and Results

  • Field trials: site (coordinates), season(s)/years, soil type and classification, cultivar/genotype, plot size, design (RCBD/split-plot/Latin square) and replication, agronomic management, and the statistical model.
  • The experimental unit stated explicitly β€” plot/pen, not plant/animal; subsamples are not replicates (pseudoreplication is the classic reviewer kill).
  • GΓ—E and season-to-season variation addressed, or the limitation stated; a single site-year does not support a general recommendation.
  • Animal work: ethics approval + ARRIVE; housing, diet composition, unit.
  • Soil work: sampling depth/strategy, bulk density, method, equivalent-soil-mass basis where stocks are claimed.
  • Units: SI; yield t/ha with moisture basis; nutrient rates kg/ha; mean Β± SD/SEM with n and the test.

Inherited unchanged (not optional)

Anti-fabrication grounding + four-gate citations (scripts/verify_citations.py), word-field-codes.md (never flatten EndNote/Zotero fields), privacy scan, human-writing.md (write like a scientist, not a chatbot), and the mandatory AI-use disclosure in Acknowledgements.

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