算法艺术创作
algorithmic-art
通过代码和可调参数创作生成艺术与交互式视觉效果。
agri-deep-research【设计与创意】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 …
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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.
Read that file first. No new machinery here.
research_architect designs the
method to that discipline's conventions.source_screener ranks agriculture + multidisciplinary
literature: Tier 1 = Q1/Q2 of the seven agriculture categories
(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).bibliography and compiler format via journal-selector
using the agriculture coverage map (domain §4); APA 7.0 by default.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.
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.
Four-gate citation verification (scripts/verify_citations.py), privacy scan,
academic style + AI-tell removal (food-paper/references/writing-style.md with human-writing.md), and the mandatory AI-use disclosure.
Also the full-text-access first move — food-deep-research's highlighted, one-time
request for the user's EndNote .Data folder / reference PDFs, and full-text
extraction via the ladder before the evidence loop
(food-research/references/full-text-access.md).