本文へ移動
cccskills
無料GitHub で公開

agsy-topic-selection

Use when deciding whether a project fits Agricultural Systems (AgSy) and which article type to target. AgSy is a systems-science journal, so the test is a genuine systems question — interactions among components, across hierarchical levels (field → farm → landscape → region → food system), trade-offs, and emergent behavior — analyzed with integrated modelling, NOT a single-factor field trial. Helps frame the question; it does not collect data.

インストール方法を見る

含まれるファイル(1)

  • SKILL.md6.4 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Topic Selection & Fit (agsy-topic-selection)

Agricultural Systems publishes the systems analysis of agricultural systems. The bar is not "a new result for crop X" — it is "a systems question about interactions and trade-offs." Use this skill to pressure-test fit before you invest, and to keep a field trial from being mistaken for a systems paper.

When to trigger

  • Choosing among possible projects or framings for an AgSy submission
  • A reviewer/colleague said the paper "is just a field trial" or "lacks a systems angle"
  • Deciding between a research paper and a short communication
  • Considering a perspective (forward-looking opinion) or a comment on a published paper

The AgSy fit test

A strong AgSy paper usually clears all four:

  1. A real systems question. The object is interactions — among components (crop–soil–livestock– economics), across hierarchical levels, between agriculture and other land uses, or with the natural/social/economic environment. If nothing interacts, it is not a systems paper.
  2. Whole-farm to food-system scope (preferred). AgSy gives preference to whole-farm and landscape-level issues. A plot-level result needs to be scaled or embedded in a larger system.
  3. Integrated modelling and trade-offs. Conceptual + empirical + dynamic / bio-economic modelling; the analysis surfaces trade-offs and synergies, not a single optimal number.
  4. Decision relevance. The result informs a design, management, or policy choice (see agsy-impact-and-implications).

Scale & system-boundary framing (state your system explicitly)

If your work is at…reach AgSy fit by…
Field / plotscaling to the farm or showing the field-level interaction that matters to the system
Whole-farmthe journal's sweet spot — show component interactions and whole-farm trade-offs
Landscape / regionspatial interactions, land-use competition, aggregation/emergence across farms
Food systemlinking production to value chains, food security, environment, and policy

Article-type choice

  • Research paper — full systems study, ~8,000 words (no hard cap; stay near it).
  • Short communication — one crisp systems result, ~4,000 words. Do not pad it into a paper.
  • Perspective — a forward-looking argument about agricultural-systems science, ~2,000 words, rapid review (see agsy-review-process).
  • Comment — a focused response to a published AgSy paper, ~1,000 words.
  • Review — usually method-application focused rather than descriptive synthesis; consult editors first where the Guide requires it.

Anti-patterns

  • A single-factor field trial with no interactions, model, or trade-off (off-fit — send to an agronomy journal)
  • "First time simulated in country X" as the whole contribution (descriptive, not a systems advance)
  • A model demo with no agricultural-systems question or decision payoff
  • Choosing research-paper length out of habit when a short communication would land harder

Fit verdict table (how the four-part test maps to a decision)

Score the project against the four fit criteria, then read off the verdict.

Systems QScopeTrade-offsDecisionVerdict
YesYesYesYesStrong AgSy fit — proceed
YesFieldYesYesNeeds scaling: embed in a farm/landscape system
YesYesOne optimumYesReframe: surface the trade-off across objectives
No———Off-fit — re-route to an agronomy/field-crops journal
YesYesYesNoAdd the decision hook (agsy-impact-and-implications)

Sibling-venue routing (where a near-miss belongs)

When a project lands near the boundary, route it deliberately:

  • Plot-/agronomy-level result, one crop, no system → a field-crops/agronomy journal, not AgSy.
  • Economics-first decision with light biophysics → an agricultural-economics outlet; AgSy expects biophysical and socioeconomic integration.
  • Policy synthesis with no model → a food-security/policy journal; AgSy wants the systems analysis.

Worked micro-example (illustrative)

A team has trial data showing a legume intercrop raises maize yield:

  • Systems question? As "intercrop raises yield" — no. Reframed as "how the legume–maize–soil-N interaction shifts the whole-farm yield–nitrogen-leaching trade-off under variable rainfall" — yes.
  • Scope? The plot-level trial is embedded in a whole-farm bioeconomic model.
  • Trade-offs? Scenarios span intercrop share 0–50%; the gross-margin vs. N-leaching Pareto front is the headline, not a single "best" share.
  • Decision relevance? A farmer choosing rotation intensity acts differently. Verdict: strong AgSy fit.

Calibration anchors

  • AgSy's remit centers on interactions, hierarchical levels, trade-offs, and integrated modelling at farm/landscape/food-system scale; live-check the current aims-and-scope statement before final submission advice.
  • The article-type lengths are guidelines, not hard caps; live-check the Guide before final upload.

Output format

【Question】one sentence (state the interaction / trade-off)
【System & boundary】components + hierarchical level(s) + scale
【Modelling approach】conceptual / empirical / dynamic / bio-economic
【Decision relevance】who acts differently if this is true
【Article type】Research paper / Short communication / Perspective / Comment / Review
【Fit verdict】strong / needs reframing / off-fit (why)
【Next】agsy-literature-positioning

Supplementary resources

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

Use when packaging AAAI code, data, multimedia appendices, technical appendices, reproducibility evidence, and post-acceptance artifact releases without violating double-blind or immutable-supplement rules.

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Awesome-Journal-Skills1,2482026年9月27日 更新

Use when drafting an AAAI author response (rebuttal) under the single short character-limited author-feedback window, the no-URL rule, no-new-results guidance, AI-generated-review handling, and the AAAI two-phase review process where Phase-2 papers receive one feedback round before SPC/AC discussion.

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Awesome-Journal-Skills1,2482026年9月27日 更新

Use when preparing an accepted AAAI paper for camera-ready source submission to AAAI Press, including proceedings page limits, two-column template compliance, copyright transfer, purchased extra technical pages, deanonymization, registration, oral or poster presentation, and final public artifact release.

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Awesome-Journal-Skills1,2482026年9月27日 更新

Use when designing or auditing AAAI experiments for the broad-AI program committee, including baselines, ablations, statistical significance, robustness, human evaluation, AI-for-Social-Impact and alignment/safety evidence, compute and cost reporting, and reproducibility-checklist alignment for Phase-1 survival.

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Awesome-Journal-Skills1,2482026年9月27日 更新

Use when positioning an AAAI paper's novelty against archival work, contemporaneous arXiv or workshop papers, and AAAI/IJCAI/NeurIPS/ICML/ICLR neighbors across the broad AI scope, while staying inside AAAI's dual-submission and AI-as-source policy constraints and writing a related-work section legible to non-specialist reviewers.

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Awesome-Journal-Skills1,2482026年9月27日 更新

Use when strengthening an AAAI paper's reproducibility checklist (placed after references), experimental traceability, seed and hyperparameter reporting, compute and cost disclosure, dataset access and licensing, code/data ZIP readiness, and the claim-to-evidence map that Phase-1 reviewers use to judge rigor across AAAI's broad AI scope.

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Awesome-Journal-Skills1,2482026年9月27日 更新

brycewang-stanford のスキルをすべて見る

このスキルの問題を報告する