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Agsy Topic Selection

Community
franklee16
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.

Overview

Publisherfranklee16
Repositoryacademic-research-skills
Skill nameagsy-topic-selection
Stars
225
Forks
34
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by franklee16 on GitHub. Read the source before you install it.

Installation

Install the Agsy Topic Selection AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/franklee16/academic-research-skills/tree/master/Awesome-Journal-Skills-main/Agricultural-Systems-Skills/skills/agsy-topic-selection
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/franklee16/academic-research-skills.git /tmp/academic-research-skills
mkdir -p .claude/skills
cp -r /tmp/academic-research-skills/Awesome-Journal-Skills-main/Agricultural-Systems-Skills/skills/agsy-topic-selection .claude/skills/agsy-topic-selection
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Agsy Topic Selection in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Agsy Topic Selection on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Agsy Topic Selection is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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.

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

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

Frequently asked questions

What does the Agsy Topic Selection AI skill do?

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.

Why use Agsy Topic Selection on TypingMind?

Because you install it once and use it with any model. Agsy Topic Selection is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Agsy Topic Selection in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/franklee16/academic-research-skills/tree/master/Awesome-Journal-Skills-main/Agricultural-Systems-Skills/skills/agsy-topic-selection. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Agsy Topic Selection?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Agsy Topic Selection?

As many as you like. As long as a model supports skills, you can use Agsy Topic Selection with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Agsy Topic Selection AI skill free?

It is published on GitHub by franklee16. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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