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.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill agsy-topic-selection --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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
- When to trigger
- The AgSy fit test
- Scale & system-boundary framing (state your system explicitly)
- Article-type choice
- Anti-patterns
- Fit verdict table (how the four-part test maps to a decision)
- Sibling-venue routing (where a near-miss belongs)
- Worked micro-example (illustrative)
- Calibration anchors
- Output format
- Supplementary resources
What does the agsy-topic-selection 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.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill agsy-topic-selection --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From brycewang-stanford/Awesome-Journal-Skills, a repository with 909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.