fcr-experimental-design
Use when designing or defending the field-experiment or modelling design of a Field Crops Research (FCR) manuscript — multi-environment trials, randomization and replication, blocking and split-plot layouts, genotype-by-environment (G×E) structure, and crop-model calibration/validation. FCR expects field experiments to span at least two seasons and/or multiple environments. Strengthens the design; it does not write code.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill fcr-experimental-design --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.
# Experimental Design (fcr-experimental-design) FCR is demanding about **field-experimental rigour**. The design must credibly connect the agronomic question to evidence that generalises across environments. The single most important FCR-specific rule: field experiments should, unless exceptional circumstances apply, span **at least two seasons and/or multiple locations/environments**. Design for that from the start. ## When to trigger - Planning a multi-environment trial (MET) or a season×site×treatment layout - A reviewer questioned randomization, replication, blocking, or G×E inference - Deciding how to characterise environments (soil, weather, phenology) - Designing a crop-modelling study (calibration/validation, scenario design) ## Field-experiment design essentials - **Multi-environment by design.** Plan ≥ 2 seasons and/or multiple sites; define what an "environment" is (site×year, managed water/N regime). State why the set spans the target population of environments. - **Randomization & replication.** Use a proper randomized design (RCBD, **resolvable incomplete-block / alpha-lattice**, split-plot for factor hierarchies, strip-plot, augmented for many genotypes). State repli
- When to trigger
- Field-experiment design essentials
- Genotype/treatment × environment (G×E)
- Crop-modelling design
- The generalisation test (FCR-specific)
- Design-choice decision table (match layout to the question)
- Sizing anchors (illustrative, hedged)
- Worked design vignette (illustrative)
- Anti-patterns
- Output format
- Supplementary resources
What does the fcr-experimental-design skill do?
Use when designing or defending the field-experiment or modelling design of a Field Crops Research (FCR) manuscript — multi-environment trials, randomization and replication, blocking and split-plot layouts, genotype-by-environment (G×E) structure, and crop-model calibration/validation. FCR expects field experiments to span at least two seasons and/or multiple environments. Strengthens the design; it does not write code.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill fcr-experimental-design --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.