From fcr-skills
Designs self-contained, quantitatively complete tables and figures for Field Crops Research manuscripts: yield/response curves, AMMI/GGE biplots, observed-vs-simulated plots, and weather-vs-phenology series with units, error (SED/LSD), and sample structure.
How this skill is triggered — by the user, by Claude, or both
Slash command
/fcr-skills:fcr-figures-and-tablesThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Exhibits are where an agronomy reviewer checks whether the result is real and general. At FCR every
Exhibits are where an agronomy reviewer checks whether the result is real and general. At FCR every exhibit must be self-contained and quantitatively complete: units, sample/replication, and a measure of error or variability (SE, SED, or LSD) belong on the exhibit itself.
The right exhibit follows from the agronomic question. Pair each with the annotation an FCR reviewer expects.
| Question | Exhibit | Must annotate |
|---|---|---|
| Yield vs. N/water/density | fitted response curve + points | model, SED or CI, units |
| Genotype ranking | AMMI / GGE / Finlay–Wilkinson | environments labelled, % variance |
| Model performance | observed-vs-simulated, 1:1 line | RMSE, nRMSE, EF, n; validation only |
| Treatment means by environment | adjusted-means table | SED/LSD, α, df, replication |
Illustrative. A first-draft Table 2 for the maize MET lists raw plot means with a/b/c letters across all 5 N rates and no error term — two flags at once: letters on a quantitative dose hide the response shape, and raw means do not match the mixed-model output. The fix is two exhibits: an N response curve per environment with fitted line and SED bar (α = 0.05), plus an adjusted-means table with one SED column — both self-contained and reproducible from the script.
Treat this skill as an executable review pass, not a prose hint. First lock the crop system, environment structure, GxE logic, and yield or physiology endpoint; then judge whether the current manuscript answers the venue's real reader: agronomy reviewers who expect field-based, multi-environment evidence and crop-level general significance.
claim / evidence / risk / manuscript location rows, so the next agent can edit rather than rediscover the issue.resources/official-source-map.md has been checked for upload-week rules and the manuscript has one concrete fix for the largest venue-specific risk.【Main exhibit】what it shows + why this exhibit type
【Self-contained?】caption + labels + crop/cultivar + envs + N + units present? [Y/N]
【Error shown?】SED / LSD / CI with α stated? [Y/N]
【Accessible?】grayscale-legible + colourblind-safe? [Y/N]
【Article vs supplement】split decided
【Reproducible?】matches analysis output + data deposit? [Y/N]
【Next】fcr-reporting-and-data-policy
../../resources/external_tools.md — plotting and G×E-biplot tooling../../resources/official-source-map.md — reporting expectations (units, weather vs. phenology)npx claudepluginhub brycewang-stanford/awesome-journal-skills --plugin fcr-skillsDesigns figures and tables for Agricultural Systems manuscripts to communicate interactions, trade-offs, and model performance. Guides choosing exhibit types like Pareto frontiers and observed-vs-simulated plots.
Guides building figures, tables, and graphical abstracts for Global Change Biology (GCB) manuscripts, emphasizing mechanism-first exhibits with visible uncertainty and accessibility.
Designs APA-formatted tables and figures for quantitative Communication Research manuscripts, emphasizing effect sizes and uncertainty over significance stars. Includes templates for experiment, mediation, SEM/CFA, and content-analysis exhibits.