agentsclimarketplace

Fcr figures and tables

Skill brycewang-stanford/Awesome-Journal-Skills/Field-Crops-Research-Skills/skills/fcr-figures-and-tables

Journal-specific Claude Code/Codex skill packs covering mainstream journals — AER, QJE, Nature, Cell, 管理世界, 经济研究 & 200+ more — your fast track to getting published. | 覆盖主流期刊的 Claude Code/Codex 期刊技能包,从选题、识别策略到表格规范与审稿回复全流程,助你快速发论文。

Install
npx -y skills add brycewang-stanford/Awesome-Journal-Skills --skill fcr-figures-and-tables

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

What its author says it does

Copied from the file, not written here

Use when building tables and figures for a Field Crops Research (FCR) manuscript so exhibits are self-contained, quantitatively complete, and agronomically informative — yield and response curves, AMMI/GGE biplots, observed-vs-simulated plots, and weather-vs-phenology series. FCR exhibits must show units, error (SED/LSD), and sample structure. Designs exhibits; it does not run the analysis.

SKILL.md

5.9 KB, as published. Nobody here has run it

Figures & Tables (fcr-figures-and-tables)

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.

When to trigger

  • Designing the main results table/figure or a key descriptive exhibit
  • Deciding what belongs in the article vs. supplementary material
  • A reviewer found an exhibit unclear, mislabeled, or missing error/units
  • Presenting G×E, response curves, or model evaluation

Principles

  1. Self-contained. A reader should understand each exhibit from its caption, axis/column labels, and footnote alone. State the crop, cultivar(s), environments (sites×seasons), N/replication, units (SI), and what the value is (mean? adjusted mean?).
  2. Show the error. Yield and treatment means need SED or LSD (with α and df) or error bars defined in the caption — never bare means. For curves, show fitted line + CI and the data.
  3. Right exhibit for the question. Use a response curve for quantitative factors (N, water, density); an AMMI/GGE biplot or Finlay–Wilkinson plot for G×E; observed-vs-simulated with the 1:1 line for model evaluation; time series vs. thermal time/phenology with weather overlays for development.
  4. Accessible. Colourblind-safe palettes; legible in grayscale; no chartjunk, no 3D, no needless colour. Vector output (PDF/EPS) for print.
  5. Reproducible & consistent. Numbers match the analysis script and the deposited data; table and figure values are internally consistent and consistent with the text.

Agronomy-specific exhibits

  • Yield-gap / boundary-line plots; nitrogen- and water-response curves with fitted models.
  • AMMI biplots, GGE biplots, Finlay–Wilkinson stability regressions for multi-environment data.
  • Weather (rainfall, temperature, radiation) shown against crop phenology (sowing, anthesis, maturity).
  • Maps where spatial/regional variation is the point; observed-vs-simulated panels for modelling.

Exhibit-selection table (question → exhibit → annotation)

The right exhibit follows from the agronomic question. Pair each with the annotation an FCR reviewer expects.

QuestionExhibitMust annotate
Yield vs. N/water/densityfitted response curve + pointsmodel, SED or CI, units
Genotype rankingAMMI / GGE / Finlay–Wilkinsonenvironments labelled, % variance
Model performanceobserved-vs-simulated, 1:1 lineRMSE, nRMSE, EF, n; validation only
Treatment means by environmentadjusted-means tableSED/LSD, α, df, replication

Worked exhibit vignette (illustrative)

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.

Anti-patterns

  • Means with no SED/LSD, error bars, or units
  • Mean-separation letters on a quantitative dose where a response curve is appropriate
  • Tables that need the prose to be intelligible (not self-contained)
  • Colour-only encoding that fails in grayscale or for colourblind readers
  • Exhibit values that don't match the analysis output or the data deposit

Operating pass for Field Crops Research

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.

  • Do the pass: Return a claim-evidence-risk ledger rather than a prose-only diagnosis; every recommendation must point to a manuscript location or missing artifact.
  • Return a ledger: give claim / evidence / risk / manuscript location rows, so the next agent can edit rather than rediscover the issue.
  • Sibling guard: compare against Agricultural Systems for whole-system modeling, European Journal of Agronomy for agronomic breadth, Crop Science for cultivar or breeding emphasis; if a sibling owns the contribution, recommend re-routing before polishing format.
  • Submission-ready gate: do not give final advice until the pack's 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.

Output format

【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

Supplementary resources

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.