Conciseness

At 781 lines the body is noticeably verbose with pervasive verbatim duplication: the seaborn boxplot/stripplot block appears twice, the correlation-heatmap block twice, the Okabe-Ito palette list twice, and set_theme/despine guidance is repeated across multiple sections. It also explains concepts Claude already knows ('Seaborn provides a high-level, dataset-oriented interface for statistical graphics, built on matplotlib' plus generic library advantages), matching anchor 2 rather than the occasional over-explanation of anchor 3.

Actionability

Provides extensive concrete code, and the claimed helpers were verified to exist (save_publication_figure/save_for_journal/check_figure_size in scripts/figure_export.py, apply_publication_style/configure_for_journal in scripts/style_presets.py, OKABE_ITO_LIST/apply_palette in assets/color_palettes.py). Minor gaps keep it below anchor 5: many snippets use undefined variables (df, timeseries, x_jittered, datasets) and script imports assume path setup, so they are not fully copy-paste ready.

Workflow Clarity

The Workflow Summary gives a clear sequenced process (Plan, Configure, Create, Verify, Export, Review) with inline commands, an explicit Verify step (check_figure_size), a fix-an-existing-figure checklist (Task 5), and a Final Checklist. It lacks an error-recovery feedback loop (no guidance on what to do when a check fails), which is the anchor-5 requirement, so it sits at anchor 4; no destructive/batch cap applies.

Progressive Disclosure

Scored against the actual bundle: the four references/, two scripts/, and four assets/ files are real, listed, and described in the Resources section, one level deep. However, the ~250-line seaborn section inlines content that belongs in a reference file, and it cites scientific-packages/seaborn/SKILL.md plus three of its reference files (lines 648-651) that do not exist in the bundle — dangling references. This matches anchor 3 ('content that should be separate is inline') rather than the well-split structure of anchor 4.

Specificity

Lists several concrete items — 'multi-panel layouts, significance annotations, error bars, colorblind-safe palettes', 'specific journal formatting (Nature, Science, Cell)' — but the action verbs are thin ('Meta-skill for publication-ready figures', 'Orchestrates matplotlib/seaborn/plotly'), so the concrete items read as output features rather than the comprehensive concrete actions of the anchor-5 example. Clearly above anchor 3, which covers only 1-2 concrete actions.

Completeness

Explicitly answers 'when' with a strong trigger clause ('Use when creating journal submission figures requiring multi-panel layouts, significance annotations, error bars, colorblind-safe palettes...'), and states 'what' ('publication-ready figures', 'Orchestrates matplotlib/seaborn/plotly with publication styles'). Falls between anchors 4 and 5: the when-clause is more explicit than the anchor-4 example, but the what relies on jargon ('meta-skill') and the when-clause for its concreteness, unlike the direct verb list in the anchor-5 example.

Trigger Term Quality

Contains natural phrases users would say: 'publication-ready figures', 'journal submission figures', 'multi-panel layouts', 'error bars', 'colorblind-safe palettes', plus journal names and library names. Missing common synonyms such as 'manuscript figure' or 'figure for my paper', matching anchor 4 ('good keyword coverage; a few natural terms missing') rather than the comprehensive synonym spread of anchor 5.

Distinctiveness Conflict Risk

Occupies a clear niche (journal submission figures, named journals) and includes a boundary statement ('For quick exploration use seaborn or plotly directly') that hands off generic plotting work. Minor overlap risk remains with general dataviz/plotting skills because it names all three plotting libraries, matching anchor 4 ('mostly distinct; minor overlap risk') rather than the minimal-conflict clarity of anchor 5.