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scientific-figure-making

Covers publication-ready matplotlib figures for academic papers, slides, and reports—bars, trends, scatter, heatmaps, and multi-panel layouts—with this repository’s house style, print/vector export conventions, and parity with figures4papers demos. Use when the user is finalizing or creating such figures in matplotlib. Do not use for interactive dashboards or web viz (Plotly, Altair, Bokeh), exploratory-only plots without a publication target, dominant 3D or geographic mapping, or Illustrator/Figma-first infographic workflows.

70

Quality

86%

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SKILL.md
Quality
Evals
Security

Quality

Content

72%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is a tight, well-structured index that practices what it preaches on progressive disclosure, with all referenced files present. Its weakness is actionability and workflow clarity: it defers all executable figure-making guidance to the reference files without surfacing even a minimal quick-start snippet.

Suggestions

Add a short 'Quick start' snippet showing one canonical figure (e.g., a styled grouped bar) so the body is actionable on its own before forcing a reference hop.

Include a minimal step sequence for the common case (pick demo -> match PALETTE/fonts -> export PDF/SVG) with a verification checkpoint that the exported file renders and matches house style.

Surface 2-3 key house-style constants (e.g., the PALETTE name, default DPI, font) inline so common cases don't require opening references/api.md.

DimensionReasoningScore

Conciseness

The ~25-line body is lean and assumes Claude's competence — it explains only the repo-specific house-style context and navigation rules, with no padding or basic-concept re-explanation.

5 / 5

Actionability

It offers concrete navigation guidance (a file table with 'Open when' triggers and an explicit 'do not preload' rule) but no executable code or commands, leaving the actual figure-making steps deferred to the reference files.

3 / 5

Workflow Clarity

A rough sequence is present ('Start from the table below, then follow links inside the document you opened') but there are no validation checkpoints; acceptable for an index skill yet not a fully sequenced workflow.

3 / 5

Progressive Disclosure

Clear overview with a well-signaled one-level-deep reference table; all five referenced files exist in references/ and the 'open only as needed' instruction prevents eager loading.

5 / 5

Total

16

/

20

Passed

Description

100%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is exemplary: concrete capabilities, natural trigger terms, explicit use/don't-use guidance, and strong boundary setting against adjacent visualization skills. Third-person voice is maintained throughout with no fluff.

DimensionReasoningScore

Specificity

Lists multiple concrete actions and figure types — 'bars, trends, scatter, heatmaps, and multi-panel layouts' plus 'print/vector export conventions' — matching the comprehensive-coverage anchor.

5 / 5

Completeness

Explicitly answers both 'what' (publication-ready matplotlib figures with house style and export conventions) and 'when' ('Use when the user is finalizing or creating such figures in matplotlib'), plus exclusion triggers.

5 / 5

Trigger Term Quality

Natural user-facing terms abound — 'matplotlib figures', 'papers, slides, or reports', 'PDF/SVG/high-DPI', 'heatmaps', 'figures4papers' — covering synonyms and concrete formats users would actually say.

5 / 5

Distinctiveness Conflict Risk

A clear niche (matplotlib publication figures for this repo) with explicit exclusions for Plotly/Altair/Bokeh, EDA-only, 3D/GIS, and Illustrator/Figma minimizes conflict with adjacent skills.

5 / 5

Total

20

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
ChenLiu-1996/figures4papers
Reviewed

Table of Contents

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