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seaborn

Statistical visualization. Scatter, box, violin, heatmaps, pair plots, regression, correlation matrices, KDE, faceted plots, for exploratory analysis and publication figures.

63

Quality

75%

Does it follow best practices?

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SecuritybySnyk

Passed

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tessl review fix ./bundled/skills/seaborn/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

78%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 content is highly actionable with comprehensive executable examples and excellent progressive disclosure via real reference files, but it is longer than necessary and explains some fundamentals Claude already knows.

Suggestions

Trim or relocate basic conceptual explanations (long-form vs wide-form data, palette type descriptions) into the reference files to reduce token load in SKILL.md.

Add a brief 'pick a plot by data shape' decision workflow with an explicit checkpoint (e.g. 'if variables are both continuous, use scatterplot; if aggregation is needed, use lineplot with errorbar').

Consolidate the per-category 'Key parameters' lists into the function_reference.md file, keeping only the most-used parameters inline.

DimensionReasoningScore

Conciseness

The body is mostly an efficient function catalog with runnable examples, but it is long and explains some basics Claude already knows (e.g. long-form vs wide-form data, palette descriptions) that could be trimmed or moved to references.

3 / 5

Actionability

Abundant copy-paste-ready, executable code blocks cover the common cases across every plot category, grids, theming, and troubleshooting, with specific parameters and concrete examples.

5 / 5

Workflow Clarity

Plotting is non-destructive so heavy validation is not required; the 'Choose the Right Plot Type' decision table and 'When to use' guidance provide a clear selection sequence, though there is no explicit multi-step workflow with checkpoints.

4 / 5

Progressive Disclosure

The body is a clear overview with well-signaled, one-level-deep references to real bundle files (function_reference.md, objects_interface.md, examples.md) listed in a Resources section, keeping detailed material out of the main file.

5 / 5

Total

17

/

20

Passed

Description

71%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 specific and well-stocked with natural trigger terms for a clearly distinct niche, but it lacks an explicit 'Use when…' trigger clause, leaving the 'when' only weakly implied.

Suggestions

Add an explicit 'Use when…' clause naming concrete triggers, e.g. 'Use when creating statistical plots, exploring distributions, or building publication figures from DataFrames.'

Include common synonyms and loose phrasings users might say (e.g. 'statistical plots', 'distribution plots', 'data visualization') to broaden trigger coverage.

Mention the library name 'seaborn' explicitly in the description so users who name the library trigger the skill directly.

DimensionReasoningScore

Specificity

Lists multiple concrete plot types — 'Scatter, box, violin, heatmaps, pair plots, regression, correlation matrices, KDE, faceted plots' — giving comprehensive coverage of the skill's capabilities.

5 / 5

Completeness

The 'what' is clear and detailed, but there is no explicit 'Use when…' clause; the trailing 'for exploratory analysis and publication figures' only weakly implies the when, capping completeness at 3 per the rubric.

3 / 5

Trigger Term Quality

Strong natural terms (scatter, box, heatmaps, pair plots, KDE, correlation matrices) that users would say, but missing common synonyms and lacks file-extension-style triggers; not fully comprehensive.

4 / 5

Distinctiveness Conflict Risk

The statistical-visualization niche and specific plot-type catalog distinguish it from generic plotting skills, with only minor overlap risk against broad matplotlib/plotting skills.

4 / 5

Total

16

/

20

Passed

Validation

93%

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

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (668 lines); consider splitting into references/ and linking

Warning

Total

15

/

16

Passed

Repository
foryourhealth111-pixel/Vibe-Skills
Reviewed

Table of Contents

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