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grammar-of-graphics-and-declarative-visualization

Build data visualizations with declarative grammars. Use when the user needs Vega-Lite, Vega, Observable Plot, or grammar-of-graphics reasoning, especially for tabular charts that do not require bespoke rendering.

68

Quality

81%

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SKILL.md
Quality
Evals
Security

Quality

Content

72%Weight 40%Scale 1-3

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

A well-organized, lean selection skill with strong progressive disclosure and a clear overview. It is held back by abstract working-pattern steps and the absence of a concrete, executable spec example or hard validation checkpoints.

Suggestions

Add one minimal copy-paste Vega-Lite or Observable Plot spec example so the skill gives executable, not just decision-level, guidance.

Tighten vague working-pattern steps ('Normalize the table shape', 'Choose the highest-level grammar') into concrete, checkable sub-actions.

Turn the 'Check whether...' steps into explicit validation gates with a clear stay-vs-leave decision so the workflow has real checkpoints.

DimensionReasoningScore

Conciseness

The body is lean and assumes Claude's competence — it avoids teaching what declarative grammars or the libraries are, and every section (selection rules, working pattern, output expectations) earns its place with only minor redundancy between sections.

3 / 3

Actionability

The selection rules give concrete tool-vs-condition guidance, but the working pattern contains vague steps like "Normalize the table shape" and there is no executable spec or code example, leaving the guidance incomplete rather than copy-paste ready.

2 / 3

Workflow Clarity

The 7-step working pattern is clearly sequenced, but the 'Check whether...' steps read as soft considerations rather than explicit validation gates with error-recovery feedback loops, so checkpoints are present-but-implicit.

2 / 3

Progressive Disclosure

The body is a concise overview pointing to well-signaled, one-level-deep references; the three skill-local ./references/*.md files exist and are organized under a clear References section with grouped navigation.

3 / 3

Total

10

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12

Passed

Description

90%Weight 40%Scale 1-3

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

A strong, well-scoped description with explicit 'Use when' triggers and natural tool-name keywords. Its only weakness is that it states a single broad action rather than enumerating several concrete capabilities.

Suggestions

Consider listing two or three concrete actions (e.g., 'compose layered specs, apply transforms and faceting, embed portable charts') to lift specificity from one broad action to a list of capabilities.

DimensionReasoningScore

Specificity

It names the domain and a concrete action ("Build data visualizations with declarative grammars") but lists only one main action rather than multiple specific concrete actions, matching the 'names domain and some actions, but not comprehensive' anchor.

2 / 3

Completeness

It explicitly answers both what ("Build data visualizations with declarative grammars") and when via an explicit "Use when the user needs Vega-Lite, Vega, Observable Plot..." trigger clause.

3 / 3

Trigger Term Quality

It surfaces natural terms users actually say — "Vega-Lite, Vega, Observable Plot" — giving good coverage of the named tools a user would mention when needing this skill.

3 / 3

Distinctiveness Conflict Risk

It carves out a clear niche (declarative grammars for tabular charts) and explicitly excludes "bespoke rendering," making it unlikely to trigger for a D3/Canvas/WebGL skill.

3 / 3

Total

11

/

12

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
openai/plugins
Reviewed

Table of Contents

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