creating-data-visualizations

Create analytical charts and plots from existing data. Use for exploratory or reporting visuals such as bars, lines, scatters, and dashboards; not for publication-grade scientific figures or AI-generated schematics.

Quality

66%

Does it follow best practices?

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Securityby

Passed

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tessl review fix ./bundled/skills/creating-data-visualizations/SKILL.md

Quality

Content

50%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 concise and well-structured as a routing/decision guide, but it is largely descriptive rather than actionable and fails to connect to its own bundled scripts and references. Adding concrete execution guidance and pointers to the bundle would substantially raise its scores.

Suggestions

Reference and show how to invoke the bundled scripts (e.g., data_validator.py to validate input, data_analyzer.py to pick a chart type, chart_generator.py to produce code) so the skill is executable rather than descriptive.

Add a short sequenced workflow with a validation checkpoint before chart generation, leveraging data_validator.py.

Link to the bundled reference files (visualization_best_practices.md, library tutorials) from the relevant sections so progressive disclosure is properly signaled.

Dimension	Reasoning	Score
Conciseness	The body is lean and assumes Claude's competence without explaining what charts are, though the chart-type lists in 'Overview' and 'When to Use This Skill' overlap redundantly and could be tightened.	4 / 5
Actionability	The body describes what to produce and when, but gives no executable guidance—no library choice, no code, and no reference to the bundled chart_generator.py/data_analyzer.py/data_validator.py scripts—leaving only high-level hints.	2 / 5
Workflow Clarity	Sections are organized but there is no sequenced process (e.g., validate data, analyze, generate chart) and no validation checkpoint, even though the bundle contains a data_validator.py implying one.	3 / 5
Progressive Disclosure	The body is well-sectioned and short, but it never signals the bundled scripts or reference files that actually exist, so navigation to those materials is missing rather than clearly referenced.	3 / 5
	Total	12 / 20 Passed

Description

83%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.

A strong, concise description that clearly states what the skill does and when to use it, with a well-drawn boundary against publication-grade work. It is mostly distinct and trigger-rich, with only minor gaps in action variety and synonyms.

Dimension	Reasoning	Score
Specificity	Names the domain and concrete outputs ('analytical charts and plots', 'bars, lines, scatters, and dashboards') but offers essentially one action verb (create) rather than multiple distinct actions, leaving minor coverage gaps.	4 / 5
Completeness	Explicitly answers both 'what' ('Create analytical charts and plots from existing data') and 'when' ('Use for exploratory or reporting visuals such as...') with concrete trigger phrases and a clear not-for boundary.	5 / 5
Trigger Term Quality	Good natural keyword coverage ('charts', 'plots', 'bars, lines, scatters', 'dashboards', 'exploratory', 'reporting visuals') that users would actually say, though common synonyms like 'graphs' are missing.	4 / 5
Distinctiveness Conflict Risk	Clear analytical/exploratory niche with an explicit 'not for publication-grade scientific figures' boundary, but minor overlap risk with closely related skills like exploratory-data-analysis.	4 / 5
	Total	17 / 20 Passed

Validation

87%

Warnings & errors only

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

Validation — 14 / 16 Passed

Validation for skill structure

Criteria	Description	Result
allowed_tools_field	'allowed-tools' contains unusual tool name(s)	Warning
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	14 / 16 Passed

Repository: foryourhealth111-pixel/Vibe-Skills
Path: bundled/skills/creating-data-visualizations/SKILL.md
Commit: d5ae560

Reviewed: 1 day ago

Table of Contents

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