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dataviz

Design guidance for charts, graphs, dashboards, maps, and data visualizations, including a local palette validator.

Quality

78%

Does it follow best practices?

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Adds up to 20 points to the overall score

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SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./packages/core/src/skills/bundled/dataviz/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

86%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 an exemplary lean overview: a clear sequenced workflow, an executable palette-validation command with failure semantics, and well-signaled one-level-deep references that all exist in the bundle. The only gaps are the path placeholder in the run command and the absence of an explicit re-validate loop after a FAIL.

DimensionReasoningScore

Conciseness

The ~50-line body is lean and operational throughout ("Prefer direct labels over legends", "Keep gridlines subtle and fewer than the data marks") with zero padding or explanation of concepts Claude already knows. Every token earns its place.

5 / 5

Actionability

The body gives an executable command with concrete arguments and explicit FAIL/WARN handling, plus a concrete 5-step workflow referencing specific files. Not 5 because the command uses the non-copy-paste placeholder `<skill-base-directory>` rather than a resolvable path.

4 / 5

Workflow Clarity

The 5-step workflow (task → form → title → colors/validate → anti-patterns) is clearly sequenced with an explicit validation checkpoint and FAIL/WARN remediation guidance. Not 5 because there is no explicit re-validation loop after fixing a FAIL, and the final anti-pattern check is stated without what to do if violations are found.

4 / 5

Progressive Disclosure

The body is a concise overview with three well-signaled, condition-scoped references (`references/choosing-a-form.md` "when the form is not obvious", `references/palette.md`, `references/anti-patterns.md` "before finalizing") plus a script, all verified to exist and only one level deep.

5 / 5

Total

18

/

20

Passed

Description

61%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 names a clear visualization domain with strong natural trigger terms and a distinctive niche, but it lacks an explicit "Use when..." trigger clause and offers only one concrete capability (the palette validator). Moving the when_to_use triggers into the description and enumerating the skill's concrete actions would lift it substantially.

Suggestions

Add an explicit "Use when..." clause to the description (e.g., "Use when creating or revising charts, graphs, plots, dashboards, or maps") — its absence caps completeness at 3 even though the frontmatter already has a when_to_use field.

Enumerate 2-3 more concrete capabilities in the description (e.g., choosing chart forms, validating palettes, checking anti-patterns) instead of the generic "Design guidance for".

Include common synonyms and formats users actually say ("plots", "data viz", "inline SVG", library names like matplotlib/D3/Plotly) to raise trigger term coverage.

DimensionReasoningScore

Specificity

"Design guidance for charts, graphs, dashboards, maps, and data visualizations" names the domain, and "including a local palette validator" is one concrete capability, matching the anchor for domain plus 1-2 concrete actions. It is not 4 because the description lists no other concrete actions (form selection, anti-pattern checks are only in the body), and not 2 because it goes beyond a bare domain mention.

3 / 5

Completeness

The description has a clear "what" (design guidance for visualizations plus a local palette validator) but contains no "Use when..." clause or equivalent explicit trigger guidance, which caps completeness at 3 per the judging guidelines. The separate when_to_use frontmatter field is not part of the description being evaluated.

3 / 5

Trigger Term Quality

"charts, graphs, dashboards, maps, and data visualizations" are natural terms users would say when they need this skill, giving good coverage. Not 5 because common variations such as "plots", "data viz", library names (matplotlib, D3), and file formats are missing from the description field.

4 / 5

Distinctiveness Conflict Risk

Charts, graphs, dashboards, and maps form a clear dataviz niche with distinct triggers and low conflict risk. Not 5 because "Design guidance" is broad enough to marginally overlap with general UI/styling/brand-design skills.

4 / 5

Total

14

/

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.

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository

QwenLM/qwen-code

Path

packages/core/src/skills/bundled/dataviz/SKILL.md

Reviewed

Table of Contents

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