frontend-design

Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.

Quality

71%

Does it follow best practices?

Impact

Pending

No eval scenarios have been run

Securityby

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./.agents/skills/frontend-design/SKILL.md

Quality

Discovery

92%

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

This is a strong skill description that clearly communicates both what the skill does and when to use it, with rich trigger terms covering many natural user phrasings. The main weakness is its broad scope which could potentially overlap with other coding or component-building skills, though the emphasis on design quality and avoiding generic AI aesthetics provides some differentiation. The description uses proper third-person voice throughout.

Dimension	Reasoning	Score
Specificity	Lists multiple specific concrete actions and outputs: 'web components, pages, artifacts, posters, applications' with further examples like 'websites, landing pages, dashboards, React components, HTML/CSS layouts'. Also specifies the quality dimension: 'production-grade', 'polished code and UI design', 'avoids generic AI aesthetics'.	3 / 3
Completeness	Clearly answers both 'what' (create distinctive, production-grade frontend interfaces) and 'when' with an explicit 'Use this skill when...' clause listing specific trigger scenarios including building web components, pages, applications, and styling/beautifying web UI.	3 / 3
Trigger Term Quality	Excellent coverage of natural terms users would say: 'web components', 'pages', 'artifacts', 'posters', 'applications', 'websites', 'landing pages', 'dashboards', 'React components', 'HTML/CSS layouts', 'styling', 'beautifying', 'web UI'. These are terms users would naturally use when requesting frontend work.	3 / 3
Distinctiveness Conflict Risk	While it focuses on frontend/UI with a design quality emphasis, the broad scope ('web components, pages, applications, dashboards, React components, HTML/CSS') could overlap with general coding skills or React-specific skills. The 'high design quality' and 'avoids generic AI aesthetics' differentiators help but the domain is still quite wide.	2 / 3
	Total	11 / 12 Passed

Implementation

50%

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

This skill provides a solid conceptual framework for creating distinctive frontend interfaces with good anti-pattern identification (avoiding generic AI aesthetics). Its main weaknesses are the lack of concrete, executable code examples for a code-generation skill, some verbosity in motivational language, and missing validation checkpoints in the workflow. The guidance is directional rather than precisely actionable.

Suggestions

Add 1-2 concrete code examples showing a well-implemented component with recommended CSS variables, typography pairing, and animation patterns — this would dramatically improve actionability for a frontend skill.

Trim motivational/aspirational language ('Claude is capable of extraordinary creative work', 'show what can truly be created') which wastes tokens without adding actionable guidance.

Add explicit validation steps to the workflow: e.g., 'Verify: Does the output avoid all listed anti-patterns? Test responsiveness at 3 breakpoints. Check color contrast ratios for accessibility.'

Consider creating a bundle reference file (e.g., EXAMPLES.md or PATTERNS.md) with curated font pairings, color palette examples, and animation snippets to keep the main skill lean while providing depth.

Dimension	Reasoning	Score
Conciseness	The skill contains some unnecessary motivational language ('Claude is capable of extraordinary creative work', 'Don't hold back') and repetitive emphasis on avoiding generic aesthetics (stated multiple times). The design thinking section and aesthetics guidelines are mostly useful but could be tightened. Some phrases like 'There are so many flavors to choose from' add no value.	2 / 3
Actionability	The skill provides concrete design principles and specific anti-patterns (e.g., avoid Inter, Roboto, purple gradients on white), which is useful guidance. However, it lacks any executable code examples, specific CSS snippets, or concrete implementation patterns. For a frontend skill, showing at least one example of a well-structured component with the recommended CSS variable approach, animation pattern, or typography pairing would significantly improve actionability.	2 / 3
Workflow Clarity	There is a loose two-phase workflow (design thinking → implementation) but no explicit validation steps. For a skill producing production-grade frontend code, there should be checkpoints like verifying accessibility, testing responsiveness, or validating that the output matches the aesthetic direction. The design thinking section has a reasonable checklist structure but the implementation phase is vague ('Then implement working code').	2 / 3
Progressive Disclosure	The content is organized into clear sections (Design Thinking, Frontend Aesthetics Guidelines) which is good. However, the aesthetics guidelines section is quite long and inline — font pairing examples, animation patterns, or layout techniques could be split into referenced files. With no bundle files, everything is monolithic. For a skill of this scope, a reference file with example implementations or a typography/color cheat sheet would improve organization.	2 / 3
	Total	8 / 12 Passed

Validation

100%

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 — 11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository: databricks/devhub
Commit: 6338825

Reviewed: about 8 hours ago

Table of Contents

Discovery Implementation Validation

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