banner-creator

Create banners using AI image generation. Discuss format/style, generate variations, iterate with user feedback, crop to target ratio. Use when user wants to create a banner, header, hero image, cover image, GitHub banner, Twitter header, or readme banner.

1.80x

Quality

92%

Does it follow best practices?

Impact

92%

1.80x

Average score across 3 eval scenarios

Securityby

Passed

No known issues

Quality

Content

85%

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

This is a well-structured skill with strong actionability and workflow clarity. The iterative design process is clearly sequenced with user checkpoints, and commands are concrete and executable. The main area for improvement is conciseness — some sections like the discovery requirements list and style preferences could be tightened since Claude can infer appropriate questions to ask.

Suggestions

Tighten the Discovery & Requirements section — instead of listing every possible platform and style, provide a brief note like 'Gather: purpose/platform, target ratio (see formats.md), style, content elements, colors' and let Claude handle the conversation naturally.

Dimension	Reasoning	Score
Conciseness	The skill is reasonably efficient but includes some unnecessary detail that Claude could infer, such as listing all possible banner purposes (GitHub README, Twitter, LinkedIn, etc.) and explaining what to ask the user in extensive detail. The prompt pattern examples and workflow steps are useful but could be tightened.	2 / 3
Actionability	Provides fully executable commands with concrete examples for each step — generation, batch generation, image editing, cropping, and HTML preview. Commands include specific flags, naming conventions, and output paths that are copy-paste ready.	3 / 3
Workflow Clarity	Clear 6-step sequential workflow with explicit checkpoints: wait for user confirmation after discovery, iterate with user feedback loop (generate → preview → feedback → regenerate), and only crop after user approval. The feedback loop for iteration is well-defined with clear re-generation and naming conventions.	3 / 3
Progressive Disclosure	Well-structured with a clear overview workflow in the main file, references to external files for detailed format information (references/formats.md) and examples (examples/opc-banner-creation.md), and templates referenced for the HTML preview. References are one level deep and clearly signaled.	3 / 3
	Total	11 / 12 Passed

Description

100%

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 what the skill does and when to use it. It lists concrete workflow actions, provides excellent trigger term coverage with platform-specific variations, and occupies a distinct niche that minimizes conflict with other skills.

Dimension	Reasoning	Score
Specificity	Lists multiple specific concrete actions: discuss format/style, generate variations, iterate with user feedback, crop to target ratio. These are clear, actionable steps in the banner creation workflow.	3 / 3
Completeness	Clearly answers both what ('Create banners using AI image generation, discuss format/style, generate variations, iterate with feedback, crop to target ratio') and when ('Use when user wants to create a banner, header, hero image, cover image, GitHub banner, Twitter header, or readme banner').	3 / 3
Trigger Term Quality	Excellent coverage of natural terms users would say: 'banner', 'header', 'hero image', 'cover image', 'GitHub banner', 'Twitter header', 'readme banner'. These are specific, varied, and match real user language.	3 / 3
Distinctiveness Conflict Risk	Highly distinctive niche focused specifically on banner/header image creation. The specific trigger terms like 'GitHub banner', 'Twitter header', 'hero image' clearly distinguish it from general image generation or design skills.	3 / 3
	Total	12 / 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: resciencelab/opc-skills
Commit: 43f1062

Reviewed: 5 days ago

Table of Contents

Discovery Implementation Validation

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