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

—

Does it follow best practices?

Impact

92%

1.80x

Average score across 3 eval scenarios

Securityby

Passed

No known issues

Quality

Content

65%

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

A well-structured, actionable banner-creation workflow, but it repeats aspect-ratio information, omits verification around batch generation/cropping, and references two bundle files that do not exist.

Suggestions

Consolidate the aspect-ratio listings repeated in Step 1, Step 5, and the Quick Reference into references/formats.md and link to it once to remove duplication.

Add a verification checkpoint after batch generation (confirm the expected number of valid image files were produced) before building the HTML preview, since batch operations warrant validation.

Fix or remove the broken references to ./examples/opc-banner-creation.md and <skill_dir>/templates/preview.html, which have no corresponding files in the bundle.

Dimension	Reasoning	Score
Conciseness	Largely action-dense and free of concept explanations Claude already knows, but aspect ratios are repeated across Step 1, Step 5, and Quick Reference, and the prompt-pattern templates add padding that could be tightened.	2 / 3
Actionability	Provides concrete, executable bash commands with real flags (generate.py, batch_generate.py, crop_banner.py), and crop_banner.py is a real bundle file, making guidance copy-paste ready modulo justified path substitutions.	3 / 3
Workflow Clarity	A clear six-step sequence with a 'Wait for user confirmation before proceeding!' checkpoint and an iterate-until-final loop, but batch generation and cropping lack verification steps; the batch-operations guideline caps this at 2.	2 / 3
Progressive Disclosure	Sections are well-organized with one-level-deep, signaled references, but two of three referenced paths — ./examples/opc-banner-creation.md and <skill_dir>/templates/preview.html — do not exist in the bundle, breaking navigation.	2 / 3
	Total	9 / 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.

A strong, third-person description that names concrete actions, gives explicit trigger guidance, and carves out a distinct niche. No over-claims or fluff.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — 'Discuss format/style, generate variations, iterate with user feedback, crop to target ratio' — rather than vague language.	3 / 3
Completeness	Explicitly answers what it does and includes an explicit 'Use when user wants to create a banner, header, hero image...' trigger clause.	3 / 3
Trigger Term Quality	Covers natural terms users would say — 'banner, header, hero image, cover image, GitHub banner, Twitter header, readme banner' — with good variation.	3 / 3
Distinctiveness Conflict Risk	A clear banner-creation niche with distinct, specific triggers unlikely to fire for unrelated skills.	3 / 3
	Total	12 / 12 Passed

Validation

93%

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 — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
relative_links	Relative link issues: 1 missing	Warning

	Total	15 / 16 Passed

Repository: resciencelab/opc-skills
Commit: 282acb4

Reviewed: 1 day ago

Table of Contents

Discovery Implementation Validation

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.