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image

When the user wants to create, generate, edit, or optimize marketing images, or asks which approach to take (generate, design, or photograph): blog heroes, social graphics, product mockups, banners, OG images. For ad images, see ad-creative. For video, see video.

Quality

88%

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Passed

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SKILL.md
Quality
Evals
Security

Quality

Content

71%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.

A well-structured, highly actionable skill with excellent progressive disclosure and a single well-used reference file. Its weaknesses are token efficiency — Claude-known explanations and rot-prone inline version/date details — and the absence of an executable API-call example for the core generation workflow.

Suggestions

Move model version numbers, deprecation dates, and pricing links into a dedicated reference file or a clearly-marked 'Deprecated / model versions' section, keeping only the decision-relevant summary inline.

Add one copy-paste-ready generation example (e.g., a curl or Python call to the Gemini or Replicate API with a sample prompt) so the core AI-generation workflow is executable end-to-end.

Trim explanations of concepts Claude already knows (what OG images are, PNG/SVG use cases, CLS basics) and add explicit verification steps to the workflows (e.g., check output file size after compression, confirm text legibility after generation).

DimensionReasoningScore

Conciseness

Mostly table-driven and dense, but includes explanations Claude already knows ("The image that appears when your URL is shared on social media", the PNG-for-transparency/SVG-scales format guide, "width and height attributes prevent layout shift (CLS)") and pervasive inline time-sensitive version/date detail (FLUX.2 [pro]/[flex]/[klein], "gpt-image-1 retires on 23 Oct 2026", Midjourney v7) that is not confined to a deprecation section — only the DALL-E note is. This is more than minor over-explanation, so it fits the "could be tightened" anchor rather than the efficient one.

3 / 5

Actionability

Strong executable guidance: copy-paste commands (cwebp, mogrify, jpegoptim), ready-to-use OG meta-tag HTML, concrete prompt patterns, and exact per-platform dimension tables. Falls short of fully executable because the core action — generating an image via API — never shows an actual API call example (only links), and mockup annotation stays vague ("Hyperframes or HTML/CSS").

4 / 5

Workflow Clarity

Each asset type has a clear numbered sequence (blog hero, social graphics, mockups, banners) plus a model-selection decision tree, with some checkpoints ("Test at actual display size", "compress to <200KB"). Validation is sparse — no verify step after generation or optimization (e.g., confirm output file size or text legibility) and no error-recovery feedback loops — so it does not reach the explicit-validation anchor.

4 / 5

Progressive Disclosure

The body is a well-sectioned overview that keeps exactly one clearly-signaled, one-level-deep reference — "For detailed prompting guides per model, see references/ai-image-prompting.md" — which exists in the bundle, and the prompting detail is appropriately split out of the main file. Navigation is easy and content is appropriately placed, matching the clear-overview anchor.

5 / 5

Total

16

/

20

Passed

Description

100%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 is exemplary: concrete verbs, comprehensive asset-type enumeration, an explicit "When the user wants to…" trigger clause, and explicit redirects to adjacent skills (ad-creative, video) that eliminate conflict risk. It uses third-person, trigger-oriented phrasing without padding.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — "create, generate, edit, or optimize" — and comprehensively enumerates the asset types it covers ("blog heroes, social graphics, product mockups, banners, OG images"), plus approach-selection guidance ("asks which approach to take (generate, design, or photograph)"). Coverage of the marketing-image domain is essentially complete, matching the comprehensive anchor rather than the minor-gaps anchor.

5 / 5

Completeness

Explicitly answers both questions: the "what" is "create, generate, edit, or optimize marketing images" and the "when" is the explicit trigger clause "When the user wants to… or asks which approach to take". This mirrors the anchor-5 pattern of concrete what-and-when with trigger phrases, not merely an implicit or generic "when".

5 / 5

Trigger Term Quality

Natural user vocabulary is thoroughly covered ("create", "generate", "blog heroes", "social graphics", "OG images") with synonyms present (create/generate, design/photograph). Users requesting marketing visuals would naturally use these exact phrases, fitting the comprehensive-synonyms anchor.

5 / 5

Distinctiveness Conflict Risk

A clear marketing-images niche with explicit boundary carve-outs to the nearest competing skills ("For ad images, see ad-creative. For video, see video."). The specific trigger vocabulary minimizes overlap risk, matching the clear-niche anchor.

5 / 5

Total

20

/

20

Passed

Validation

100%

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

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

coreyhaines31/marketingskills

Path

skills/image/SKILL.md

Reviewed

Table of Contents

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