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image-optimization

Expert guidance on image optimization for web performance. Use when auditing or improving image delivery, Core Web Vitals (LCP/CLS/INP), responsive images (srcset/sizes), lazy loading, preloading, image CDN pipelines (Sirv, Cloudinary, imgix, Vercel, Cloudflare), format choice (AVIF, WebP, JPEG XL, SVG, HDR), compression and quality settings, placeholders, image alt text, or image-heavy frontend code. For Sirv URL parameters, Sirv REST API calls, Sirv Media Viewer galleries, or video, the sibling skills own the details.

80

Quality

100%

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

100%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 a model skill overview: lean and information-dense, with executable audit commands, concrete decision matrices and quality numbers, an explicitly sequenced and verifiable workflow, and clean one-level-deep disclosure into a well-organized references bundle. No dimension shows more than nitpick-level room for improvement.

DimensionReasoningScore

Conciseness

The ~96-line body is pure operational density — checklists, decision matrices, and quality-number tables — with zero tutorial prose explaining concepts Claude already knows. The single version-sensitive line ('In Next.js 16+, `priority` is deprecated') is framed as deprecation guidance with its replacement, matching the guideline's intended pattern, so nothing reads as padding or over-explanation.

5 / 5

Actionability

Guidance is fully executable: copy-paste commands ('node <skill-base-dir>/scripts/audit-images.mjs --head https://example.com/' — the placeholder is explicitly justified with resolution instructions), concrete quality ranges (JPEG 75-85, AVIF 60-75), and specific failure patterns ('Writing sizes="100vw" for images that render in a 33-50vw grid'). Common cases across LCP, formats, compression, and loading are all covered with specifics.

5 / 5

Workflow Clarity

The Default Workflow is a clear 5-step sequence with an explicit verification step ('Verify with evidence: rendered markup, response headers/content type, decoded/displayed size, Lighthouse/WebPageTest/DevTools') and a before-and-after audit feedback loop, plus a dedicated Fast Audit Checklist — all three anchor-5 elements. Since validation is present, the destructive/batch cap of 3 does not apply.

5 / 5

Progressive Disclosure

'When To Read References' provides six one-line, well-signaled pointers (sirv-workflows.md, formats.md, optimization.md, responsive.md, performance.md, tools.md), all verified to exist in the bundle's references/ directory, alongside the bundled audit script in scripts/. The body stays a true overview with details appropriately split one level deep; sibling skills are clearly labeled by scope, so navigation is easy.

5 / 5

Total

20

/

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.

An exemplary description: it states what the skill does, gives an explicit and comprehensive 'Use when' trigger list spanning metrics, techniques, formats, and products, and closes with a clear delegation boundary to sibling skills. No vagueness, padding, or voice violations are present.

DimensionReasoningScore

Specificity

The description enumerates concrete capability areas covering the whole domain — 'auditing or improving image delivery', 'responsive images (srcset/sizes)', 'lazy loading, preloading', 'format choice (AVIF, WebP, JPEG XL, SVG, HDR)', 'compression and quality settings, placeholders, image alt text' — with no vague filler and no coverage gaps, matching the comprehensive-coverage anchor rather than the minor-gaps anchor at 4.

5 / 5

Completeness

Both halves are explicit: 'Expert guidance on image optimization for web performance' answers what, and 'Use when auditing or improving image delivery, ... or image-heavy frontend code' answers when with concrete trigger phrases — the exact pattern of the anchor-5 example. The explicit 'Use when...' clause also avoids the completeness cap of 3.

5 / 5

Trigger Term Quality

Natural user phrasing is comprehensively covered with synonyms and named products: 'Core Web Vitals (LCP/CLS/INP)', 'lazy loading', 'image CDN pipelines (Sirv, Cloudinary, imgix, Vercel, Cloudflare)', 'AVIF, WebP', 'image alt text', 'image-heavy frontend code'. This exceeds the good-coverage anchor at 4, whose example is only a handful of terms.

5 / 5

Distinctiveness Conflict Risk

A clear niche (web image optimization) with distinct triggers, and the closing boundary sentence — 'For Sirv URL parameters, Sirv REST API calls, Sirv Media Viewer galleries, or video, the sibling skills own the details' — explicitly routes overlapping requests away, minimizing conflict with adjacent skills.

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

IgorVaryvoda/image-optimization-skill

Path

skills/image-optimization/SKILL.md

Reviewed

Table of Contents

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