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Web image optimization v1.0.0

Use this resource to reduce web image weight with modern formats and lazy loading

New

  • 393 downloads
  • 159 likes
  • 214 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install web-image-optimization

With no option, the skill goes to ~/.agents/skills/; add --agent claude-code (or codex, cursor…) to target an agent.

First time: connect the CLI with

npx --yes palatekit@latest login

The agent picks the right format for each image, prepares responsive sizes with picture and srcset, and sets up lazy loading. You get lighter pages and performance targets to verify.

Mostly picked by

Updated November 2, 2026

Card for the “Web image optimization” skill

Details

Generates with
Your agent's model
Licence
MIT

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What you get

  • SKILL.md : format selection and picture and srcset markup
  • SKILL.md : lazy loading and a Sharp build pipeline

Good fit for

  • Images slow down your pages' loading
  • You are preparing a site's visuals before launch

Not for

    Tags

    • images
    • performance
    • webp
    • avif

    About

    You say

    “Optimize my product page photos as AVIF and WebP, with responsive sizes.”

    Card for the “Web image optimization” skill

    Skill published by secondsky under the MIT license, delivered in its original version.

    Show more

    How to use it

    1. Install the skill in your agent's skills folder
    2. Ask your agent to reduce web image weight with modern formats and lazy loading
    3. Review and adjust the result

    Content preview

    Files

    • LICENSE1.1 KB
    • NOTICE-PALATEKIT.md0.5 KB
    • SKILL.md2 KB

    Origin and licence

    Listed unmodified

    Author
    secondsky
    Source
    github.com/secondsky/claude-skills/tree/88378361314f558fb719aec0af9fd898ab36f0b2/plugins/image-optimization/skills/image-optimization
    Licence
    MIT

    Notice

    « image-optimization » (secondsky, MIT) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.

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