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Looped visual tuning with a vision model v1.0.0

Use this resource to tune a render that only a human eye can judge

New

  • 487 downloads
  • 170 likes
  • 130 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install visual-tuning-vision-loop

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

A vision model rates several rendered variants, suggests better values and picks the best one, in a loop. It suits easing, colour, layout or render settings when no numeric metric exists.

Mostly picked by

Updated November 2, 2026

Card for the “Looped visual tuning with a vision model” skill

Details

Works in
Install guides
Generates with
Your agent's model
Licence
MIT

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What you get

  • SKILL.md: visual evaluation loop steps and stop criteria
  • SKILL.md: when not to use it, known limits and an example

Good fit for

  • You look for the right easing or timing of an animation
  • You adjust a tint or spacing by comparing renders

Not for

    Tags

    • visual tuning
    • animation
    • loop
    • vision model
    • render

    About

    You say

    “Run the render loop on four easing variants of my intro and keep the best one.”

    Card for the “Looped visual tuning with a vision model” skill

    Skill published by Conner K Ward 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 tune a render that only a human eye can judge
    3. Review and adjust the result

    Content preview

    Files

    • LICENSE1.1 KB
    • NOTICE-PALATEKIT.md0.5 KB
    • SKILL.md6.3 KB

    Origin and licence

    Listed unmodified

    Author
    Conner K Ward
    Source
    github.com/sickn33/agentic-awesome-skills/tree/e9809578fd426a284af017c5db99f8eb6628e6ca/skills/lookdev-auto
    Licence
    MIT

    Notice

    « lookdev-auto » (Conner K Ward, MIT) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.

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