Skills

Dream Loop

Build a game or app from a description so that a live screenshot matches a generated...

Install

npx skills add achimala/dream-loop --skill dream-loop -g -a claude-code -y
Repository
achimala/dream-loop1.8k
Category
Engineering
Updated
2mo ago
License
MIT
Context cost
Lightabout 662 tokens
Runs scripts
No, instructions only

What it does

Build a game or app from a description so that a live screenshot matches a generated rendering. Use when the user says "dream loop" or asks for something built to a very high level of graphical fidelity.

dream-loop

This is a process for you to autonomously build extremely impressive visuals, especially for 3D scenes (e.g. in a game or app).

Your first step is to determine which workflow to use:

  • If the user told you to use the Plus or Pro workflow explicitly, that's your answer
  • If not, check if the user is on a low or high tier coding subscription. "Low tier" means ChatGPT Plus or equivalent. "High tier" means ChatGPT Pro. For low-tier subscriptions, use the Plus workflow. For high-tier, use the Pro workflow.

Plus workflow: read references/plus-mode/workflow.md

Pro workflow: read references/pro-mode/workflow.md

Do not read both documents. They are not inter-compatible.

Guidance applicable to both workflows

General

Create and use a .dream-loop folder for working context/files, and gitignore it.

The target image

The key piece of Dream Loop is to first create the "dream version" of the user request using image generation, then iterate to build it.

If the user supplies this, use that directly. If not, you need to generate it.

If you don't have an image generation tool, stop and ask the user to either provide the target image, or connect you to an image generation API.

Before generating the image, determine if there is an existing product or if you're starting fresh. If fresh, you can directly generate a new image. If there's an existing product, you should capture a screenshot of the current version of it, then use that as the baseline input to the image model and generate a refined version of it based on the user direction, so that it is an improvement over the original and not a divergence.

Read the whole SKILL.md on GitHub

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