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design-image-studio

design-image-studio

github.com/kangarookingCreative & media10436 installsUpdated 27w ago
Repository

About design-image-studio

design-image-studio is a skill for turning design-system guidance into prompts and generated images. It serves visual-design tasks such as posters and product imagery, using a compilation workflow that preserves detailed design reasoning before shortening the image prompt.

Key features

  1. 01Compiles design-system guidance
  2. 02Supports six visual task types
  3. 03Builds reasoning and brief layers
  4. 04Generates images through a wrapper script
  5. 05Offers prompt-only output
  6. 06Refines results one variable at a time

Use cases

  1. 01Creating posters and key visuals
  2. 02Producing product ads and e-commerce images
  3. 03Making slide illustrations and covers
  4. 04Exploring infographic or teaching visuals

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/kangarooking/design-image-studio --skill design-image-studio

After installing, type/design-image-studioin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

README.md
.gitignore
LICENSE
requirements.txt
references/
infographic.md
claude-design-map.md
anti-slop-and-failure-patterns.md
design-compiler.md
ppt-visual.md
poster.md
models.md
product-image.md
teaching-demo.md
model-routing.md
claude-design-sys-prompt-full.txt
prompt-framework.md
design-principles.md
troubleshooting.md
scripts/
generate.py
design_image.py

Details

From the project README

Design Image Studio

Generate design-quality images directly. This skill preserves the full Claude design-system prompt as the upstream design brain, then compiles that design logic into a shorter image-model prompt.

Primary Source of Truth

Do not treat references/design-principles.md as the whole design system. It is only an index.

The primary design source is:

  • references/claude-design-sys-prompt-full.txt

Always read that file first for substantive design work. Then use:

  • references/claude-design-map.md
  • references/design-compiler.md
  • the task-specific reference file for the current request

This skill should preserve as much of the original design-system prompt as possible at the reasoning layer, while stripping away HTML/tool-specific noise before handing a prompt to the image model.

When to Use

Use this skill when the user wants any of the following:

  • Poster generation
  • Product hero images, ad visuals, or e-commerce scenes
  • PPT cover art, chapter art, or slide illustrations
  • Infographic-style visuals
  • Teaching/demo diagrams or explanatory scenes
  • Visual concept exploration with stronger art direction than a generic image prompt

Do not use this skill for pixel-accurate UI recreation, editable charts, or layouts that require precise text rendering. For those, generate HTML/SVG/PPT assets instead.

Default Workflow

  1. Classify the request into one of: poster, product, ppt, infographic, teaching, or auto
  2. Read the full design system prompt:
    • references/claude-design-sys-prompt-full.txt
  3. Read the compiler references:
    • references/claude-design-map.md
    • references/design-compiler.md
    • references/model-routing.md
  4. Read the matching task file, such as references/poster.md
  5. If the user wants refinement or the first result is weak, also read:
    • references/anti-slop-and-failure-patterns.md
  6. Compile the full design system into a design_reasoning layer:
    • purpose
    • audience
    • channel
    • context/brand strategy
    • visual system
    • hierarchy strategy
    • safe-zone or text-zone logic
    • anti-filler rules
    • anti-slop rules
    • task-specific design constraints
  7. Condense the reasoning into a compiled_brief
  8. Translate the compiled brief into the shortest useful image prompt
  9. Run scripts/design_image.py to generate directly, unless the user explicitly asks for prompt-only output
  10. Iterate by changing one major variable at a time: direction, hierarchy, palette, lighting, realism, or density

What Must Be Preserved From the Full Prompt

These must survive the compilation process:

  • Start from purpose, audience, and channel
  • Create a coherent visual system up front
  • Treat hierarchy and whitespace as design decisions
  • Avoid filler content and decorative noise
  • Avoid AI-slop tropes
  • Respect brand/context when available
  • If no context exists, still commit to a strong direction instead of averaging styles
  • Prefer multiple directions for ambiguous work, usually conservative, balanced, and bold

Primary Command

Use the wrapper script first. It is the opinionated entry point for this skill.

python3 scripts/design_image.py \
  --task poster \
  --brief "为 AI 训练营生成一张高冲击力招生海报,强调增长、实战和速度" \
  --direction balanced \
  --aspect 3:4 \
  --quality final \
  --output training-poster.png

Prompt-Only Mode

If the user only wants prompts, do:

python3 scripts/design_image.py \
  --task product \
  --brief "高端陶瓷咖啡杯广告图,适合电商首图" \
  --prompt-only

The wrapper prints:

  • design_reasoning
  • compiled_brief
  • final prompt

Use those intermediate layers to judge whether the full design-system prompt has actually been preserved.

Task References

  • references/poster.md — posters, key visuals, covers
  • references/product-image.md — product ads, hero shots, e-commerce visuals
  • references/ppt-visual.md — slide cover art, chapter visuals, concept illustrations
  • references/infographic.md — infographic-like visuals and structured information compositions
  • references/teaching-demo.md — educational and explanatory diagrams/scenes
  • references/claude-design-map.md — which sections of the full design prompt matter for image generation
  • references/design-compiler.md — how to compile the full prompt into design reasoning, a compiled brief, and a final image prompt

Execution Notes

  • Prefer Seedream 5.0 lite as the default final model
  • Use lower-cost draft settings before premium reruns when the direction is still unclear
  • Use image-to-image or multi-image fusion when the user provides source materials
  • For infographic or teaching visuals, avoid asking the model to render dense, tiny text accurately; prefer text placeholders or low-text compositions
  • The wrapper script is not the design brain; it is the compiler between the full design system and the image model
  • Do not collapse the full design prompt into a few style adjectives unless the user explicitly wants a minimal prompt

Files

  • scripts/design_image.py — design compiler and prompt builder
  • scripts/generate.py — bundled Volcengine generation engine
  • references/claude-design-sys-prompt-full.txt — full upstream design-system prompt
  • references/claude-design-map.md — section map for image use
  • references/design-compiler.md — compilation workflow
  • references/models.md — model and resolution reference
  • references/troubleshooting.md — common error handling

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