image-generation

name	image-generation
description	Use when the user wants to generate or edit images through the local `image_creator` MCP server — especially when the agent should pick the right image profile or model, use reference images, iterate drafts into final assets, or produce style-transfer / character-consistent edits saved to disk.

Image Generation

Use this skill when image quality depends on choosing the right profile, composing a clean prompt, and using the local image_creator MCP server effectively.

This skill is not a rule pile. It is a compact knowledge layer for:

• choosing the right image profile,
• prompting efficiently,
• using reference images correctly,
• converging to a strong result through generate -> edit loops,
• knowing when the right move is deterministic cutout instead of another edit prompt.

Start here

Unless the user already specified an exact model or you already know the right profile from the current turn:

1. call list_image_profiles
2. choose the smallest profile that fits the task
3. use generate_image for first composition
4. once composition is correct, prefer edit_image for narrow changes
5. if the image is already correct and only the background must go away, prefer remove_background

Default bias:

• first pass -> draft
• final-fidelity pass -> quality
• typography / text inside image -> text_heavy
• local corrections -> edit
• style transfer -> style_transfer
• recurring character identity -> character_consistency
• balanced transparent background / cutout -> transparent_bg
• cheaper/faster transparent draft -> transparent_bg_fast
• higher-fidelity isolated asset -> cutout

Open only what you need

Always useful:

• references/tool-surface.md

Read when needed:

• references/profile-selection.md when choosing between profiles
• references/prompting-patterns.md when the prompt quality is the bottleneck
• references/reference-images.md when using refs or doing edits / style transfer / identity preservation

Workflow

1. Choose the profile before reaching for a raw model id

Prefer the curated profile surface first. Use explicit model override only when:

• the user asked for a specific model,
• the profile is close but not exact,
• you are doing a bounded comparison or recovery move.

2. Generate first, then narrow by editing

Strong default loop:

1. generate_image -> get the composition / framing / rough style right
2. inspect result
3. edit_image -> make one narrow change at a time

Do not keep re-generating from scratch once the composition is already good.

3. Keep prompts structured, not magical

Good prompt shape is usually:

• subject
• style / medium
• composition / framing
• lighting / mood
• important details
• explicit constraints

See references/prompting-patterns.md.

4. Treat references as typed guidance

Do not send a pile of images without roles. Use reference_images=[{path, role}] with roles like:

• style
• subject
• object
• character
• layout

For edits, input_path is the only editable base image; refs are guidance only.

5. Use GPT-image for true transparent backgrounds

In the current repo truth, transparent background generation is not a Gemini-family job. If the user wants:

• transparent background
• alpha channel
• clean cutout / isolated asset

prefer one of these:

• transparent_bg for balanced quality
• transparent_bg_fast for cheap drafts
• cutout for higher-fidelity final isolated assets

6. Use remove_background for existing assets

If the subject is already correct and the real task is:

• remove background
• cut out object
• extract alpha

do not push that through edit_image.

Use remove_background.

Common traps

• jumping straight to raw model ids when a profile already fits
• giant prompt with 20 demands instead of a draft -> edit loop
• re-generating from scratch when only one detail is wrong
• sending reference images without roles
• using quality too early, before composition is proven
• using draft for text-heavy final assets
• trying to get a real transparent background from Gemini-family image routes
• trying to do deterministic cutout through edit_image when remove_background is the real primitive
• forgetting that the deliverable is the saved file path, not just the model response