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AI Image Generation

面向 AI 图像生成与编辑的技能文档,覆盖 GPT Image、Gemini/Imagen、FLUX、Midjourney、Leonardo、Ideogram、Replicate 与 Stable Diffusion,提供别名到官方模型 ID 映射、按任务选型、提示词技巧、先廉价草稿再精修、回退链与 API 调用模式,并把用户偏好保存在本地 ~/image-generation/。

ivangdavila
ivangdavila
热度 99.15
最近更新 2026-05-11 16:25:06
分类:创作依赖:代码执行 / 第三方 API / 读写文件应用场景:图像生成 / API 集成 / 工作流

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add image-generation
Metadata
name
AI Image Generation
slug
image-generation
version
1.0.3
homepage
https://clawic.com/skills/image-generation
description
Create AI images with GPT Image, Gemini Nano Banana, FLUX, Imagen, and top providers using prompt engineering, style control, and smart editing.
changelog
Updated for 2026 with benchmark-backed model selection and clearer guidance for modern image generation stacks.
metadata
{"clawdbot":{"emoji":"🎨","requires":{"bins":[],"env.optional":["OPENAI_API_KEY","GEMINI_API_KEY","BFL_API_KEY","GOOGLE_CLOUD_PROJECT","REPLICATE_API_TOKEN","LEONARDO_API_KEY","IDEOGRAM_API_KEY"],"config":["~/image-generation/"]},"os":["linux","darwin","win32"]}}

Setup

On first use, read setup.md.

When to Use

User needs AI-generated visuals, edits, or consistent image sets. Use this skill to pick the right model, write stronger prompts, and avoid outdated model choices.

Architecture

User preferences persist in ~/image-generation/. See memory-template.md for setup.

~/image-generation/
├── memory.md      # Preferred providers, project context, winning recipes
└── history.md     # Optional generation log

Quick Reference

Topic File
Initial setup setup.md
Memory template memory-template.md
Migration guide migration.md
Benchmark snapshots benchmarks-2026.md
Prompt techniques prompting.md
API handling api-patterns.md
GPT Image (OpenAI) gpt-image.md
Gemini and Imagen (Google) gemini.md
FLUX (Black Forest Labs) flux.md
Midjourney midjourney.md
Leonardo leonardo.md
Ideogram ideogram.md
Replicate replicate.md
Stable Diffusion stable-diffusion.md

Core Rules

1. Resolve aliases to official model IDs first

Community names shift quickly. Before calling an API, map the nickname to the provider model ID.

Community label Official model ID to try first Notes
Nano Banana gemini-2.5-flash-image-preview Common nickname, not an official Google model ID
Nano Banana 2 / Pro Verify provider docs Usually a provider preset over Gemini image models
GPT Image 1.5 gpt-image-1.5 Current OpenAI high-tier image model
GPT Image mini / iMini gpt-image-1-mini Budget/faster OpenAI variant
FLUX 2 Pro / Max flux-pro / flux-ultra Many platforms rename these SKUs

2. Pick models by task, not by hype

Task First choice Backup
Exact text in image gpt-image-1.5 Ideogram
Multi-turn edits gemini-2.5-flash-image-preview flux-kontext-pro
Photoreal hero shots imagen-4.0-ultra-generate-001 flux-ultra
Fast low-cost drafts gpt-image-1-mini imagen-4.0-fast-generate-001
Character/product consistency flux-kontext-max gpt-image-1.5 with references
Local no-API workflows flux-schnell SDXL

3. Use benchmark tables as dated snapshots

Benchmarks drift weekly. Use benchmarks-2026.md as a starting point, then recheck current rankings when quality is critical.

4. Draft cheap, finish expensive

Start with 1-4 low-cost drafts, pick one, then upscale or rerender only the winner.

5. Keep a fallback chain

If the preferred model is unavailable, fallback by tier:

  1. same provider lower tier, 2) cross-provider equivalent, 3) local/open model.

6. Treat DALL-E as legacy

OpenAI lists DALL-E 2/3 as legacy. Do not use them as default for new projects.

Common Traps

  • Using vendor nicknames as model IDs -> API errors and wasted retries
  • Assuming "Nano Banana Pro" or "FLUX 2" are universal IDs -> provider mismatch
  • Copying old DALL-E prompt habits -> weaker output vs modern GPT/Gemini image models
  • Comparing text-to-image and image-editing scores as if they were the same benchmark
  • Optimizing every draft at max quality -> cost spikes without quality gain

Security & Privacy

Data that leaves your machine:

  • Prompt text
  • Reference images when editing or style matching

Data that stays local:

  • Provider preferences in ~/image-generation/memory.md
  • Optional local history file

This skill does NOT:

  • Store API keys
  • Upload files outside chosen provider requests
  • Persist generated images unless user asks to save them

External Endpoints

Provider Endpoint Data Sent Purpose
OpenAI api.openai.com Prompt text, optional input images GPT Image generation/editing
Google Gemini API generativelanguage.googleapis.com Prompt text, optional input images Gemini image generation/editing
Google Vertex AI aiplatform.googleapis.com Prompt text, optional input images Imagen 4 generation
Black Forest Labs api.bfl.ai Prompt text, optional input images FLUX generation/editing
Replicate api.replicate.com Prompt text, optional input images Hosted third-party image models
Midjourney discord.com Prompt text Midjourney generation via Discord workflows
Leonardo cloud.leonardo.ai Prompt text, optional input images Leonardo generation/editing
Ideogram api.ideogram.ai Prompt text Typography-focused image generation

No other data is sent externally.

Migration

If upgrading from a previous version, read migration.md before updating local memory structure.

Trust

This skill may send prompts and reference images to third-party AI providers. Only install if you trust those providers with your content.

Related Skills

Install with clawhub install <slug> if user confirms:

  • image-edit - Specialized inpainting, outpainting, and mask workflows
  • video-generation - Convert image concepts into video pipelines
  • colors - Build palettes for visual consistency across assets
  • ffmpeg - Post-process image sequences and exports

Feedback

  • If useful: clawhub star image-generation
  • Stay updated: clawhub sync