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onlyloveher

Image Generation

by onlyloveher · GitHub ↗ · v1.0.0 · MIT-0
linuxdarwinwin32 ✓ Security Clean
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Install in OpenClaw
/install image-generation-zhouli
Description
Create AI images with GPT Image, Gemini Nano Banana, FLUX, Imagen, and top providers using prompt engineering, style control, and smart editing.
README (SKILL.md)

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 Use this skill to pick the right model, write stronger prompts, and avoid outdated model choices.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 \x3Cslug> 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
Usage Guidance
This skill appears internally consistent for image-generation tasks. Before installing: - Know that prompts and any reference images you provide will be sent to the chosen third‑party provider(s). Do not submit confidential or sensitive images/text to those providers unless you trust them. - The skill will create ~/image-generation/ and may save memory.md and optional history.md — review those files and avoid logging sensitive prompt content if privacy is a concern. - Provider API keys are optional and reasonable for the stated purpose; grant keys only to trusted providers and do not paste secrets into chat. If you need stronger privacy, prefer local models (Stable Diffusion/SDXL) as documented. - Note minor metadata inconsistencies (version/owner ids) in the package manifest; they look like bookkeeping issues but you may want to confirm the publisher if provenance matters. Overall, the skill is coherent and behaves as advertised; exercise normal caution around provider data sharing and local logs.
Capability Analysis
Type: OpenClaw Skill Name: image-generation-zhouli Version: 1.0.0 The skill bundle is a comprehensive and well-structured toolkit for AI image generation across multiple providers (OpenAI, Google, BFL, etc.). It includes detailed API patterns, model selection logic, and prompt engineering guides in files like `gpt-image.md`, `flux.md`, and `api-patterns.md`. Security is explicitly addressed in `SKILL.md` and `setup.md`, which provide safe methods for verifying environment variables without exposing secrets and define clear boundaries for data privacy. No evidence of malicious intent, data exfiltration, or harmful prompt injection was found.
Capability Assessment
Purpose & Capability
Name/description (AI image generation, multi-provider routing, prompt engineering) match the actual artifacts: multiple provider guides, prompting patterns, and local memory usage. The optional environment variables and config path correspond to expected provider API keys and a local workspace. Minor metadata inconsistencies exist (SKILL.md/_meta.json/registry show different versions and slightly different owner IDs), which look like bookkeeping issues rather than functional deviations.
Instruction Scope
Runtime instructions (SKILL.md and companion docs) limit actions to: resolving model aliases, choosing providers, calling provider APIs, and storing user preferences/history under ~/image-generation/. Setup checks only test for the presence of provider env vars and explicitly warns what data is sent externally. There are no instructions to read unrelated system files, exfiltrate secrets, or contact unexpected endpoints. The guidance explicitly states prompts and reference images will be sent to chosen providers (which is expected).
Install Mechanism
This is an instruction-only skill with no install spec and no code files to execute. That minimizes on-disk execution risk. The documented API endpoints are standard provider endpoints (OpenAI, Google, Replicate, BFL, Leonardo, Ideogram, Discord for Midjourney). No downloads, executables, or obscure URLs are referenced.
Credentials
No required env vars are declared; several provider API keys are listed as optional (OPENAI_API_KEY, GEMINI_API_KEY, BFL_API_KEY, GOOGLE_CLOUD_PROJECT, REPLICATE_API_TOKEN, LEONARDO_API_KEY, IDEOGRAM_API_KEY), which is proportional to a multi-provider image skill. The skill does require a local config path (~/image-generation/) to persist preferences/history — this is reasonable, but users should be aware that prompt text and reference images may be recorded in those files unless they opt out of logging.
Persistence & Privilege
always: false and no install hooks are present. The skill stores only its own workspace under ~/image-generation/ (memory.md, optional history.md) and does not request system-wide config changes or other skills' credentials. It does not store API keys per its documentation. Autonomous invocation is allowed by default (normal for skills) but not combined with any other high-risk factors here.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install image-generation-zhouli
  3. After installation, invoke the skill by name or use /image-generation-zhouli
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Initial release of the AI Image Generation skill, providing modern AI image creation and editing across multiple providers. - Includes updated 2026 benchmark-guided model selection, with clear guidance on best practices and common pitfalls. - Supports prompt engineering, style control, and automated model alias resolution for consistent results. - Documents privacy practices and all external endpoints used. - Adds migration guidance, troubleshooting, and links to related skills for advanced workflows.
Metadata
Slug image-generation-zhouli
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Image Generation?

Create AI images with GPT Image, Gemini Nano Banana, FLUX, Imagen, and top providers using prompt engineering, style control, and smart editing. It is an AI Agent Skill for Claude Code / OpenClaw, with 102 downloads so far.

How do I install Image Generation?

Run "/install image-generation-zhouli" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Image Generation free?

Yes, Image Generation is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Image Generation support?

Image Generation is cross-platform and runs anywhere OpenClaw / Claude Code is available (linux, darwin, win32).

Who created Image Generation?

It is built and maintained by onlyloveher (@onlyloveher); the current version is v1.0.0.

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