---

name: free-quota-image-skill description: Generate images from text with a free-quota-first multi-provider workflow. Use this skill when a user asks for text-to-image generation that needs provider routing (Hugging Face, Gitee, ModelScope, A4F, OpenAI-compatible private endpoints), token pooling with automatic rotation on quota/auth failures, public API fallback for Hugging Face, prompt optimization, model fallback, batch generation in one command, and structured generation outputs. metadata: {"openclaw":{"homepage":"https://github.com/Amery2010/peinture"}}

Free Quota Image Skill

Overview

Use this skill to run a provider-agnostic text-to-image pipeline with free-quota-first routing, token rotation, and prompt enhancement.

Workflow

1. Load config from {baseDir}/assets/config.example.yaml or user-provided config.
2. Resolve provider order (--provider auto follows routing.provider_order).
3. Resolve model candidates per provider (requested -> z-image-turbo -> provider default).
4. Prepare prompt for each attempt:
   • optionally auto-translate for target models
   • optionally optimize prompt with provider text model
5. Execute generation request.
6. On quota/auth failures, rotate token; if exhausted, move to next provider.
7. Repeat the generation flow when --count > 1, and rotate provider/token start position per image to spread load.
8. Return stable JSON output fields or direct URL output.

Commands

Install dependencies:

python -m pip install -r {baseDir}/scripts/requirements.txt

Run generation:

python {baseDir}/scripts/run_text2img.py --prompt "cinematic rainy tokyo alley" --json

Run with explicit provider/model:

python {baseDir}/scripts/run_text2img.py --prompt "a fox astronaut" --provider gitee --model flux-2 --json

Save image locally:

python {baseDir}/scripts/run_text2img.py --prompt "retro sci-fi city" --output ./out.png

Generate multiple images in one run:

python {baseDir}/scripts/run_text2img.py --prompt "anime passport portrait" --count 4 --json

CLI contract

Use {baseDir}/scripts/run_text2img.py with the fixed contract:

• --prompt (required)
• --provider (auto|huggingface|gitee|modelscope|a4f|openai_compatible, default auto)
• --model (default z-image-turbo)
• --aspect-ratio (default 1:1)
• --seed (optional int)
• --steps (optional int)
• --guidance-scale (optional float)
• --enable-hd (flag)
• --optimize-prompt / --no-optimize-prompt (default on)
• --auto-translate / --no-auto-translate (default off)
• --config (default {baseDir}/assets/config.example.yaml)
• --output (optional output file path)
• --count (number of images in one run, default 1)
• --json (structured output)

Output contract

When --json is used, output these fields on success:

• id
• url
• provider
• model
• prompt_original
• prompt_final
• seed
• steps
• guidance_scale
• aspect_ratio
• fallback_chain
• elapsed_ms

On failure, output structured error fields:

• error_type
• error
• fallback_chain

When --count > 1, JSON output contains:

• count
• images (array of standard success payloads)
• elapsed_ms

References

Read only what is needed:

• Provider API wiring: references/provider-endpoints.md
• Model coverage and fallback: references/model-matrix.md
• Token rotation and date rules: references/token-rotation-policy.md
• Prompt optimization pipeline: references/prompt-optimization-policy.md
• OpenClaw setup details: references/openclaw-integration.md

Scope boundaries

Keep this skill focused on text-to-image core only.

Do not add image editing, video generation, or cloud storage workflows in this skill.