---
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:

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

Run generation:

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

Run with explicit provider/model:

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

Save image locally:

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

Generate multiple images in one run:

```bash
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.


---
Source attribution: modbender
Original project: https://github.com/modbender/skill-library-mcp/blob/d9c8fe903b5b4e82237dbe8d0df8567783022e18/data/free-quota-image-skill/SKILL.md
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2025 skill-library-mcp contributors

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Mega AI Hub resource metadata

Creator / publisher: modbender
Original project: https://github.com/modbender/skill-library-mcp/blob/d9c8fe903b5b4e82237dbe8d0df8567783022e18/data/free-quota-image-skill/SKILL.md
Attribution basis: Source repository record

Fields of work: Content & Media, Design, Marketing
Roles: Content Marketer, Graphic Designer, Influencer Marketer, UX Designer, Video Producer
Specialties: API
Tools: Hugging Face, OpenAI API
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: 73ebc89d5b924cf9752b18c5d622f7566bd6d5e8c8aab4d30a58deb53564155d