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OpenClaw

free-quota-image-skill

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.

chiayengu0 source installs☆ 0 Repository stars

Installation

Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.

SkillHub CLI

skillhub install chiayengu/free-quota-image-skill

Inspect the source and compatibility requirements, then follow its installation steps.

Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.

View source ↗Guides

Skill instructions

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)...

Source information

Source
github
Repository
openclaw/skills
Path
skills/chiayengu/free-quota-image-skill
Version
—
Commit
3e2ec2e984dce5b785c6a9b14af571c8a317627b
Classification source
rules
Status
active
Visibility
public

These signals come from indexed source analysis and may lag behind changes. Check the current source files.

Extracted content

SKILL.md
# 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)...

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