text-to-image
Skill0 starsChanged 7 months agoMITView on GitHub
Generates images from text descriptions using the Token Plan text-to-image model. Use this skill when asked to "draw a picture," "generate an image," or "create an image based on a description," such as "生成一张图片" or "根据描述创建图像" or "draw a cat wearing a hat" or "generate a night view of a futuristic city." Accepts plain text prompts and outputs images.
- Reads credentials
- Sends data out
2 other projects use a version of this.
Adopted by
Most recently taken up by
- 0gfoundation/0g-agent-skillstheir own version, first seen Sep 17, 2026
- meitu/meitu-skillstheir own version, first seen Jun 15, 2026
Other versions2 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 2
- meitu/meitu-skills★ 33same name
- 0gfoundation/0g-agent-skills★ 15same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository2 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- sense-infographicSkill
The file
We split this skill into the rules it gives an agent
5 rules. About 0 are common, 1 is distinctive, and 4 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
4
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 20
Step-0: Check that the environment variable $TOKEN_PLAN_API_KEY exists.
- Very specific: line 41
If code is not null, stop and tell the user the error with message.
- Very specific: line 42
If images has entries, download them one by one to the current directory.
- Distinctive: line 43
If the user has explicitly specified a save path, save there instead.
- Very specific: line 73
When the user provides an aspect ratio, convert it to the corresponding size.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Generate an image by calling the Token Plan text-to-image API based on the text description.
Execution Steps
Step-0: Check that the environment variable $TOKEN_PLAN_API_KEY exists. Keep it secret. If not set, stop and prompt the user to configure it.
Step-1: Extract parameters from user input:
prompt(required): The image description.model(optional, default:qwen-image-2.0-pro): See Available Models.size(optional, default:2688*1152): Image dimensions inWIDTH*HEIGHTformat. See Available Sizes.asratio(optional): Aspect ratio like16:9,9:16,1:1. If provided, convert tosizeusing the Aspect Ratio table. Takes precedence oversize.
Step-2: Execute the curl command to generate the image:
RESPONSE=$(curl -s -X POST "https://token-plan.cn-beijing.maas.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation" \
-H "Authorization: Bearer $TOKEN_PLAN_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"<model>","input":{"messages":[{"role":"user","content":[{"text":"<prompt>"}]}]},"parameters":{"size":"<size>"}}')
echo "$RESPONSE"|jq -r '{code, message, images: [.output.choices[]?.message.content[]?.image]}'Step-3: Extract the jq result — code is the error code, message is the error description, images is a list of image URLs from output.choices[*].message.content[*].image.
- If
codeis not null, stop and tell the user the error withmessage. - If
imageshas entries, download them one by one to the current directory. - If the user has explicitly specified a save path, save there instead.
Result Example
Successful response
{
"code": null,
"message": null,
"images": [
"https://dashscope-7c2c.oss-accelerate.aliyuncs.com/..."
]
}Failed response — invalid parameter
{
"code": "InvalidParameter",
"message": "Image area must be between 262144 (512x512) and 4194304 (2048x2048) pixels.",
"images": []
}Step-4: Return the file path(s) of the downloaded image(s).
Aspect Ratio
When the user provides an aspect ratio, convert it to the corresponding size. asratio takes precedence over size — if both are given, use the ratio.
| Aspect Ratio | Size | Best For |
2.35:1 | 2688*1152 | Ultrawide cinematic (default) |
1:1 | 1024*1024 | Square format |
1:1:high | 2048*2048 | High-resolution square |
16:9 | 2688*1536 | Landscape / widescreen |
9:16 | 1536*2688 | Mobile / vertical |
4:3 | 2368*1728 | Standard landscape |
3:4 | 1728*2368 | Standard portrait |
21:9 | 2368*1024 | Ultrawide banner |
Available Sizes
Can also be specified directly in WIDTH*HEIGHT format:
1024*1024, 720*1280, 1280*720, 2048*2048, 2688*1536, 1536*2688, 2368*1728, 1728*2368, 2368*1024, 2688*1152
Available Models
| Model | Description |
qwen-image-2.0 | General-purpose, versatile, proficient in Chinese text rendering |
qwen-image-2.0-pro | Higher quality (default) |
wan2.7-image | Multiple styles, defaults to 4 images |
wan2.7-image-pro | Supports 4K resolution |
Prompt Writing Tips
The qwen-image models handle detailed prompts well. For best results:
- Be specific about subjects: describe the main subject clearly — appearance, pose, expression, clothing.
- Describe the scene: background, lighting, weather, time of day, camera angle.
- Specify the art style: photorealistic, oil painting, watercolor, anime, pixel art, 3D render, etc.
- Mention color palette: e.g., "暖色调" (warm tones), "冷色调蓝紫色" (cool blue-purple tones).
- Include composition hints: close-up, wide shot, bird's-eye view, centered, rule of thirds.
- State the mood: dreamy, dramatic, serene, vibrant, moody.
A good image prompt is typically 50-200 words, rich in visual detail.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

