Glm Image Gen
zai-org/GLM-skills
Official skill for generating high-quality images from text prompts using ZhiPu GLM-Image API.
Implement AI image generation capabilities using the z-ai-web-dev-sdk.
$ npx skills add jjyaoao/HelloAgents --skill image-generation -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install jjyaoao/HelloAgents image-generation --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/jjyaoao/HelloAgents.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/image-generation .claude/skills/image-generation && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "image-generation" agent skill from https://github.com/jjyaoao/HelloAgents/tree/main/skills/image-generation into .claude/skills/image-generation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "image-generation", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/jjyaoao/HelloAgents/tree/main/skills/image-generationType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add jjyaoao/HelloAgents --skill image-generation -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install jjyaoao/HelloAgents image-generation --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jjyaoao/HelloAgents.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/image-generation .agents/skills/image-generation && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "image-generation" agent skill from https://github.com/jjyaoao/HelloAgents/tree/main/skills/image-generation into .agents/skills/image-generation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "image-generation", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add jjyaoao/HelloAgents --skill image-generation -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install jjyaoao/HelloAgents image-generation --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jjyaoao/HelloAgents.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/image-generation .cursor/skills/image-generation && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "image-generation" agent skill from https://github.com/jjyaoao/HelloAgents/tree/main/skills/image-generation into .cursor/skills/image-generation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "image-generation", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/jjyaoao/HelloAgents.git --path skills/image-generation--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add jjyaoao/HelloAgents --skill image-generation -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install jjyaoao/HelloAgents image-generation --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jjyaoao/HelloAgents.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/image-generation .gemini/skills/image-generation && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "image-generation" agent skill from https://github.com/jjyaoao/HelloAgents/tree/main/skills/image-generation into .gemini/skills/image-generation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "image-generation", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install jjyaoao/HelloAgents image-generationInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add jjyaoao/HelloAgents --skill image-generation -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/jjyaoao/HelloAgents.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/image-generation .github/skills/image-generation && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "image-generation" agent skill from https://github.com/jjyaoao/HelloAgents/tree/main/skills/image-generation into .github/skills/image-generation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "image-generation", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add jjyaoao/HelloAgents --skill image-generation -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install jjyaoao/HelloAgents image-generation --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jjyaoao/HelloAgents.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/image-generation .opencode/skills/image-generation && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "image-generation" agent skill from https://github.com/jjyaoao/HelloAgents/tree/main/skills/image-generation into .opencode/skills/image-generation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "image-generation", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
image-generationImplement AI image generation capabilities using the z-ai-web-dev-sdk.
Image Generation is an agent skill from jjyaoao/HelloAgents. Implement AI image generation capabilities using the z-ai-web-dev-sdk. Use this skill when the user needs to create images from text descriptions, generate visual content, create artwork, design assets, or build applications with AI-powered image creation. Supports multiple image sizes and returns base64 encoded images. Also includes CLI tool for quick image generation.
Its SKILL.md is about 3.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including scripts (for example `scripts/image-generation.ts`).
It sits in Media & Creative, covering Image generation. It works with Zhipu GLM. The repository describes itself as: A agent framework based on the tutorial hello-agents. The licence is MIT.
3 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit c597a7c. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Ships 1 file in scripts/ (TypeScript), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Image Generation loads about 3.8k tokens when it runs. Until then it costs about 97 tokens; SKILL.md has 499 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
The full file from jjyaoao/HelloAgents at commit c597a7c, republished under its MIT licence (© jjyaoao). 499 words, ~3,780 tokens.
.claude/skills/image-generation/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.This skill guides the implementation of image generation functionality using the z-ai-web-dev-sdk package and CLI tool, enabling creation of high-quality images from text descriptions.
Skill Location: {project_path}/skills/image-generation
this skill is located at above path in your project.
Reference Scripts: Example test scripts are available in the {Skill Location}/scripts/ directory for quick testing and reference. See {Skill Location}/scripts/image-generation.ts for a working example.
Image Generation allows you to build applications that create visual content from text prompts using AI models, enabling creative workflows, design automation, and visual content production.
IMPORTANT: z-ai-web-dev-sdk MUST be used in backend code only. Never use it in client-side code.
The z-ai-web-dev-sdk package is already installed. Import it as shown in the examples below.
import ZAI from 'z-ai-web-dev-sdk';
import fs from 'fs';
async function generateImage(prompt, outputPath) {
const zai = await ZAI.create();
const response = await zai.images.generations.create({
prompt: prompt,
size: '1024x1024'
});
const imageBase64 = response.data[0].base64;
// Save image
const buffer = Buffer.from(imageBase64, 'base64');
fs.writeFileSync(outputPath, buffer);
console.log(`Image saved to ${outputPath}`);
return outputPath;
}
// Usage
await generateImage(
'A cute cat playing in the garden',
'./cat_image.png'
);import ZAI from 'z-ai-web-dev-sdk';
import fs from 'fs';
// Supported sizes
const SUPPORTED_SIZES = [
'1024x1024', // Square
'768x1344', // Portrait
'864x1152', // Portrait
'1344x768', // Landscape
'1152x864', // Landscape
'1440x720', // Wide landscape
'720x1440' // Tall portrait
];
async function generateImageWithSize(prompt, size, outputPath) {
if (!SUPPORTED_SIZES.includes(size)) {
throw new Error(`Unsupported size: ${size}. Use one of: ${SUPPORTED_SIZES.join(', ')}`);
}
const zai = await ZAI.create();
const response = await zai.images.generations.create({
prompt: prompt,
size: size
});
const imageBase64 = response.data[0].base64;
const buffer = Buffer.from(imageBase64, 'base64');
fs.writeFileSync(outputPath, buffer);
return {
path: outputPath,
size: size,
fileSize: buffer.length
};
}
// Usage - Different sizes
await generateImageWithSize(
'A beautiful landscape',
'1344x768',
'./landscape.png'
);
await generateImageWithSize(
'A portrait of a person',
'768x1344',
'./portrait.png'
);The z-ai CLI tool provides a convenient way to generate images directly from the command line.
# Generate image with full options
z-ai image --prompt "A beautiful landscape" --output "./image.png"
# Short form
z-ai image -p "A cute cat" -o "./cat.png"
# Specify size
z-ai image -p "A sunset" -o "./sunset.png" -s 1344x768
# Portrait orientation
z-ai image -p "A portrait" -o "./portrait.png" -s 768x1344# Website hero image
z-ai image -p "Modern tech office with diverse team collaborating" -o "./hero.png" -s 1440x720
# Product image
z-ai image -p "Sleek smartphone on minimalist desk, professional product photography" -o "./product.png" -s 1024x1024
# Blog post illustration
z-ai image -p "Abstract visualization of data flowing through networks" -o "./blog_header.png" -s 1344x768
# Social media content
z-ai image -p "Vibrant illustration of community connection" -o "./social.png" -s 1024x1024
# Website favicon/logo
z-ai image -p "Simple geometric logo with blue gradient, minimal design" -o "./logo.png" -s 1024x1024
# Background pattern
z-ai image -p "Subtle geometric pattern, pastel colors, website background" -o "./bg_pattern.png" -s 1440x720import ZAI from 'z-ai-web-dev-sdk';
import fs from 'fs';
import path from 'path';
async function generateImageBatch(prompts, outputDir, size = '1024x1024') {
const zai = await ZAI.create();
// Ensure output directory exists
if (!fs.existsSync(outputDir)) {
fs.mkdirSync(outputDir, { recursive: true });
}
const results = [];
for (let i = 0; i < prompts.length; i++) {
try {
const prompt = prompts[i];
const filename = `image_${i + 1}.png`;
const outputPath = path.join(outputDir, filename);
const response = await zai.images.generations.create({
prompt: prompt,
size: size
});
const imageBase64 = response.data[0].base64;
const buffer = Buffer.from(imageBase64, 'base64');
fs.writeFileSync(outputPath, buffer);
results.push({
success: true,
prompt: prompt,
path: outputPath,
size: buffer.length
});
console.log(`✓ Generated: ${filename}`);
} catch (error) {
results.push({
success: false,
prompt: prompts[i],
error: error.message
});
console.error(`✗ Failed: ${prompts[i]} - ${error.message}`);
}
}
return results;
}
// Usage
const prompts = [
'A serene mountain landscape at sunset',
'A futuristic city with flying cars',
'An underwater coral reef teeming with life'
];
const results = await generateImageBatch(prompts, './generated-images');
console.log(`Generated ${results.filter(r => r.success).length} images`);import ZAI from 'z-ai-web-dev-sdk';
import fs from 'fs';
import path from 'path';
import crypto from 'crypto';
class ImageGenerationService {
constructor(outputDir = './generated-images') {
this.outputDir = outputDir;
this.zai = null;
this.cache = new Map();
}
async initialize() {
this.zai = await ZAI.create();
if (!fs.existsSync(this.outputDir)) {
fs.mkdirSync(this.outputDir, { recursive: true });
}
}
generateCacheKey(prompt, size) {
return crypto
.createHash('md5')
.update(`${prompt}-${size}`)
.digest('hex');
}
async generate(prompt, options = {}) {
const {
size = '1024x1024',
useCache = true,
filename = null
} = options;
// Check cache
const cacheKey = this.generateCacheKey(prompt, size);
if (useCache && this.cache.has(cacheKey)) {
const cachedPath = this.cache.get(cacheKey);
if (fs.existsSync(cachedPath)) {
return {
path: cachedPath,
cached: true,
prompt: prompt,
size: size
};
}
}
// Generate new image
const response = await this.zai.images.generations.create({
prompt: prompt,
size: size
});
const imageBase64 = response.data[0].base64;
const buffer = Buffer.from(imageBase64, 'base64');
// Determine output path
const outputFilename = filename || `${cacheKey}.png`;
const outputPath = path.join(this.outputDir, outputFilename);
fs.writeFileSync(outputPath, buffer);
// Cache result
if (useCache) {
this.cache.set(cacheKey, outputPath);
}
return {
path: outputPath,
cached: false,
prompt: prompt,
size: size,
fileSize: buffer.length
};
}
clearCache() {
this.cache.clear();
}
getCacheSize() {
return this.cache.size;
}
}
// Usage
const service = new ImageGenerationService();
await service.initialize();
const result = await service.generate(
'A modern office space',
{ size: '1440x720' }
);
console.log('Generated:', result.path);# Using CLI for quick website asset generation
z-ai image -p "Modern tech hero banner, blue gradient" -o "./assets/hero.png" -s 1440x720
z-ai image -p "Team collaboration illustration" -o "./assets/team.png" -s 1344x768
z-ai image -p "Simple geometric logo" -o "./assets/logo.png" -s 1024x1024function buildEffectivePrompt(subject, style, details = []) {
const components = [
subject,
style,
...details,
'high quality',
'detailed'
];
return components.filter(Boolean).join(', ');
}
// Usage
const prompt = buildEffectivePrompt(
'mountain landscape',
'oil painting style',
['sunset lighting', 'dramatic clouds', 'reflection in lake']
);
// Result: "mountain landscape, oil painting style, sunset lighting, dramatic clouds, reflection in lake, high quality, detailed"function selectOptimalSize(purpose) {
const sizeMap = {
'hero-banner': '1440x720',
'blog-header': '1344x768',
'social-square': '1024x1024',
'portrait': '768x1344',
'product': '1024x1024',
'landscape': '1344x768',
'mobile-banner': '720x1440',
'thumbnail': '1024x1024'
};
return sizeMap[purpose] || '1024x1024';
}
// Usage
const size = selectOptimalSize('hero-banner');
await generateImage('website hero image', size, './hero.png');import ZAI from 'z-ai-web-dev-sdk';
import fs from 'fs';
async function safeGenerateImage(prompt, size, outputPath, retries = 3) {
let lastError;
for (let attempt = 1; attempt <= retries; attempt++) {
try {
const zai = await ZAI.create();
const response = await zai.images.generations.create({
prompt: prompt,
size: size
});
if (!response.data || !response.data[0] || !response.data[0].base64) {
throw new Error('Invalid response from image generation API');
}
const imageBase64 = response.data[0].base64;
const buffer = Buffer.from(imageBase64, 'base64');
fs.writeFileSync(outputPath, buffer);
return {
success: true,
path: outputPath,
attempts: attempt
};
} catch (error) {
lastError = error;
console.error(`Attempt ${attempt} failed:`, error.message);
if (attempt < retries) {
// Wait before retry (exponential backoff)
await new Promise(resolve => setTimeout(resolve, 1000 * attempt));
}
}
}
return {
success: false,
error: lastError.message,
attempts: retries
};
}import express from 'express';
import ZAI from 'z-ai-web-dev-sdk';
import fs from 'fs';
import path from 'path';
const app = express();
app.use(express.json());
app.use('/images', express.static('generated-images'));
let zaiInstance;
const outputDir = './generated-images';
async function initZAI() {
zaiInstance = await ZAI.create();
if (!fs.existsSync(outputDir)) {
fs.mkdirSync(outputDir, { recursive: true });
}
}
app.post('/api/generate-image', async (req, res) => {
try {
const { prompt, size = '1024x1024' } = req.body;
if (!prompt) {
return res.status(400).json({ error: 'Prompt is required' });
}
const response = await zaiInstance.images.generations.create({
prompt: prompt,
size: size
});
const imageBase64 = response.data[0].base64;
const buffer = Buffer.from(imageBase64, 'base64');
const filename = `img_${Date.now()}.png`;
const filepath = path.join(outputDir, filename);
fs.writeFileSync(filepath, buffer);
res.json({
success: true,
imageUrl: `/images/${filename}`,
prompt: prompt,
size: size
});
} catch (error) {
res.status(500).json({
success: false,
error: error.message
});
}
});
initZAI().then(() => {
app.listen(3000, () => {
console.log('Image generation API running on port 3000');
});
});#!/bin/bash
# Generate website assets using CLI
echo "Generating website assets..."
z-ai image -p "Modern tech hero banner, blue gradient" -o "./assets/hero.png" -s 1440x720
z-ai image -p "Team collaboration illustration" -o "./assets/team.png" -s 1344x768
z-ai image -p "Simple geometric logo" -o "./assets/logo.png" -s 1024x1024
echo "Assets generated successfully!"Issue: "SDK must be used in backend"
Issue: Invalid size parameter
Issue: Generated image doesn't match prompt
Issue: CLI command not found
Issue: Image file is corrupted
1024x1024 - Square768x1344 - Portrait864x1152 - Portrait1344x768 - Landscape1152x864 - Landscape1440x720 - Wide landscape720x1440 - Tall portrait© jjyaoao, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 2 other files (scripts) in skills/image-generation of jjyaoao/HelloAgents.
Open the folder on GitHubat commit c597a7c
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in jjyaoao/HelloAgents, which our catalogue first saw on October 7, 2026.
Image Generation next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Image Generation this skilljjyaoao/HelloAgents | 3.2k | 1 repos | ~3.8k | Automated safety check: Pass | MIT | |
| Glm Image Genzai-org/GLM-skills | 476 | — | ~2.9k | Automated safety check: Pass | Apache-2.0 | |
| Image EditAli-Marandi/Web-Scraper-Framework | 107 | — | ~6.2k | Automated safety check: Pass | MIT | |
| Image Genopen-octo/octo-agent | 125 | — | ~3.1k | Automated safety check: Notes | MIT | |
| Baoyu Image GenJimLiu/baoyu-skills | 27k | 1 repos | ~5.3k | Automated safety check: Notes | MIT | |
| Baoyu Imagineguanyang/open-agent-hub | 977 | — | ~4.6k | Automated safety check: Notes | MIT |
zai-org/GLM-skills
Official skill for generating high-quality images from text prompts using ZhiPu GLM-Image API.
Ali-Marandi/Web-Scraper-Framework
Implement AI image editing and modification capabilities using the z-ai-web-dev-sdk.
open-octo/octo-agent
Acquire images as files — generate them with an AI image model (14 providers: OpenAI/gpt-image, Gemini, Qwen, Zhipu, Volcengine, Stability, FLUX, Ideogram, MiniMax, and more), search openly-licensed…
JimLiu/baoyu-skills
AI image generation with OpenAI GPT Image 2.5, Azure OpenAI, Google, OpenRouter, DashScope, Z.AI GLM-Image, MiniMax, Jimeng, Seedream, Replicate and Agnes APIs.
guanyang/open-agent-hub
AI image generation with OpenAI GPT Image 2, Azure OpenAI, Google, OpenRouter, DashScope, Z.AI GLM-Image, MiniMax, Jimeng, Seedream and Replicate APIs.
zhayujie/CowAgent
Generates or edits images from text prompts through a Python script that picks an image backend based on which API keys are configured.
jjyaoao/HelloAgents
Implement specialized video understanding capabilities using the z-ai-web-dev-sdk.
jjyaoao/HelloAgents
Implement web page content extraction capabilities using the z-ai-web-dev-sdk.
jjyaoao/HelloAgents
Implement web search capabilities using the z-ai-web-dev-sdk.
jjyaoao/HelloAgents
Comprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction.
jjyaoao/HelloAgents
The PRIMARY tool for Spring Festival gift analysis and social interaction generation.
jjyaoao/HelloAgents
Transform UI style requirements into production-ready frontend code with systematic design tokens, accessibility compliance, and creative execution.
Works with
Categories
Implement AI image generation capabilities using the z-ai-web-dev-sdk. Image Generation is an agent skill from jjyaoao/HelloAgents. Implement AI image generation capabilities using the z-ai-web-dev-sdk.
Image Generation fits situations like: the user needs to create images from text descriptions; generate visual content; build applications with AI-powered image creation.
Run `npx skills add jjyaoao/HelloAgents --skill image-generation -a claude-code`. Or copy the skill folder (skills/image-generation in jjyaoao/HelloAgents) into .claude/skills/image-generation in your project. Claude Code loads it when a task matches its description.
Run `npx skills add jjyaoao/HelloAgents --skill image-generation -a codex`. Or copy the skill folder (skills/image-generation in jjyaoao/HelloAgents) into .agents/skills/image-generation in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jjyaoao/HelloAgents --skill image-generation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/image-generation, .gemini/skills/image-generation, .github/skills/image-generation and .opencode/skills/image-generation in your project.
Going by SKILL.md and its folder, Image Generation needs TypeScript for the scripts in its folder. Our summary lists: Node.js.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
Image Generation is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.8k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Image Generation: Glm Image Gen (zai-org/GLM-skills, 476 stars), Image Edit (Ali-Marandi/Web-Scraper-Framework, 107 stars), Image Gen (open-octo/octo-agent, 125 stars) and Baoyu Image Gen (JimLiu/baoyu-skills, 27k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
jjyaoao (a GitHub user) maintains it in jjyaoao/HelloAgents, which has 3,187 GitHub stars. The repository holds 11 skills in this directory. The repository was last updated on October 6, 2026.
Source: jjyaoao/HelloAgents on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.