Agent skill

Image Generation

by jjyaoao in jjyaoao/HelloAgents

Implement AI image generation capabilities using the z-ai-web-dev-sdk.

MITAuto-check passedMedia & Creative

Install Image Generation

skills CLI
$ npx skills add jjyaoao/HelloAgents --skill image-generation -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jjyaoao/HelloAgents image-generation --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ 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-src

Use ~/.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/

Facts

Skill name
image-generation
GitHub stars
3.2k
Used in
1 other repo
Token cost
~3.8k tokens
SKILL.md length
499 words
Files
3 (incl. scripts)
Skills in repo
11
Repo updated
First seen
Licence
MIT

At a glance

Implement AI image generation capabilities using the z-ai-web-dev-sdk.

  • Works in 3 steps: Effective Prompt Engineering → Size Selection Helper → Error Handling
  • The user needs to create images from text descriptions
  • SKILL.md covers Skills Path, Overview, Prerequisites and Basic Image Generation, plus 10 more sections
  • Runs TypeScript scripts from its folder

What it does

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.

When your agent uses it

  • The user needs to create images from text descriptions
  • Generate visual content
  • Build applications with AI-powered image creation

Example prompts

  • “/image-generation”

Requirements

  • Node.js

Workflow steps

3 steps, taken from the step headings in SKILL.md.

  1. Effective Prompt Engineering
  2. Size Selection Helper
  3. Error Handling

What it can do on your machine

Read from SKILL.md and the folder at commit c597a7c. It shows what the files ask for, not the result of running them.

  • Tool permissions

    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.

  • Runs code

    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.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

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.

Always · name and description, kept in context so the agent knows when to use it
~97
When it runs · the whole SKILL.md, loaded when a task matches
~3.8k

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.

Safety

Auto-check passed

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.

SKILL.md

The full file from jjyaoao/HelloAgents at commit c597a7c, republished under its MIT licence (© jjyaoao). 499 words, ~3,780 tokens.

Download SKILL.mdSave it as .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.
name
image-generation
description
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.
license
MIT

Image Generation Skill

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.

Skills Path

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.

Overview

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.

Prerequisites

The z-ai-web-dev-sdk package is already installed. Import it as shown in the examples below.

Basic Image Generation

Simple Image Creation
javascript
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'
);
Multiple Image Sizes
javascript
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'
);

CLI Tool Usage

The z-ai CLI tool provides a convenient way to generate images directly from the command line.

Basic CLI Usage
bash
# 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
CLI Use Cases
bash
# 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 1440x720

Advanced Use Cases

Batch Image Generation
javascript
import 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`);
Image Generation Service
javascript
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);
Website Asset Generator
bash
# 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 1024x1024

Best Practices

1. Effective Prompt Engineering
javascript
function 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"
2. Size Selection Helper
javascript
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');
3. Error Handling
javascript
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
  };
}

Common Use Cases

  1. Website Design: Generate hero images, backgrounds, and visual assets
  2. Marketing Materials: Create social media graphics and promotional images
  3. Product Visualization: Generate product mockups and variations
  4. Content Creation: Produce blog post illustrations and thumbnails
  5. Brand Assets: Create logos, icons, and brand imagery
  6. UI/UX Design: Generate interface elements and illustrations
  7. Game Development: Create concept art and game assets
  8. E-commerce: Generate product images and lifestyle shots

Integration Examples

Express.js API Endpoint
javascript
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');
  });
});

CLI Integration in Scripts

Shell Script Example
bash
#!/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!"
Show full SKILL.md (231 more words)Show less

Troubleshooting

Issue: "SDK must be used in backend"

  • Solution: Ensure z-ai-web-dev-sdk is only used in server-side code

Issue: Invalid size parameter

  • Solution: Use only supported sizes: 1024x1024, 768x1344, 864x1152, 1344x768, 1152x864, 1440x720, 720x1440

Issue: Generated image doesn't match prompt

  • Solution: Make prompts more specific and descriptive. Include style, details, and quality terms

Issue: CLI command not found

  • Solution: Ensure z-ai CLI is properly installed and in PATH

Issue: Image file is corrupted

  • Solution: Verify base64 decoding and file writing are correct

Prompt Engineering Tips

Good Prompts
  • ✓ "Professional product photography of wireless headphones, white background, studio lighting, high quality"
  • ✓ "Mountain landscape at golden hour, oil painting style, dramatic clouds, detailed"
  • ✓ "Modern minimalist logo for tech company, blue and white, geometric shapes"
Poor Prompts
  • ✗ "headphones"
  • ✗ "picture of mountains"
  • ✗ "logo"
Prompt Components
  1. Subject: What you want to see
  2. Style: Art style, photography style, etc.
  3. Details: Specific elements, colors, mood
  4. Quality: "high quality", "detailed", "professional"

Supported Image Sizes

  • 1024x1024 - Square
  • 768x1344 - Portrait
  • 864x1152 - Portrait
  • 1344x768 - Landscape
  • 1152x864 - Landscape
  • 1440x720 - Wide landscape
  • 720x1440 - Tall portrait

Remember

  • Always use z-ai-web-dev-sdk in backend code only
  • The SDK is already installed - import as shown
  • CLI tool is available for quick image generation
  • Supported sizes are specific - use the provided list
  • Base64 images need to be decoded before saving
  • Consider caching for repeated prompts
  • Implement retry logic for production applications
  • Use descriptive prompts for better results

© jjyaoao, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (scripts) in skills/image-generation of jjyaoao/HelloAgents.

  • SKILL.md
  • LICENSE.txt
  • scripts/image-generation.ts

Open the folder on GitHubat commit c597a7c

Used in 1 other repository

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.

Compare with similar skills

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.

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Image EditAli-Marandi/Web-Scraper-Framework107—~6.2kAutomated safety check: PassMIT
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Baoyu Image GenJimLiu/baoyu-skills27k1 repos~5.3kAutomated safety check: NotesMIT
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Works with

Questions about Image Generation

What does Image Generation do?

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.

When should I use Image Generation?

Image Generation fits situations like: the user needs to create images from text descriptions; generate visual content; build applications with AI-powered image creation.

How do I install Image Generation in Claude Code?

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.

How do I install Image Generation in Codex?

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.

Can I use Image Generation in Cursor, Gemini CLI or GitHub Copilot?

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.

What does Image Generation need to run?

Going by SKILL.md and its folder, Image Generation needs TypeScript for the scripts in its folder. Our summary lists: Node.js.

Does Image Generation access the network?

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.

Is Image Generation safe to install?

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.

What licence does Image Generation use?

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.

How many tokens does Image Generation use?

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.

What are the alternatives to Image Generation?

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.

Who maintains Image Generation?

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.