ID

ideogram-reference-architecture

Provides a production-grade architecture for Ideogram, covering prompt templating, asset storage, and pipeline design.

Install

mkdir -p .claude/skills/ideogram-reference-architecture && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/6316" && unzip -o skill.zip -d .claude/skills/ideogram-reference-architecture && rm skill.zip

Installs to .claude/skills/ideogram-reference-architecture

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Implement Ideogram reference architecture with prompt templates, asset
70 charsno explicit “when” trigger
Intermediate

Key capabilities

  • Implement prompt template systems for brand consistency
  • Execute generation pipelines using six API endpoints
  • Automate asset downloading and local storage
  • Perform reference-based generation via describe-then-remix
  • Generate multi-format assets including PNG and WebP
  • Track asset metadata for reproducibility

How it works

The architecture uses a template-based prompt system to standardize generation requests across six API endpoints. It automatically downloads generated images to local storage to prevent URL expiration and tracks assets in a manifest.

Inputs & outputs

You give it
Template key and variable object
You get back
Local file path, image seed, and metadata manifest

When to use ideogram-reference-architecture

  • Design scalable image generation pipelines
  • Implement prompt templating systems
  • Set up asset storage and CDN delivery
  • Establish brand guidelines for AI assets

About this skill

Ideogram Reference Architecture

Overview

Production architecture for AI image generation with Ideogram at scale. Covers prompt templating for brand consistency, generation pipelines using all six API endpoints, asset storage and CDN delivery, and metadata tracking for reproducibility.

Architecture Diagram

┌─────────────────────────────────────────────────────────┐
│  Prompt Engineering Layer                                │
│  Templates │ Brand Guidelines │ Negative Prompts         │
└──────────────────────────┬──────────────────────────────┘
                           │
                           ▼
┌─────────────────────────────────────────────────────────┐
│  Ideogram API (api.ideogram.ai)                          │
│  ┌──────────┐ ┌────────┐ ┌───────┐ ┌────────┐          │
│  │ Generate │ │ Edit   │ │ Remix │ │Describe│          │
│  │(text→img)│ │(inpaint)│ │(vary) │ │(img→txt)│         │
│  └────┬─────┘ └───┬────┘ └──┬────┘ └───┬────┘          │
│       │           │         │          │                │
│  ┌────┴───────────┴─────────┴──────────┘                │
│  │  ┌──────────┐  ┌─────────┐                           │
│  │  │ Upscale  │  │ Reframe │                           │
│  │  └────┬─────┘  └────┬────┘                           │
│  └───────┴──────────────┘                               │
└──────────────────────────┬──────────────────────────────┘
                           │
                           ▼
┌─────────────────────────────────────────────────────────┐
│  Post-Processing & Storage                               │
│  Download │ Resize │ WebP Convert │ S3/GCS │ CDN        │
└─────────────────────────────────────────────────────────┘

Instructions

Step 1: Prompt Template System

interface PromptTemplate {
  name: string;
  base: string;
  style: string;
  negativePrompt: string;
  aspectRatio: string;
  model: string;
  renderingSpeed?: string;
}

const BRAND_TEMPLATES: Record<string, PromptTemplate> = {
  socialPost: {
    name: "Social Media Post",
    base: "{subject}, modern clean design, vibrant colors, professional",
    style: "DESIGN",
    negativePrompt: "blurry text, misspelled, watermark, low quality",
    aspectRatio: "ASPECT_1_1",
    model: "V_2",
  },
  blogHero: {
    name: "Blog Hero Image",
    base: "{subject}, editorial photography, wide composition, cinematic lighting",
    style: "REALISTIC",
    negativePrompt: "text overlay, watermark, blurry, oversaturated",
    aspectRatio: "ASPECT_16_9",
    model: "V_2",
  },
  storyVertical: {
    name: "Story / Reel",
    base: "{subject}, vertical composition, eye-catching, bold colors",
    style: "DESIGN",
    negativePrompt: "horizontal layout, small text, blurry",
    aspectRatio: "ASPECT_9_16",
    model: "V_2_TURBO",
  },
  ogImage: {
    name: "Open Graph Image",
    base: '{subject}, with text "{title}" in bold clean font, tech aesthetic',
    style: "DESIGN",
    negativePrompt: "blurry text, misspelled words, cluttered",
    aspectRatio: "ASPECT_16_9",
    model: "V_2",
  },
};

function buildPrompt(templateKey: string, vars: Record<string, string>): string {
  const template = BRAND_TEMPLATES[templateKey];
  if (!template) throw new Error(`Unknown template: ${templateKey}`);
  let prompt = template.base;
  for (const [key, value] of Object.entries(vars)) {
    prompt = prompt.replace(`{${key}}`, value);
  }
  return prompt;
}

Step 2: Generation Service

import { writeFileSync, mkdirSync } from "fs";
import { join } from "path";

const API_KEY = process.env.IDEOGRAM_API_KEY!;

async function generateFromTemplate(
  templateKey: string,
  vars: Record<string, string>,
  outputDir = "./assets"
) {
  const template = BRAND_TEMPLATES[templateKey];
  const prompt = buildPrompt(templateKey, vars);

  const response = await fetch("https://api.ideogram.ai/generate", {
    method: "POST",
    headers: { "Api-Key": API_KEY, "Content-Type": "application/json" },
    body: JSON.stringify({
      image_request: {
        prompt,
        model: template.model,
        style_type: template.style,
        aspect_ratio: template.aspectRatio,
        negative_prompt: template.negativePrompt,
        magic_prompt_option: "AUTO",
      },
    }),
  });

  if (!response.ok) throw new Error(`Generate failed: ${response.status}`);
  const result = await response.json();
  const image = result.data[0];

  // Download immediately (URLs expire ~1hr)
  const imgResp = await fetch(image.url);
  const buffer = Buffer.from(await imgResp.arrayBuffer());
  mkdirSync(outputDir, { recursive: true });
  const filename = `${templateKey}-${image.seed}.png`;
  writeFileSync(join(outputDir, filename), buffer);

  return {
    localPath: join(outputDir, filename),
    seed: image.seed,
    prompt,
    resolution: image.resolution,
    template: templateKey,
  };
}

Step 3: Multi-Format Asset Pipeline

import sharp from "sharp";

async function generateBrandAssetSet(subject: string, title: string) {
  const results = [];

  for (const [key, template] of Object.entries(BRAND_TEMPLATES)) {
    const asset = await generateFromTemplate(key, { subject, title });
    results.push(asset);

    // Generate WebP variant for web
    await sharp(asset.localPath)
      .webp({ quality: 85 })
      .toFile(asset.localPath.replace(".png", ".webp"));

    // Rate limit courtesy
    await new Promise(r => setTimeout(r, 3000));
  }

  // Generate manifest for asset tracking
  const manifest = results.map(r => ({
    template: r.template,
    seed: r.seed,
    prompt: r.prompt,
    files: {
      png: r.localPath,
      webp: r.localPath.replace(".png", ".webp"),
    },
  }));

  writeFileSync("./assets/manifest.json", JSON.stringify(manifest, null, 2));
  console.log(`Generated ${results.length} brand assets with manifest`);
  return results;
}

Step 4: Describe-then-Remix Pipeline

// Use Describe to analyze a reference image, then Remix to create variations
async function referenceBasedGeneration(referenceImagePath: string, modifications: string) {
  // Step 1: Describe the reference image
  const form1 = new FormData();
  form1.append("image_file", new Blob([readFileSync(referenceImagePath)]));
  form1.append("describe_model_version", "V_3");

  const descResp = await fetch("https://api.ideogram.ai/describe", {
    method: "POST",
    headers: { "Api-Key": API_KEY },
    body: form1,
  });
  const descriptions = await descResp.json();
  const basePrompt = descriptions.descriptions[0].text;

  // Step 2: Remix with modifications
  const form2 = new FormData();
  form2.append("image", new Blob([readFileSync(referenceImagePath)]));
  form2.append("prompt", `${basePrompt}, ${modifications}`);
  form2.append("image_weight", "40");
  form2.append("rendering_speed", "DEFAULT");

  const remixResp = await fetch("https://api.ideogram.ai/v1/ideogram-v3/remix", {
    method: "POST",
    headers: { "Api-Key": API_KEY },
    body: form2,
  });

  return remixResp.json();
}

Project Structure

project/
├── src/
│   ├── ideogram/
│   │   ├── client.ts          # API wrapper
│   │   ├── templates.ts       # Prompt templates
│   │   ├── pipeline.ts        # Generation pipeline
│   │   └── types.ts           # TypeScript types
│   ├── storage/
│   │   └── s3.ts              # Image upload to S3/GCS
│   └── api/
│       └── generate.ts        # API route handler
├── assets/                    # Generated image output
│   └── manifest.json          # Asset tracking
├── tests/
│   ├── templates.test.ts      # Prompt template tests
│   └── pipeline.test.ts       # Pipeline tests (mocked)
└── config/
    ├── ideogram.ts            # API configuration
    └── templates.json         # Prompt templates (optional)

Error Handling

IssueCauseSolution
Inconsistent styleNo template systemUse branded prompt templates
URL expiredLate downloadDownload in same function call
Text misspelledPrompt too vagueUse DESIGN style, quote exact text
Wrong aspect ratioTemplate mismatchMap templates to target platforms

Output

  • Prompt template system for brand consistency
  • Generation service with auto-download
  • Multi-format asset pipeline (PNG + WebP)
  • Describe-then-remix pipeline for reference-based generation
  • Asset manifest for tracking and reproducibility

Resources

Next Steps

For multi-environment setup, see ideogram-multi-env-setup.

When not to use it

  • When using outdated Ideogram API versions
  • When manual asset management is required

Prerequisites

IDEOGRAM_API_KEY environment variableNode.js environment with fs and path modulesSharp library for image processing

Limitations

  • Text misspellings occur if prompts are too vague

How it compares

This approach replaces manual API calls with a structured pipeline that enforces brand guidelines and automates post-processing tasks like resizing and format conversion.

Compared to similar skills

ideogram-reference-architecture side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
ideogram-reference-architecture (this skill)127dCautionIntermediate
software-architecture3336moNo flagsIntermediate
architect-review1094moNo flagsAdvanced
mcp-builder1363moReviewAdvanced

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