adobe-core-workflow-a
Execute Adobe Firefly Services workflow: AI image generation, generative fill, and expand image using the Firefly v3 API. Use when generating images from prompts, filling or expanding images with AI, or building creative automation pipelines. Trigger with phrases like "adobe firefly", "generate image adobe", "firefly text to image", "adobe AI image", "generative fill".
Best use case
adobe-core-workflow-a is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Execute Adobe Firefly Services workflow: AI image generation, generative fill, and expand image using the Firefly v3 API. Use when generating images from prompts, filling or expanding images with AI, or building creative automation pipelines. Trigger with phrases like "adobe firefly", "generate image adobe", "firefly text to image", "adobe AI image", "generative fill".
Teams using adobe-core-workflow-a should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/adobe-core-workflow-a/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How adobe-core-workflow-a Compares
| Feature / Agent | adobe-core-workflow-a | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Execute Adobe Firefly Services workflow: AI image generation, generative fill, and expand image using the Firefly v3 API. Use when generating images from prompts, filling or expanding images with AI, or building creative automation pipelines. Trigger with phrases like "adobe firefly", "generate image adobe", "firefly text to image", "adobe AI image", "generative fill".
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# Adobe Core Workflow A — Firefly Services
## Overview
Primary creative workflow using Adobe Firefly v3 APIs: text-to-image generation, generative fill (inpainting), and image expansion (outpainting). These are the most common Firefly Services operations for marketing asset automation.
## Prerequisites
- Completed `adobe-install-auth` with Firefly API scopes (`firefly_api,ff_apis`)
- `@adobe/firefly-apis` installed, or direct REST access
- Pre-signed cloud storage URLs for input/output images (S3, Azure Blob, or Dropbox)
## Instructions
### Step 1: Text-to-Image Generation (Synchronous)
```typescript
// src/workflows/firefly-generate.ts
import { getAccessToken } from '../adobe/client';
interface FireflyGenerateOptions {
prompt: string;
negativePrompt?: string;
width?: number; // 1024, 1472, 1792, 2048
height?: number;
n?: number; // 1-4 images
contentClass?: 'art' | 'photo';
style?: {
presets?: string[]; // e.g., ['digital_art', 'cinematic']
strength?: number; // 0-100
};
}
interface FireflyOutput {
outputs: Array<{
image: { url: string };
seed: number;
}>;
}
export async function generateImage(opts: FireflyGenerateOptions): Promise<FireflyOutput> {
const token = await getAccessToken();
const body: Record<string, any> = {
prompt: opts.prompt,
n: opts.n || 1,
size: { width: opts.width || 1024, height: opts.height || 1024 },
contentClass: opts.contentClass || 'photo',
};
if (opts.negativePrompt) body.negativePrompt = opts.negativePrompt;
if (opts.style?.presets) {
body.styles = { presets: opts.style.presets };
}
const response = await fetch('https://firefly-api.adobe.io/v3/images/generate', {
method: 'POST',
headers: {
'Authorization': `Bearer ${token}`,
'x-api-key': process.env.ADOBE_CLIENT_ID!,
'Content-Type': 'application/json',
},
body: JSON.stringify(body),
});
if (!response.ok) {
const err = await response.text();
throw new Error(`Firefly generate failed (${response.status}): ${err}`);
}
return response.json();
}
```
### Step 2: Async Generation (for High Volume)
```typescript
// For production pipelines, use async endpoint to avoid HTTP timeouts
export async function generateImageAsync(opts: FireflyGenerateOptions) {
const token = await getAccessToken();
const response = await fetch('https://firefly-api.adobe.io/v3/images/generate-async', {
method: 'POST',
headers: {
'Authorization': `Bearer ${token}`,
'x-api-key': process.env.ADOBE_CLIENT_ID!,
'Content-Type': 'application/json',
},
body: JSON.stringify({
prompt: opts.prompt,
n: opts.n || 1,
size: { width: opts.width || 1024, height: opts.height || 1024 },
}),
});
const { jobId, statusUrl, cancelUrl } = await response.json();
console.log(`Firefly async job: ${jobId}`);
// Poll for completion
let result: any;
while (true) {
await new Promise(r => setTimeout(r, 2000));
const poll = await fetch(statusUrl, {
headers: {
'Authorization': `Bearer ${token}`,
'x-api-key': process.env.ADOBE_CLIENT_ID!,
},
});
result = await poll.json();
if (result.status === 'succeeded' || result.status === 'failed') break;
}
if (result.status === 'failed') throw new Error(`Async generation failed: ${result.error}`);
return result;
}
```
### Step 3: Generative Fill (Inpainting)
```typescript
// Fill a masked region of an image with AI-generated content
export async function generativeFill(
imageUrl: string,
maskUrl: string,
prompt: string
): Promise<FireflyOutput> {
const token = await getAccessToken();
const response = await fetch('https://firefly-api.adobe.io/v3/images/fill', {
method: 'POST',
headers: {
'Authorization': `Bearer ${token}`,
'x-api-key': process.env.ADOBE_CLIENT_ID!,
'Content-Type': 'application/json',
},
body: JSON.stringify({
image: { source: { url: imageUrl } },
mask: { source: { url: maskUrl } },
prompt,
n: 1,
}),
});
if (!response.ok) throw new Error(`Fill failed: ${response.status}`);
return response.json();
}
```
### Step 4: Image Expansion (Outpainting)
```typescript
// Expand an image to a larger canvas size with AI-generated surroundings
export async function expandImage(
imageUrl: string,
targetWidth: number,
targetHeight: number,
prompt?: string
): Promise<FireflyOutput> {
const token = await getAccessToken();
const response = await fetch('https://firefly-api.adobe.io/v3/images/expand', {
method: 'POST',
headers: {
'Authorization': `Bearer ${token}`,
'x-api-key': process.env.ADOBE_CLIENT_ID!,
'Content-Type': 'application/json',
},
body: JSON.stringify({
image: { source: { url: imageUrl } },
size: { width: targetWidth, height: targetHeight },
...(prompt && { prompt }),
n: 1,
}),
});
if (!response.ok) throw new Error(`Expand failed: ${response.status}`);
return response.json();
}
```
## Output
- AI-generated images from text prompts (sync or async)
- Inpainted regions via generative fill with mask
- Expanded/outpainted images to larger canvas sizes
- Temporary URLs for generated images (download within 24h)
## Error Handling
| Error | Cause | Solution |
|-------|-------|----------|
| `400` prompt rejected | Content policy violation | Remove trademarks, real people, or explicit content from prompt |
| `403 Forbidden` | Missing `firefly_api` scope | Add Firefly API to Developer Console project |
| `413 Payload Too Large` | Image too large for fill/expand | Resize input to max 4096x4096 |
| `429 Too Many Requests` | Rate limited | Use async endpoint; honor `Retry-After` header |
| `500 Internal Server Error` | Transient Firefly error | Retry with backoff; check status.adobe.com |
## Resources
- [Firefly API Reference](https://developer.adobe.com/firefly-services/docs/firefly-api/api/)
- [Firefly Generate Image Tutorial](https://developer.adobe.com/firefly-services/docs/firefly-api/guides/how-tos/firefly-generate-image-api-tutorial)
- [Using Async APIs](https://developer.adobe.com/firefly-services/docs/firefly-api/guides/how-tos/using-async-apis)
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