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adobe-firefly-image

Create, edit, composite, expand, fill, and upscale images via Adobe Firefly Services APIs.

123|21|Updated Jul 11, 2026
Search Tags:#image generation#provenance#api integration#image editing#adobe firefly#product compositing#mask fill
One-click install
npx skills add https://github.com/calesthio/generative-media-skills --skill adobe-firefly-image
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: adobe-firefly-image
Source: https://github.com/calesthio/generative-media-skills/tree/main/skills/providers/image-generation/adobe-firefly-image
Command: npx skills add https://github.com/calesthio/generative-media-skills --skill adobe-firefly-image

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps teams create, edit, composite, expand, fill, and upscale still images with Adobe Firefly while managing asynchronous jobs, API version differences, rights, provenance, and production QA.

Core Features & Use Cases

  • Image Generation: Use current Firefly Image 5 or Image 3/4 APIs for controlled text-to-image production with model-specific schemas, aspect ratios, resolutions, references, seeds, and locale settings.
  • Image Editing and Compositing: Perform masked fills, canvas expansion, similar-image generation, instruct edits, precise product composites, adaptive composites, and fidelity-oriented upscaling.
  • Production Integration: Authenticate securely, upload source assets and masks, poll asynchronous jobs, handle rate limits and failures, download outputs promptly, and preserve audit metadata.
  • Use Case: Create campaign concepts, place regulated product packaging into supplied environments, or generate seeded fill variations while validating unchanged regions, label fidelity, dimensions, and provenance.

Quick Start

Use the Adobe Firefly image skill to create a still-image production plan or implement an authenticated asynchronous workflow for the requested generation, edit, composite, or validation task.

Frequently Asked Questions about adobe-firefly-image

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate Adobe Firefly images via API integration?▼

To generate Adobe Firefly images via API integration, you send authenticated text-to-image requests using model-specific schemas for aspect ratios, resolutions, and seeds, then poll asynchronous jobs to download the final outputs.

Can I perform masked fills and product compositing with Adobe Firefly APIs?▼

Yes, masked fills and product compositing with Adobe Firefly APIs allow you to upload source assets and masks, apply precise product composites, and generate seeded fill variations while validating unchanged regions and label fidelity.

How does asynchronous job polling work for image generation workflows?▼

Asynchronous job polling for image generation workflows works by submitting authenticated API requests, continuously checking job status to handle rate limits and failures, and promptly downloading the completed visual outputs.

Do I need secure server-side OAuth to use Adobe Firefly image editing APIs?▼

Yes, you need secure server-side OAuth to authenticate with Adobe Firefly image editing APIs, ensuring your production integration safely handles schema-aware requests, asset rights checks, and provenance tracking.

What is the best way to track provenance for AI-generated campaign concepts?▼

The best way to track provenance for AI-generated campaign concepts is to preserve audit metadata throughout the creation and editing workflow, ensuring visual QA validates dimensions, asset rights, and content authenticity.

Why handle rate limits and failures during canvas expansion or upscaling?▼

Handling rate limits and failures during canvas expansion or upscaling prevents workflow interruptions, ensuring your asynchronous API requests successfully complete fidelity-oriented upscaling and adaptive composites without dropping jobs.

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