Which image models do these prompts work with?

They are written in plain descriptive language with a separate negative block, which suits Midjourney, Firefly, Stable Diffusion, Flux and similar models. Some tools want negatives in a dedicated field — move that section across when yours does.

Do I need an API key to generate prompts?

No. Prompt assembly is local and free. Keys are only needed elsewhere in the toolbox, where an AI provider actually writes metadata for your files.

Why does every prompt exclude logos, text and faces?

Because those are the most common reasons a generative stock submission is rejected. Trademarks and readable text create licensing problems, and identifiable faces need a model release that generated people cannot provide.

Will these prompts guarantee acceptance on Adobe Stock?

No prompt can. They remove the predictable failure modes — generic framing, brand artefacts, stray text — but the model output still needs your own review for anatomy errors, warped detail and mangled typography before you submit.

How should I keyword generated images afterwards?

Run the finished files through the metadata studio, which writes titles, descriptions and ranked keywords against each marketplace's limits, and flag the AI disclosure when you embed or export.

Tools / Prompt generator

Adobe Stock prompt generator

Unique, production-ready prompts built around Adobe Stock's content policy. Every batch is checked against everything already generated so you avoid similar-content rejections.

Prompts (0)

Set a brief and generate your first batch. Prompts stay in this browser and are never sent anywhere except your own AI provider.

About the prompt generator

Generative stock succeeds or fails on the brief. This generator turns a subject into a structured, commercially-minded prompt — with the composition, lighting, and negative constraints written in — instead of the one-line request that produces images no buyer searches for.

The problem it solves

A prompt like "business meeting" returns the most generic image the model knows: centred, evenly lit, cluttered, and identical to thousands of existing files. Prompts that actually sell read like an art director's brief — they name the subject, the setting, the lens behaviour, the light, the mood, the colour direction, and the copy space a designer will need.

There is a second constraint specific to stock: what must not appear. Logos, recognisable faces without releases, readable text, brand-shaped objects and watermark-like artefacts are all rejection triggers, and models add them unprompted unless told otherwise. Writing that exclusion list by hand every time is exactly the sort of repetitive work worth automating.

How it works, step by step

1. Start from a theme or your own subject
Pick a category from the built-in catalogue of commercially proven stock themes, or type your own subject. Categories carry their own conventions, so a food brief and a business brief are not treated identically.
2. Set the direction
Choose the shot type, lighting, mood, colour treatment and orientation. Each control maps to phrasing that image models respond to consistently rather than to vague adjectives.
3. Structured assembly
The prompt is assembled in a deliberate order — subject, action, environment, camera and lens, lighting, colour, mood, then technical qualifiers — because leading tokens carry the most weight in most models.
4. Commercial guardrails
A negative-constraint block is appended automatically: no logos or brand marks, no readable text, no watermarks, no recognisable identifiable faces where a release would be required. These map directly to the reasons generative submissions get rejected.
5. Take variations away
Generate several variants at once, copy any of them, or export the set so you can run a spread of prompts in one session and keep the ones that land.

Using the output well

Treat a generated prompt as a first draft to iterate on, not a lottery ticket. Change one element at a time — the lighting, then the lens, then the mood — so you learn which token actually moved the image. Keep the prompt text with the file too: when a set sells, the prompt is the record of how to make more of it.

Disclosure still applies. Generative work must be declared as AI-generated on Adobe Stock and Shutterstock, and orientation and copy space matter more here than in traditional shooting, because buyers are usually placing headlines over these images. If you generate wide with intentional negative space, say so in the prompt rather than cropping for it afterwards.

Questions about this tool

Which image models do these prompts work with?: They are written in plain descriptive language with a separate negative block, which suits Midjourney, Firefly, Stable Diffusion, Flux and similar models. Some tools want negatives in a dedicated field — move that section across when yours does.
Do I need an API key to generate prompts?: No. Prompt assembly is local and free. Keys are only needed elsewhere in the toolbox, where an AI provider actually writes metadata for your files.
Why does every prompt exclude logos, text and faces?: Because those are the most common reasons a generative stock submission is rejected. Trademarks and readable text create licensing problems, and identifiable faces need a model release that generated people cannot provide.
Will these prompts guarantee acceptance on Adobe Stock?: No prompt can. They remove the predictable failure modes — generic framing, brand artefacts, stray text — but the model output still needs your own review for anatomy errors, warped detail and mangled typography before you submit.
How should I keyword generated images afterwards?: Run the finished files through the metadata studio, which writes titles, descriptions and ranked keywords against each marketplace's limits, and flag the AI disclosure when you embed or export.