How does the Reject Rescuer help me get my images approved?

This skill acts as a technical translator, taking vague rejection codes from agencies like Adobe Stock and providing specific instructions on how to fix artifacts, noise, or IP issues so you can successfully resubmit.

What exactly is included in this freebie skill package?

Since this is a 'freebie' skill, you get full access to the diagnostic engine and technical fixing instructions at no cost to help you streamline your microstock workflow.

Do I need a specific AI agent or software to use this skill?

The skill is designed to work with any text-based AI agent; simply copy the rejection reason provided by the agency and a brief description of your image to receive a diagnosis.

Does this skill automatically edit my images for me?

While the skill identifies technical flaws and IP risks based on agency standards, it does not visually 'see' your file; it relies on the metadata and rejection text you provide to generate fix-it steps.

How often is the knowledge base updated for new microstock guidelines?

This skill is regularly updated to reflect the evolving quality standards and submission guidelines of major platforms like Shutterstock and Adobe Stock, especially regarding AI-generated content.

Can I use this for rejected DSLR photos, or is it only for AI images?

Yes, it is highly effective for both AI-generated art and traditional DSLR photography, addressing common issues like chromatic aberration, sensor noise, and focus soft-spots.

freebie microstock reject rescuer

Example session with this skill installed

My AI image was rejected by Adobe Stock for 'Technical Quality.' It is a portrait of a woman in a forest. What does this mean and how do I fix it?

Read your context and instructions
Compiled the freebie microstock reject

I have analyzed the rejection reason for your AI portrait. In the context of Adobe Stock, 'Technical Quality' for AI assets usually points to specific generative artifacts or interpolation errors.

Rejection Diagnosis & Fix Plan

Likely Issue	What it Means	Technical Fix
Edge Halation	Glowing white or dark lines around the subject's hair or clothes.	Use a Layer Mask in Photoshop to contract the edges by 1-2 pixels.
Upscaling Noise	Grainy patterns caused by low-quality AI enlargers.	Apply Camera Raw 'Denoise' at 20% or use a Topaz Photo AI pass.
AI Artifacting	'Melted' details in the background foliage or extra fingers.	Use Generative Fill or a Stamp Tool to clean up non-organic shapes.
Interpolation Blur	Lack of sharp focus on the eyes, common in mid-range AI models.	Apply a High Pass filter at 1.5px radius to the eyes only.
Sensor Spots	Rejection code sometimes triggers if the AI replicates dust.	Check for repeating dark spots in the sky or uniform areas.

Technical Checklist for Resubmission

Check the Eyes: Zoom in to 200%. If the iris is not perfectly circular, use a circular marquee tool to reshape.

Flatten Colors: AI often creates 'banding' in out-of-focus forest backgrounds. Add a 1% monochromatic noise layer to break up the bands.
3. Property Check: Ensure no recognizable hiking gear brands are visible on the clothing.

Next steps

Inspect your file at 100% zoom for the specific artifacts listed above.
Apply a subtle sharpening pass to the primary subject before re-exporting as a high-quality JPEG.
Once fixed, use my

Microstock Commercial Metadata Generator to create the 50 SEO tags required for the commercial marketplace.

Connects securely to your tools. The creator never sees your data.

About this skill

The problem

Microstock agencies provide cryptic rejection reasons like "Technical Issues" or "Artifacting" without explaining how to fix them. Creators waste hours guessing why their AI images or photos were declined.

What it does

Translates vague agency rejection codes into actionable technical feedback.
Identifies common AI generation failures like edge halation, noise, and upscaling artifacts.
Flags potential Intellectual Property (IP) violations before you resubmit.
Provides specific post-processing steps to salvage rejected files.

Why this beats prompting it yourself

Generic AI prompts often miss the specific quality standards of platforms like Adobe Stock or Shutterstock. This skill uses a specialized knowledge base of microstock inspector criteria to pinpoint technical flaws that general models overlook.

Use cases

Deciphering "Technical Issues" rejections for AI-generated landscapes.
Cleaning up noise and chromatic aberration in DSLR photography.
Identifying logos or trademarked property that trigger IP rejections.
Preparing rejected images for successful second-round submission.

Known limitations

Requires the user to provide the specific rejection text and an image description. It cannot visually inspect the image file directly without an LLM vision interface.

How to install

Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.

~30 seconds

1
Download the ZIP
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2
Unzip into your skills folder
Every agent reads skills from one folder on your machine. Drop the unzipped folder in there.
3
Ask your agent to use it
Restart the agent if it was already running. It picks the skill up automatically - no config needed.

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Click the path to copy it. Create the folder if it does not exist yet.

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freebie microstock reject rescuer