Why Adobe Rejects Your Metadata CSV Header Instantly And How To Fix It

Description and use

Automating CSV header creation prevents instant rejections on Adobe Stock and other platforms, while upload tracking avoids duplicate submissions.

Problem

Hand‑built CSV headers cause instant rejection by Adobe Stock and other platforms, wasting time and risking account flags.

Outcome

Automated metadata generation eliminates header errors, reduces rejection emails, and prevents account flagging from duplicate uploads.

Workflow

• 1. Run make_metadata.py with --platform to generate a CSV with the exact header required by the target platform.
• 2. (Optional) Provide a titles.json file with real titles and keywords via --titles.
• 3. Use upload_tracker.py to track which assets have already been uploaded and avoid double‑posting.
• 4. Verify header, titles, and tracker status before uploading.
• 5. Upload the assets and CSV to the platform.

Evidence

Adobe’s uploader reads a strict 5‑column format. The header row must be exactly these five columns, in this order: Filename,Title,Keywords,Category,Releases

Source

I stopped writing CSVs by hand. make_metadata.py in my pipeline takes a folder of files and writes the header each platform demands, and nothing else

Source

Once the header was fixed I hit the next failure. I re‑ran a batch to fix one bad file and accidentally re‑uploaded the whole set. Uploading the same asset twice is one of the fastest ways to get an account flagged

Source