watermarks-remover
Removes embedded provenance markers and metadata across multiple file formats, enabling clean data pipelines and reducing downstream compliance friction from…
Strip multi-vendor AI provenance marks: Unicode text hygiene, statistical rewrite hooks, and C2PA/metadata from PNG/JPEG/SVG/PDF/DOCX/HTML/MD
- Remove AI-generated watermarks and metadata from images before republishing to internal systems.
- Strip C2PA provenance marks from documents to normalize supplier files across vendor sources.
- Clean Unicode artifacts and statistical markers from text before processing through analytics pipelines.
Removes embedded provenance markers and metadata across multiple file formats, enabling clean data pipelines and reducing downstream compliance friction from mixed AI-generated and human content sources.
Data engineering teams processing mixed-origin content for training datasets or analytics workflows.
https://github.com/guillaumemeyer/watermarks-remover
By guillaumemeyer
How to Get It
claude plugins install guillaumemeyer/watermarks-remover
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
After installing, paste this into Claude:
Help me remove AI-generated watermarks and metadata from images before republishing to internal systems
Trust Signals Auto-scanned
Community Pulse New
No community discussions found yet. This doesn't mean the tool isn't good — it may be new or serve a niche use case.
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 17,186 GitHub stars; contributors unknown; last commit 0d ago; license MIT.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
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Evaluation
Scored from trust signals (evidence-eval-v1): 17,186 GitHub stars; contributors unknown; last commit 0d ago; license MIT.