watermarks-remover

watermarks-remover strips AI provenance marks: invisible Unicode in text, and C2PA, EXIF and XMP metadata from images, PDFs, Office files, audio and video. Optional add-ons go after the statistical watermarks hidden in AI text and pixels, including SynthID-class marks. Visible stock-photo watermarks are untouched. It ships as an agent skill and Claude Code plugin over a local Python service, MIT licensed and free.

The core is easy: make serve or Docker Compose, and the skill calls it over HTTP. A hook can check every file your agent writes. The add-ons are not: text rewriting needs an LLM backend, and pixel removal wants a GPU and about 10GB of models from an upstream repo with no license file.

There's no paid tier. Solo and small teams: free, and the metadata cleanup is useful hygiene. Larger teams: free, but get legal sign-off before anyone runs the removal add-ons.

The catch: this grew from hygiene into attacks. v0.7.0 added a watermark-stealing module, audio and video watermark removal, and its rewrite benchmark scores human-likeness with Pangram, a commercial AI-text detector. Its own ethics page rules out passing AI text off as human. China bans tools that help others maliciously strip AI labels.