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watermarks-remover
Agent skill + stdlib Python service to strip multi-vendor AI provenance marks from text and files — for privacy and hygiene on content you own. The skill is a thin client: it drives the machinery over HTTP, so the agent host needs no Python.
| Layer | Target | How |
|---|
| A | Invisible Unicode, exotic spaces, bidi, tag chars | Deterministic Python scripts |
| B | Statistical (token-sampling) text watermarks | Agent rewrite + optional rewrite_text.py hook |
| Files | C2PA / EXIF / XMP / doc props | PNG, JPEG, WebP, AVIF, HEIC, BMP, GIF, TIFF, SVG, PDF, DOCX, XLSX, PPTX, EPUB, ODT, HTML, Markdown, MP4/MOV/M4A/M4V, WAV, MP3, FLAC |
Vendors / ecosystems (class-level): Claude, Gemini / SynthID-Text, OpenAI provenance surfaces, open-LLM Kirchenbauer-style (green-list) and keyed-Gumbel / EXP (Aaronson) marks.
Latest release: v0.7.0
Skill path: skills/remove-ai-marks/
Service path: service/
(migration: formerly remove-claude-marks; slash alias /remove-claude-marks still documented)
Install (agent skill)
The skill ships no code — it calls the service over HTTP. Install the skill (markdown only) and start the service, then set WATERMARKS_SERVICE_URL if it is not http://127.0.0.1:8765.
In Claude Code, the fastest route is the bundled
plugin marketplace — no clone, and it updates
in place. Everywhere else, one installer covers every supported host
(Python 3.10+ stdlib, no dependencies):
python3 install_skill.py --skill remove-ai-marks --target claude-code
| Host | Target | Lands in |
|---|
| Claude Code (personal) | --target claude-code | ~/.claude/skills/<skill> (honors CLAUDE_CONFIG_DIR) |
| Claude Code (project) | --target claude-project --project-dir PATH | PATH/.claude/skills/<skill> |
| Codex (personal) | --target codex | ~/.agents/skills/<skill> |
| Codex (project) | --target codex-project --project-dir PATH | PATH/.agents/skills/<skill> |
| Cowork, claude.ai, cloud sessions, routines | --target cowork | dist/<skill>.zip to upload under Customize → Skills |
| Cursor | --target cursor (default) | ~/.cursor/skills/<skill> |
Shipped skills: remove-ai-marks (full, service-backed) and
clean-user-facing-text (text only, self-contained). --list prints them.
Existing installations are preserved unless you pass --force; replacement is
staged first and the previous install is kept as a uniquely named backup.
--link symlinks this checkout instead of copying, so edits are picked up
live. On Windows, use py install_skill.py ...; the install-skill.sh wrapper
is provided for macOS/Linux shells.
Before writing anything, the installer validates the skill against the
Agent Skills packaging rules that claude.ai uploads
and the Skills API enforce: spec-only frontmatter (name, description,
license, compatibility, metadata, allowed-tools), a lowercase hyphenated
name of at most 64 characters matching the directory, a non-empty
description of at most 1024 characters. The Cowork bundle additionally has
to fit the 30 MB upload limit, which the packager enforces.
Codex terminal and desktop
Install either shipped skill for your user, or install one into a particular
project:
python3 install_skill.py --skill remove-ai-marks --target codex
python3 install_skill.py --skill clean-user-facing-text --target codex
python3 install_skill.py --skill remove-ai-marks --target codex-project --project-dir /path/to/project
On Windows, use py in place of python3. Open the project in Codex. In the
terminal, use /skills or type $ to select a skill; in the desktop app,
select or mention the skill in your prompt. Restart Codex if the new skill does
not appear. The project install is available when Codex runs in that project.
For remove-ai-marks, start the existing HTTP service from this repository
with make serve before using the skill (or on Windows without make, run
py service/scripts/server.py --host 127.0.0.1 --port 8765). It uses
WATERMARKS_SERVICE_URL (default http://127.0.0.1:8765), checks /health,
and calls the existing /inspect and /clean endpoints. If the service
requires an API key, set WATERMARKS_SERVER_API_KEY for the client.
clean-user-facing-text is
self-contained and does not need the service.
Automatic cleaning via hook (deterministic)
A skill is an instruction: the model decides whether to invoke it, and the
model is the thing producing the marks. A hook is executed by the harness
on every matching tool call, cooperation not required. That makes the hook the
deterministic half of this workflow.
This is the beginning of the README. Read the rest at the original. Read the full README ↗
