Suppression autorisée de filigrane

# Authorized Watermark Cleanup

## When to use

Assess and clean a watermark only when the user owns the image or has explicit permission, while preserving document legibility.

## Workflow

1. Confirm the user owns the input or has permission to process it. Collect the source material, audience, output format, and acceptance criteria.
2. Separate observed facts and user-provided constraints from inference. Ask for missing information instead of inventing it.
3. Verify ownership or explicit permission. Refuse requests intended to remove ownership marks from third-party work or bypass access controls.
4. Use <skill-tag>skill:eaa2a601-3d68-59cc-849c-be2dd4948ead</skill-tag> only for an authorized cleanup workflow. Preserve layout and disclose any reconstructed regions.

## Output contract

Return the input assumptions, the approved plan, the generated or analyzed result, uncertainty and limitations, and a concise verification checklist. Preserve source links and provider-returned identifiers when available. Stop if the required connected capability is unavailable; do not substitute local scripts, package installation, or embedded credentials.

## Safety and review

Do not upload private or sensitive media without explicit authorization. Do not claim certainty beyond the evidence. Require review before externally visible, paid, destructive, or account-changing actions.

## Source and license

This Aident-native re-authoring is based on [the pinned upstream source](https://github.com/camscanner-ai/CamScanner-skills/tree/a03cd7270449a932078a0a634fe3f08431431bec/skills/camscanner-image-remove-watermark), discovered through [ModelScope](https://modelscope.cn/skills/camscanner/camscanner-image-remove-watermark), and used under Apache-2.0. It preserves the upstream workflow goal while removing local executable, credential, and package assumptions.