In brief
Anthropic has announced plans to let users and third parties detect supported Claude marks. It has not yet published the technical method required for a reliable independent detector.
Detection is a provenance signal with limits: a positive result would not prove complete authorship, and a negative result would not prove that a person wrote the text without AI assistance.
What Anthropic has announced
Anthropic says it will support detection of two types of Claude marking: watermarks embedded in generated text and signed provenance metadata attached to supported files.
Its public documentation describes the purpose and broad interpretation of detection, then states that details of the mechanisms will be shared in forthcoming technical documentation.
How detection is expected to be used
Based on Anthropic’s published description, detection checks whether text or a file carries a supported Claude mark. The intended use is to provide context about whether Claude may have processed content.
The implementation should not be guessed. Anthropic has not disclosed the signal representation, detector algorithm, confidence model, passage-length requirement, or public interface.
What a positive result could mean
Anthropic says finding a supported mark indicates that content may have been processed by Claude. That includes generation as well as tasks such as proofreading, translation, summarization, and file conversion.
A positive signal is not fully conclusive about original authorship. Human-originated material can pass through Claude, and marked output can be changed after processing.
What a negative result could mean
A negative result would mean that a detector did not find a supported mark in the supplied sample. It would not establish that the content is human-authored or that Claude never processed it.
The model may predate marking support, the platform or feature may not support that mark, or the text may have changed too much to retain a detectable signal.
Editing and detection limitations
Anthropic says some editing may preserve a text watermark, while heavy editing, paraphrasing, translation, or mixing with other writing may prevent detection. Very short passages may also provide too little information.
For files, provenance metadata can be stripped by format conversion, re-saving, screenshots, or other operations. Text and file detection therefore have different failure modes.
Current detector status
As of this page’s August 11, 2026 review, Anthropic’s cited documentation says detection guidance is forthcoming. This site therefore offers no positive, negative, percentage, or confidence result.
The Claude Watermark Checker page reports this status directly. It does not reinterpret generic AI-writing patterns as an official watermark.
Technical updates
This section will be revised when Anthropic publishes material that can be independently reviewed and implemented. Any update must identify the source, document result semantics, preserve user privacy, and include tests for known limitations.
Last reviewed: August 11, 2026. Current status: not yet publicly documented.