AI Content Detector
Get an authorship-style (AI-likeness) signal to help prioritize review. The AI Content Detector analyzes statistical and stylistic writing patterns and summarizes them into a score, confidence, and risk level. It’s designed for editorial and moderation workflows: use it to decide what to review next, then confirm with context (draft history, sources, or author process) before making decisions.
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About
This tool estimates AI-likeness based on writing patterns. It’s meant to speed up review, not to make final determinations about authorship.
How it works
Paste text and run the check. The tool analyzes writing features and produces a score and risk level with a short explanation of which signals contributed.
- Analyzes style/pattern signals
- Summarizes into score + confidence
- Explains which signals were used
Result interpretation
Higher scores suggest more AI-like patterns. Confidence reflects how consistently signals align. Longer samples typically produce more stable signals than short or highly templated text.
Use cases
Use it to triage content for manual review, especially when you have multiple samples or a known baseline writing style.
- Moderation triage
- Editorial review
- Policy compliance workflows
Limitations
Like any detector, results can be wrong in both directions. Treat outputs as a prioritization signal and follow up with manual checks when the stakes are high.
Best practices
Use longer samples, compare across drafts, and avoid making decisions based on a single score. When in doubt, request source material or revisions.
Related reading
FAQ
Can this reliably detect AI writing?
How do I reduce false positives?
Integrity and privacy
- Designed for review support, not for certainty claims about authorship.
- Pair outputs with context (draft history, sources, author process) for high-stakes decisions.
- Inputs are sent to the API to compute results. Avoid pasting sensitive personal data.
- For best accuracy, avoid very short samples that can mislead.