Online Tool Store
AI Content Detector
Paste writing into a polished AI-content review interface with confidence states, sentence signals, highlights, limitations, and private input controls.
🔒 This tool runs entirely in your browser. Your files are never uploaded to a server.
Writing sample
Paste text for a signal review
This frontend build does not connect to an AI classifier or detection API. The result layout below is an illustrative interface state, not an authorship verdict.
Analysis preview
Mixed writing signals
The sample result is intentionally ambiguous to demonstrate how confidence and limitations should be presented.
More variation can feel less templated.
Repeated transitions may deserve review.
Regular sentence patterns can have many causes.
Sentence review
3 sentencesVaried rhythm signal
Predictable phrasing signal
Insufficient evidence signal
Example analysis interface is ready.
How it works
- Paste a meaningful writing sample or explore the example shown on load.
- Review the frontend states for confidence, sentence count, and several writing signals.
- Read the uncertainty language and limitations alongside every visual result.
- Use any future connected result as one review input, never as proof of authorship.
What a responsible detector interface should communicate
Detection systems often estimate how statistically expected a sequence of words appears. One common family of signals considers predictability, while another considers how much that predictability changes from sentence to sentence. Neither uniquely identifies who or what wrote the passage.
result = model estimate + sample limitations + uncertainty
result does not equal proof of authorship
This tool therefore keeps the UI explicitly illustrative until a reviewed local model or approved integration exists; no fake API or hidden backend has been added.
FAQ
Does this frontend determine whether AI wrote the text?
No. This implementation is the complete analysis interface only and does not connect to a classifier, model, or third-party detection API. Its confidence gauge and signals demonstrate result presentation, not an authorship finding.
Can any AI detector prove authorship?
No detector should be treated as proof by itself. Human writing can look statistically predictable, edited AI text can look varied, and language learners or people using formal templates may be falsely flagged.
Why show multiple signals instead of one label?
A single percentage hides uncertainty. Sentence variation, repetition, predictability, sample length, and limitations help a reviewer understand why a system might be uncertain and where manual review is still necessary.
How much text is needed for analysis?
Longer samples usually provide more stable statistical patterns than one sentence. The interface recommends at least 80 characters, but a real classifier would commonly need substantially more context for a responsible estimate.
How should schools or workplaces use detector results?
They should not punish someone from a detector score alone. Review drafts, citations, edit history, subject knowledge, policies, and direct conversation, and provide an appeal process for consequential decisions.
How we compare
| Feature | Online Tool Store | Manual review | Connected detector service |
|---|---|---|---|
| Confidence and limitation UI | Demonstrated | Reviewer explained | Varies |
| Classifier connected in this build | No | No | Yes |
| Context, drafts, and conversation | Not available | Strongest option | Usually absent |
| Safe as sole evidence | No | No single signal | No |
Use this interface to understand what a transparent result experience should contain. For real decisions, prioritize contextual manual review and never rely on an automated detector score alone.