Explainable writing signals, reviewed locally
AI-Likelihood Writing Review
Inspect the patterns that can make a draft feel automated: unusually even sentence rhythm, repeated openings, recurring phrases, formulaic transitions, flat vocabulary, and limited punctuation range. The tool shows its evidence so an editor can improve the copy instead of trusting a black-box verdict.
Use a complete draft with several paragraphs. Short text, technical templates, translated copy, and highly edited brand language can produce unstable results.
Content quality
AI-Likelihood Writing Review
Review explainable rhythm, repetition, vocabulary, punctuation, and formulaic-language signals locally.
An editorial aid
Review the pattern, not the accusation
No text-only detector can reliably prove who or what wrote a passage. Models change, human writing varies, and editing can blur the patterns. This tool therefore reports an automated-style pattern likelihood, confidence based on sample coverage, and the evidence contributing to the score.
The signal table shows the measured risk, administrator-defined weight, contribution to the final result, and plain-language evidence. Editors can then decide whether the draft needs varied sentence structure, fewer repeated transitions, more concrete examples, a stronger point of view, or no change at all.
Signals in the local model
- Sentence-length and paragraph-length variation
- Repeated two-word sentence openings
- Repeated three-word phrases
- Transition phrase density
- Formulaic phrase density
- Lexical diversity and punctuation variety
Human editing loop
Turn flagged patterns into better copy
Run the complete draft
Paste the article or load a supported text-based file. A larger sample gives the engine more sentences and paragraphs to compare, but it still does not establish authorship.
Start with paragraph evidence
Open the highest-scoring segments and read them naturally. Look for repeated framing, identical sentence lengths, empty transitions, vague claims, and passages that say little despite using many words.
Edit for the reader
Add firsthand detail, specific examples, qualified opinions, useful comparisons, and a rhythm suited to the audience. Re-run the draft only to check the pattern changes, not to chase a perfect score.
Your editorial model
Adjust phrases, weights, and thresholds
WordPress administrators can set the minimum sample length, mixed and high-review thresholds, and the weight of every signal. Transition and formulaic phrase libraries are editable line by line, making the model adaptable to the wording your editors actually encounter.
Local, Copyscape, and hybrid modes are available. Local mode keeps text on the WordPress server. Provider modes require licensed credentials and a clear paid-check acknowledgement on the public form.
Use with care
A high likelihood can occur in human-written templates, academic summaries, technical instructions, second-language writing, and heavily standardized brand copy. A low likelihood can occur in edited AI-assisted text. The result should guide a conversation with the writer, never become an automatic rejection.
Complete the quality review
Check the draft from three angles
Responsible use
AI-likelihood review FAQs
Can this tool prove that AI wrote an article?
No. It measures selected writing patterns and reports a likelihood for editorial review. It cannot establish authorship.
Why does the tool require a longer sample?
Rhythm, repetition, and vocabulary measurements become less meaningful when there are too few sentences or paragraphs to compare.
What should I do with a high score?
Read the strongest contributing signals and paragraph segments. Ask whether the section is repetitive, vague, overly uniform, or missing concrete detail. Edit for readers rather than for the score.
Does local mode send my draft elsewhere?
No. Local mode runs on this WordPress server. External provider checks occur only when the administrator enables them and the user confirms the paid check.
Draft reviewed?
Send the article with your guest post brief
Use the order handoff to include the useful result details, then add the target page, topic, audience, preferred market, anchor direction, and publisher requirements.
We review content and publisher fit before confirming a placement.