Feature Request
Feature Request
If there is a missing feature that would make your rewrite workflow better, send it to us with as much context as possible.
Quick signals
- best for: users who know what control or workflow step is missing
- strongest value: helping the team prioritize features that solve repeated problems
- biggest mistake to avoid: requesting a feature without the use case that makes it matter
What helps us evaluate requests
- what type of text you work with
- where the current workflow breaks down
- what outcome you wanted instead
- whether this is a one-off need or a repeated pattern
What makes a request stronger
- the exact task you were trying to do
- the missing control or capability
- why the current workaround is not enough
- how often this issue appears
Send requests
Best next step
If the missing feature blocks a real workflow, send one concrete example with the text type, the failed step, and the control you expected to have.
Related Pages
Continue with more specific use cases and keyword pages.
Understand what AI detectors can and cannot tell you before you rely on them for review.
Learn when plagiarism checks help and why originality still needs human review.
Use grammar checks to clean up final drafts after rewriting for tone and clarity.
A practical essay workflow starts with a draft, then moves into revision, structure checks, and final review.
Rewrite college drafts into clearer, more natural language while keeping final review in human hands.
A professor-facing workflow should focus on readability, transparency, and review standards.
These pages belong to the review layer, not the hype layer
On trust pages, the real test is whether standards, limits, and human responsibility are clear, not whether the promises sound bigger.
1
Start with the trust hub
Put detector, plagiarism, grammar, and ethics back into one review layer.
2
Read boundaries and feedback pages
Continue into ethics, reviews, issue-report, and feature-request pages.
3
Return to the product
Use a real draft to judge whether the workflow feels credible in practice.
Trust layer
These pages work best when the boundaries are explicit
Detector, plagiarism, grammar, and ethics pages should clarify standards and limits. That builds trust better than inflated promises ever will.
Trust Review
Start with the trust-layer hub before branching into detector, ethics, feedback, and issue pages.
Ethics Statement
See the product boundaries and the claims we intentionally avoid making.
Reviews & Feedback
Specific feedback is part of how the product earns credibility over time.
Feature Request
If your concern is workflow quality, this is the clearest product-feedback path.
Try the AI Humanizer tool
If you are reading one of these keyword pages, the fastest next step is to paste in your own AI draft and generate a more natural version.