Llama passive voice fixer

Llama passive voice fixer

What the Llama passive voice fixer does

Drop in text drafted with a Llama-based model and the app checks for inconsistent passive voice usage across the document, where one paragraph reads heavily passive and another reads blunt and active, because different sections may trace back to different fine-tunes or sampling settings. It fixes the inconsistency and leaves correctly used passive voice alone.

It's a server tool, your text is sent to our AI server to be analyzed rather than processed on your device. You get 5 free runs every rolling 24 hours, no account needed.

The problem

Why passive usage varies within a single Llama-drafted document

Because Llama is open-weight, a document assembled from more than one session, or produced by a deployment that shifted behavior across a long generation, can carry two different defaults: one part heavily hedged and passive, in the style some instruction-tuned fine-tunes lean toward, and another part blunt and active, produced by a differently tuned or differently sampled pass.

Neither default is wrong alone. The problem is having both in the same document without a reason, which reads as inconsistent rather than a deliberate stylistic choice. The actual issue is narrower: agentless passive that drops responsibility, and passive used inconsistently rather than by any real editorial choice.

How it works

How to fix passive voice in Llama text in three steps

Three steps, nothing to configure first.

Step 1

Paste the Llama draft into the box, whole document or a section at a time.

Step 2

Hit Fix. The text goes to our AI server, which finds passive constructions and evens out inconsistent usage across the passage.

Step 3

Check the result against your original. Sentences where passive voice is the right choice for the context are left exactly as they were.

Scope

What gets rewritten, and what stays exactly as you wrote it

The app brings the whole document to one consistent standard for passive voice, correcting agentless passive that dodges attribution along the way. A document that shifts between hedged, passive prose and blunt, active statements reads as though two different people wrote it, even when every fact in it is correct.

It doesn't add or remove facts, and it doesn't reorder your points. Check the result against your draft before you use it anywhere that matters, especially wherever the surrounding paragraphs were confidently active.

The actual test

When passive voice is the right call, regardless of which fine-tune wrote it

Passive voice is correct when the agent is unknown, irrelevant, or the result matters more than who caused it. Scientific writing leans on it for exactly this reason.

The failure mode isn't passive voice itself, it's agentless passive dodging a responsible party, and inconsistency that tracks which part of the pipeline wrote which paragraph rather than any actual editorial reasoning.

Straight answer

Does this make Llama text undetectable?

No, and fixing consistency was never going to do that alone. We don't test this app against AI detectors and don't tune it to beat any of them, so we have no basis to promise what a detector would conclude.

What it does reliably do is bring one document to one consistent standard, correcting agentless passive along the way, which is a real improvement in how the writing reads independent of any claim about detection.

In practice

Who runs Llama text through this, and why

Developers and hobbyists running local Llama-based models who noticed a document reads inconsistently after combining output from more than one session or fine-tune.

Writers and editors cleaning up a Llama-assisted draft who want one consistent standard applied throughout, rather than whatever each section happened to inherit from whichever pass wrote it.