A Yi humanizer for reference-entry structure

Yi tends to answer even simple, conversational questions the way a glossary or an encyclopedia would: a dictionary-style opener, a formal taxonomy imposed on a simple idea, definitions nested inside definitions. This tool targets that specific structural habit, distinct from the essay-style scaffolding other models default to.

The rewrite happens server-side, since loosening a rigid taxonomy into natural explanation takes a language model of its own. The allowance is 5 free runs per rolling 24-hour window, with no account required and no upgrade path attached.

These recur across Yi output with unusual consistency, and every one traces to formal reference and dictionary convention.

Dictionary-first openers

"X refers to..." or "X can be understood as..." starting an answer the way a reference entry starts, even for a casual question that wanted a quick answer.

Over-categorised taxonomies

A simple two-part distinction broken into four or five formally labelled categories, imposing more structure than the underlying idea has.

A formal register throughout

The same measured, encyclopedic tone applied whether the question was technical or an offhand one.

Sub-definitions inside definitions

A term defined, and then a term inside that definition also formally defined, nesting explanation past the point a reader needed it.

Exhaustive enumeration

A question with one clear answer receiving a list of every conceivable related consideration instead of the direct answer itself.

The process is short by design: three steps, no configuration.

Step 1

Paste the Yi-drafted text: an email, a paragraph, a full section of a document.

Step 2

Run it. The text is sent to our AI server, rewritten, and returned within a few seconds.

Step 3

Review the result against the source, then copy it. The interface shows how many of your 5 runs remain in the current window.

The rewrite operates directly on the patterns above: it converts dictionary-style openers into a natural first sentence, collapses an over-categorised taxonomy back to the distinction it actually needed, and cuts nested sub-definitions and exhaustive lists down to a direct answer.

It does not add, remove or reinterpret facts. Names, figures, quotations and the sequence of your points are preserved; only definitional structure moves. Reviewing the output against the source before publishing remains the user's responsibility.

Yi trains on a large bilingual mix of English and Chinese material, with a strong emphasis on formal, well-structured reference and educational content in its tuning. That background rewards precision through categorisation, a habit that reads as thorough in a formal reference work and as over-engineered in a quick, casual answer.

None of this makes the underlying explanation wrong. It is a structural habit, defining before explaining, categorising before answering, that a formal reference audience expects and that a casual reader finds slower to get through than the question required.

No, and we state that plainly. We do not test this tool against AI-detection services, we do not tune its output against any detector's scoring, and we make no claim about what a detector will report after a rewrite. Detector methods are not public and are not something we can reliably predict.

The rewrite's honest, verifiable effect is structural: dictionary-style definitions and over-categorised taxonomies loosened into natural explanation. That improvement holds on its own merits. Treat any product, ours or a competitor's, that promises a guaranteed detector outcome as making a claim it cannot back.

Writers and technical teams use it on Yi's longer explanatory answers so a report or a document gives a direct answer instead of a formal taxonomy of every related concept.

Agencies run client copy through it before nested definitions ship where a quick, direct answer would have served better. Students use it to bring an AI-assisted draft back toward their own voice, governed entirely by their institution's own policy on AI-assisted writing tools, a policy this product does not set and cannot interpret on anyone's behalf.