AI word finder

Where these phrases come from

A language model chooses each next word by likelihood. Words that fit almost any sentence are therefore the safest choices available, and they get picked far more often than a person would pick them. That is the whole mechanism.

"Moreover" fits after nearly any claim. "Landscape" attaches to any field. "It is important to note" can precede any sentence at all. Their flexibility is exactly what makes them empty — a word that fits everywhere tells the reader nothing about where they are.

Reinforcement training compounds it. Models tuned to be helpful and inoffensive learn to hedge, qualify and signpost, which is why the hedges below cluster so heavily in AI-assisted drafts. None of this makes the words defective. It makes their frequency a fingerprint.

The five categories, and what to do about each

Connective throat-clearing. Transitions that announce a turn the sentence was making anyway. Usually deletable with no loss.

Abstract stand-ins. Nouns that gesture at a subject without naming anything. Replace with the specific thing you meant.

Hedges and softeners. Phrases that lower the stakes of a claim until it says nothing. Either commit or cut the sentence.

Inflated verbs and adjectives. Words doing more work in the sentence than in reality. Swap for the plain equivalent.

Stock openers and closers. Sentences that exist to introduce or summarise other sentences. Start at the point instead.

The single highest-value edit is deletion. Most flagged connectives can be removed outright with no loss — the logical relationship they announce is usually already carried by the order of the sentences. Cutting is faster than substituting and reads better than both.

The order to edit in

Working through the results top to bottom is the slowest route. There is an order that removes more in less time, because the categories are not equally expensive to fix.

Delete the connectives first. They need no replacement and no thought — "moreover", "furthermore", "that being said" can almost always come out whole, and the sentences either side hold together without them. This is usually a third of the flags, cleared in a couple of minutes.

Then the stock openers and closers. Also deletions rather than substitutions. If a sentence exists to announce another sentence, cutting it moves the reader forward rather than losing anything.

Then the abstractions, which need decisions. Replacing "landscape" with the actual market, or "framework" with the actual method, requires you to know what you meant. This is the slow part and the part that improves the writing most, because a vague noun is usually hiding a vague thought.

Leave the hedges until last. Some are load-bearing. "Research suggests" is weak when it hides an unnamed study and correct when the evidence genuinely is suggestive. Removing hedges mechanically produces overconfident writing, which is a different failure and a worse one.

One pass in that order handles most drafts. Re-running the tool afterwards is worth doing — deletions frequently expose a second flagged phrase that the first one was hiding.

What this tool will not tell you

It will not tell you whether a detector will flag your text. Detection works on statistical properties of a whole document, not a word list, and clearing every term here will not reliably move a score. How detectors actually work explains the mechanism, and it is worth reading before trusting any tool that implies otherwise.

It also will not find the tells that matter most. Sentence length that never varies, paragraphs of near-identical weight, an argument that never meets an objection — these are stronger signals than vocabulary and no list of words detects them. For the first, the sentence rhythm tool shows the distribution directly. For repeated vocabulary beyond this list, the word frequency tool counts everything.

A draft with zero flagged terms can still read as machine-written, and a good essay can contain several of these words used deliberately. The count is a prompt to look, not a verdict.