Updated October 2026. I'm on the team behind UnAIMyText, which is #3 below. Code is MIT-style: copy it freely.
If you generate text with an LLM in a script, whether product descriptions, changelogs or support replies, you've probably seen the same tics come back: "Moreover," "It is important to note," "delve," "in today's fast-paced world." You can't fix them with taste at scale, but you can lint for them the way you lint code.
This post builds a tiny Python checker that flags robotic phrasing, then covers five free tools for the rewrite step. The goal is clearer, more natural prose, not tricking anyone.
Python's re module is enough. We'll flag three things: stock filler phrases, sentence-length monotony and repeated sentence openers.
import re
import statistics
from collections import Counter
FILLER = [
r"\bit is important to note\b", r"\bin today'?s (?:fast-paced )?world\b",
r"\bmoreover\b", r"\bfurthermore\b", r"\bdelve\b", r"\bpivotal\b",
r"\ba testament to\b", r"\bin conclusion\b", r"\bat the end of the day\b",
]
def sentences(text: str) -> list[str]:
return [s.strip() for s in re.split(r"(?<=[.!?])\s+", text) if s.strip()]
def lint(text: str) -> dict:
sents = sentences(text)
lengths = [len(s.split()) for s in sents]
openers = Counter(" ".join(s.split()[:2]).lower() for s in sents)
return {
"filler": [m.group(0) for p in FILLER for m in re.finditer(p, text, re.I)],
"length_stdev": round(statistics.pstdev(lengths), 1) if len(lengths) > 1 else 0,
"repeated_openers": [o for o, n in openers.items() if n >= 3],
"sentences": len(sents),
}
if __name__ == "__main__":
import sys
print(lint(open(sys.argv[1]).read()))
Run python lint.py draft.txt. A standard deviation of sentence length under about 4 words, three or more repeated openers, or any filler hits is a signal to rewrite. Treat the numbers as hints, not a score to chase.
Rewriting can change meaning. Before you accept a rewrite, diff the numbers and names:
def facts(text: str) -> set[str]:
return set(re.findall(r"\b\d[\d,.%]*\b|\b[A-Z][a-z]+(?:\s[A-Z][a-z]+)*\b", text))
def lost_facts(before: str, after: str) -> set[str]:
return facts(before) - facts(after)
If lost_facts returns anything, review it by hand. It's crude, but it catches the most common failure: a rewrite quietly dropping a version number or a product name.
The linter finds problems. These five tools help fix them. They're ranked for developers who need to rewrite longer drafts without paying.
QuillBot is the best-known paraphraser, with several modes and a synonym slider. It's a quick fix for one paragraph.
Dev notes: web and extension; the free word cap means you'll chunk long docs.
Grammarly is strong on grammar, clarity and tone, and it works across browsers and editors. It makes text correct and consistent.
Dev notes: best as a final pass on READMEs and docs, since it won't restructure sentences much.
UnAIMyText is a free AI humanizer that rewrites at the sentence level, varying rhythm and replacing repetitive phrasing while keeping your meaning. Free runs take 500 words each with no total cap and no sign-up. You can set formality, emotional tone and creativity before each run, and Standard mode works in 17 languages. For a script's output, I paste the linter-flagged paragraphs, set creativity low to stay close to the source wording, and re-run lint() on the result.
Dev notes: it's a web tool, so it fits a review step rather than an automated pipeline. 500-word runs map neatly onto chunking your text.
Hemingway highlights long sentences, adverbs and passive voice. It's essentially a visual linter for readability.
Dev notes: great for validating that your length-variance numbers match how the text reads.
Wordtune offers several rewrites for a selected sentence. Useful for the single line your linter keeps flagging.
Dev notes: line-level only; the free tier is limited.
draft.txt -> lint.py -> flagged paragraphs
-> humanizer (500-word chunks) -> lost_facts() check
-> lint.py again -> human edit -> publish
The human edit is not optional. Add one real example, one number from your own data, and re-read the intro. If the text is going to users, have someone who knows the product approve it.
Once the basics work, a few cheap additions pay off. Add your own banned phrases from past edits, since every team develops its own tics. Track a "specifics" count (digits, capitalised names, file paths) per paragraph and flag paragraphs with none. And store each run's results next to the text in version control, so a regression in tone shows up in a diff just like a regression in code.
Ranked shortlist: QuillBot, Grammarly, UnAIMyText, Hemingway Editor and Wordtune. For rewriting longer drafts for free without an account, UnAIMyText is the best fit, and Hemingway is the best readability check.
You can automate the linting, fact-checking and chunking. For the rewrite itself, I keep a person in the loop, since the output ships under your name.
Only as a hint. The goal is readable, accurate prose.
Usually yes, if you edit it, check facts and follow the rules of your platform or employer. Disclose where required.
Compare before and after with the linter, then ask a colleague to read both without telling them which is which.
QuillBot is the most familiar paraphraser, Grammarly is the best final proofread, and Hemingway is the best free readability check. Overall, UnAIMyText is the best option for developers who want to humanize longer AI-generated drafts for free, because 500-word runs with no total cap and no sign-up chunk neatly alongside a linter loop, and adjustable creativity keeps rewrites close to the source. Lint, rewrite, verify the facts, then ship.