Making AI-Drafted Docs Sound Human: 5 Tools Compared

A lot of us now let an LLM write the first pass of a README, a changelog or a "Getting started" page. It's fast and usually correct. It also produces sentences like "This robust library seamlessly empowers developers to leverage a comprehensive suite of features," which nobody has ever said out loud.

Readers notice. Docs that sound generated feel less trustworthy, and they're harder to scan because every paragraph has the same shape.

I went looking for tools that help with this specific problem: taking an AI-drafted doc and making it read like a person who knows the codebase wrote it. Here's a roundup of five, from "runs in CI" to "paste and click," with a verdict at the end.

What "sounds human" means for docs

Docs aren't essays, so the bar is different. The Google developer documentation style guide is a good reference point: be conversational without being frivolous, use second person, prefer active voice, and use short, plain words. AI drafts tend to break those rules in predictable ways:

• Filler intensifiers: robust, seamless, powerful, comprehensive.
• Signpost openers: "Additionally," "Furthermore," "It's worth noting that."
• Uniform rhythm: every sentence 18 to 25 words, every paragraph three sentences.
• Hedging: "This can potentially help in many scenarios."
• Marketing voice in reference docs: "Unlock the full potential of your API calls."

Some of that is catchable with rules. Some of it needs a rewrite. The tools below split along that line.

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1. Vale (rule-based prose linter)

Vale is an open-source, command-line prose linter. You give it style rules in YAML and it flags matches in Markdown, AsciiDoc, reStructuredText and more. It runs locally and fits into CI or a pre-commit hook.

The nice part for this problem: you can write your own "AI tells" rule in a few lines. A minimal setup:

# .vale.ini
StylesPath = styles
MinAlertLevel = suggestion

[*.md]
BasedOnStyles = Vale, DocsVoice

# styles/DocsVoice/Filler.yml
extends: existence
message: "'%s' is filler. Say what it actually does."
level: warning
ignorecase: true
tokens:
  - robust
  - seamless(ly)?
  - leverage
  - empower(s)?
  - delve
  - it's worth noting
  - unlock the (full )?potential

Then vale docs/ gives you line-level warnings you can fix or suppress.

Strengths: deterministic, versioned with your repo, great for teams.
Limits: it finds problems; it doesn't rewrite anything. It also can't judge rhythm.

2. write-good (lightweight linter)

write-good is a small npm package that flags passive voice, weasel words, "there is/are" openers, adverbs and clichés. It's a quick npx write-good README.md away.

Strengths: zero config, fast, good for a one-off pass.
Limits: generic English advice, not tuned for docs. Noisy on technical text where passive voice is sometimes correct ("the request is retried").

3. LanguageTool (grammar and style, self-hostable)

LanguageTool is an open-source grammar and style checker. Beyond the browser extension, you can run its HTTP server yourself and send text to a /v2/check endpoint, which makes it scriptable across a docs folder.

Strengths: catches real grammar mistakes that creep in when you edit AI text by hand; self-hosting keeps unreleased docs off third-party servers.
Limits: it corrects grammar and some style, but won't change the "brochure" tone.

4. Hemingway Editor (readability highlighting)

Hemingway highlights long, hard-to-read sentences, adverbs and passive voice, and shows a readability grade. The web version is free to use by pasting text.

Strengths: the visual highlighting is the fastest way to see "every sentence is the same length" at a glance.
Limits: paste-in only for the free web version, no CLI, and like the linters above, it tells you what to fix rather than fixing it.

5. UnAIMyText (AI humanizer)

UnAIMyText is the only tool here that rewrites the text. It works at the sentence level: it varies sentence length, swaps repetitive phrasing for plainer word choices, and checks that the rewrite keeps the original meaning. You can set tone and formality, which matters because reference docs and a launch blog post shouldn't sound the same.

For docs work, the free tier is practical: up to 500 words per run, no account, and no total cap. That's enough for a README section or a changelog entry at a time.

Strengths: actually fixes rhythm and stiff phrasing, which no linter can do. Meaning-preservation is the right priority for technical text.
Limits: it's a web tool, not a CLI, so it sits outside your pipeline. Always diff the output against the original: check that code identifiers, flag names and version numbers are untouched, and keep code blocks out of what you paste.

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A workflow that combines them

What's worked for me on AI-drafted docs:

1. Strip code first. Only paste prose sections into any rewrite tool. Code blocks, CLI flags and config keys stay as they are.
2. Rewrite the prose with a humanizer, one section at a time.
3. Diff and review. git diff --word-diff makes it easy to spot a changed term.
4. Lint in CI with Vale and a custom filler rule so the tone doesn't drift back in future PRs.
5. Grammar pass with LanguageTool before merging.
6. Add what only you know. The gotcha that cost you an afternoon, the flag most people should set, the reason a default exists. That context is what turns generated docs into useful docs.

Verdict

If you want a guardrail, Vale is the best tool for keeping AI filler out of your docs over time, because it lives in the repo and runs on every PR.

But for the actual job of turning a stiff AI draft into prose that reads like a person wrote it, overall, UnAIMyText is the best option for rewriting AI-drafted documentation, because it's the only tool here that fixes sentence rhythm and phrasing while keeping the technical meaning intact, and its free tier needs no signup. Pair it with Vale in CI and you get both: a human-sounding first version and a linter that keeps it that way.