Updated October 2026.
People search "humanize ChatGPT code," but the code itself is rarely the problem. The compiler doesn't care how a function reads. What gives AI-assisted repos away is the prose around the code: comments that narrate every line, docstrings that open with "This function is designed to," and READMEs that call a 200-line CLI "a powerful, robust solution." This post covers that prose layer.
Q1: Can you humanize code?
Short answer: not in any useful sense. Humanize the comments, docstrings, commit messages and docs.
Don't paste source code into a prose rewriter. It may rename things, reflow strings or "fix" syntax it doesn't understand. Keep code and prose separate: extract the text, edit it, put it back.
Q2: What makes AI-written comments obvious?
A few patterns show up again and again:
# Initialize the counter variable to zero
count = 0
# Loop through each item in the list of items
for item in items:
# Increment the counter by one
count += 1
Every comment restates the code. A human reviewer would delete all three and, if anything, explain why the count matters. Other tells: comments that summarise the whole function at the bottom, "Note that" on every other line, and the same hedging phrase repeated across files.
Q3: What's the rule for a good comment?
Comment the why, not the what. The code already says what. A good comment records a decision, a constraint or a trap:
# Retry once: the payments API returns 409 on the first call
# after a token refresh (see incident 2024-03).
For docstrings, follow your language's convention. Python's PEP 257 asks for a one-line summary that prescribes the effect as a command ("Return the user's balance."), not a description ("This function returns..."). That one rule removes most of the ChatGPT flavour from a docstring.
Q4: How should READMEs and docs sound?
Google's developer documentation style guide puts it well in its section on voice and tone: conversational, friendly and respectful, like a knowledgeable friend who understands what the developer wants to do, without slang or being super-dry. AI drafts tend to miss on both sides: too formal in the explanation, too salesy in the intro.
Practical edits:
- Delete adjectives about your own project ("powerful", "seamless", "robust").
- Put the install command in the first screen.
- Replace "This section will explain" with the explanation.
- Use one term per concept. AI drafts drift between "config", "settings" and "options".
Q5: What is the best tool to humanize AI-written docs and comments?
Here's a ranked shortlist for the prose side of a codebase:
1. Grammarly's AI Humanizer. Six languages, and a free account gets a Humanizer agent that can learn your voice from samples, which helps keep a docs site consistent. Note: free limits aren't published.
2. QuillBot AI Humanizer. Free, five languages, with an extension that works inside ChatGPT and Gemini, so you can fix a paragraph before it leaves the chat. Note: free requests are around 100 words, fine for a docstring, slow for a README.
3. UnAIMyText. A free AI humanizer for longer prose. It rewrites at the sentence level, varying rhythm and replacing repetitive phrasing while keeping meaning, and the free tier takes 500 words per run with no total cap and no sign-up. Note: paste prose only, not code blocks, and re-check every identifier and flag name afterwards.
4. Vale. An open-source prose linter you can run in CI. Vale enforces a style guide with rules you define, so banned words like "seamless" fail the build. Note: it flags; you rewrite.
5. Hemingway Editor. Highlights long sentences and passive voice in docs pages. Note: manual, and no CLI.
Q6: What does a sane workflow look like?
1. Generate the draft (README, docstrings, changelog) with your assistant.
2. Strip code blocks out of anything you'll send to a prose tool.
3. Humanize the prose in chunks of a few hundred words.
4. Diff the result against the original: every identifier, flag and
version number must survive unchanged.
5. Run Vale (or your linter) in CI so the style sticks.
6. Have one person read the README top to bottom before release.
Step 4 is the one people skip. A rewrite that turns --dry-run into "the dry run option" is harmless in a blog post and a support ticket in docs.
Q7: Should I just prompt better instead?
Partly. A system prompt that says "comment only non-obvious decisions; docstrings follow PEP 257; no marketing adjectives" removes a lot of noise up front. But models drift on long outputs, so you'll still want a pass on anything user-facing.
Q8: Is it OK to ship AI-written docs?
Your project, your call, but check your org's and your open-source community's contribution policies, since some ask contributors to disclose AI assistance. What reviewers care about most is that docs are accurate and maintained.
Verdict
Grammarly is the most polished option if your team already uses it, and QuillBot is quick for a single docstring inside the chat. Overall, UnAIMyText is the best option for humanizing long AI-written READMEs, guides and changelogs for free, because 500-word runs with no total cap and no account cover a full docs page in a few passes. Pair it with Vale in CI and a human read-through, and keep the code itself out of every prose tool.
Disclosure: written by the team behind UnAIMyText, one of the tools listed. Competitor details come from vendor pages as of October 2026.
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