Why Content Linting Matters: QA for the GenAI Era

Content QA in the Age of GenAI

"Looks good to me" isn't good enough anymore.

If you're using GenAI to help create content, you're not alone. Blog posts, landing pages, emails, even documentation — all of it is now being generated, edited, or improved by LLMs.

That's a huge win for speed.

But also? A massive risk for brand consistency, SEO integrity, and message accuracy.

And most marketing teams don't have the tools to keep up with the new volume. What’s worse, they rely on manual checks or subjective opinions before hitting publish.

That’s why MoMa includes something new in the modern GTM stack: A Linter. For Content.

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🧠 What is a Linter Anyway?

In software development, a linter is a tool that scans your code to catch errors before you push it live. Typos, style issues, unused variables — it flags them early, fast, and predictably.

We’ve borrowed that concept for marketing.

MoMa Linter scans your marketing content before publishing, making sure it aligns with:

• Your SEO strategy
• Your brand guidelines
• Your messaging tone and structure
• Channel-specific rules (a LinkedIn post ≠ a newsletter ≠ a blog)

It’s not a grammar checker. It’s a GTM quality gate.

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🧪 Why You Need a Linter Now (More Than Ever)

Let’s break down the key reasons why this matters in modern, AI-powered content workflows:

1. GenAI hallucinations are subtle and dangerous

GenAI tools are helpful — but sometimes confident and wrong. The MoMa Linter validates links, references, formatting, and tone to prevent embarrassing mistakes from slipping through.

2. SEO is compounding — don't let it drift

MoMa Linter cross-checks every piece of content with your live keywords.md file. That way, your target keywords are always enforced — and new ones can be added with ease.

3. Brand guidelines are hard to scale manually

Whether you're a startup or an enterprise, brand voice is sacred. With a linter, you don’t need every writer or agent to memorize your style guide. It’s enforced in code.

4. Channels behave differently — and your content should too

The linter supports channel-aware rules: things like hashtag length for LinkedIn, emoji usage in email, CTA placement in blog posts, and more.

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🛠 How MoMa Linter Works

Here’s the lifecycle of a blog post in a modern, version-controlled marketing stack:

1. A new feature goes live in your product

2. MoMa Agent detects the release and triggers a blog idea

3. A GenAI model drafts the blog

4. The content passes through the MoMa Linter, which checks:

   • Does it include one or more of the target keywords?
   • Are all links valid?
   • Does it match tone (as defined in brand.md)?
   • Are the H1/H2 structures optimized for SEO?
   • Is it channel-appropriate if it’s being repurposed?
   • Does the post length meet platform standards?

5. If approved, the post is dispatched via MoMa Dispatcher to your platforms.

6. If not, it fails CI and returns a clear log of what to fix.

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🧩 Built for Developers, Loved by Marketers

The linter runs in your CI/CD pipeline — just like a dev linter.

It’s written in TypeScript, supports GitHub Actions out of the box, and works locally too.

You can lint:

• Markdown (.md)
• HTML
• JSON (for structured content blocks)

And you can configure everything via a linter.config.yml.

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🔄 Why It Matters: From Gut Feeling to GTM Confidence

Most marketing teams are used to asking:

“Does this feel okay to post?”

But in the MoMa world — where releases are frequent, and content needs to match — we ask:

“Does this pass the test?”

That shift is subtle. But it changes everything.

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🚀 Wrapping Up

Linters for content might feel strange at first — but they're essential if you want to build scalable, automated GTM workflows.

GenAI will write more. MoMa Linter makes sure it's worth publishing.

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Read Part 3: The Stack