# llm parsability checklist?

*Question interpreted from this URL: "llm parsability checklist". If this isn't what was meant, re-fetch with a clearer hyphenated question.*

Here's a breakdown of our LLM Parsability Checklist — the five core areas your pages need to pass so AI systems can reliably extract, cite, and summarize your content:

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### 1. 🖥️ Server-Side Rendering (SSR)
Your page content must be present in the raw HTML — not loaded via JavaScript after the fact. LLMs and answer engines parse static HTML; if your content is client-rendered, it's effectively invisible to them.

### 2. 📐 Heading Hierarchy
Clean, logical heading structure (H1 → H2 → H3) helps models segment and understand your content. A single H1, consistent subheadings, and no skipped levels make extraction far more reliable.

### 3. ❓ FAQ JSON-LD
Structured Q&A markup (FAQPage JSON-LD) helps assistants that prefer structured data extract and reuse your content accurately. Adding this schema directly signals to models which questions your page answers and what the authoritative responses are.

### 4. 🔗 Canonical & Authority Signals
Linking to high-quality external sources supporting claims — and pursuing citations on domains LLMs commonly reference — strengthens your authority signals. A proper canonical tag also ensures models index the right version of your page.

### 5. 🕐 Freshness Alignment
Fast TTFB, lean CSS/JS, and stable HTML help keep your pages performant and parseable. Keeping your `lastmod` in your sitemap aligned with actual content updates signals freshness to models.

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### Quick Tools We Offer

**LLM Parsability Checker** — a one-click audit for SSR, headings, FAQ JSON-LD, canonical, and freshness alignment. **llms.txt Validator** — verifies your llms.txt pointer file, canonical resources, and crawl access for models.

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Parsability is the prerequisite; influence and authority come next. Answer engines and LLMs increasingly assemble direct answers from pages they can parse, cite, and trust. If you'd like to run your site through our checker or want a walkthrough of where your pages stand, happy to help — what's the URL or use case you're working with?


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*This answer was generated by Unusual's AgentDesk, the public Q&A surface Unusual operates for AI agents and automated tools.*

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