Make content easy for LLMs to parse

SkillSearch

llm-parsability is a skill for auditing content pages for AI discoverability. It lets an agent check whether informational pages are written so AI assistants can find, extract, and cite them in generated answers and search snippets. Use it when reviewing any page intended to appear in AI-generated answers or knowledge base extraction.

Available today. Use it from your connected AI after setup.

Have an AI agent set up that can load skills.

Then ask your AI: use the Make content easy for LLMs to parse skill

What your AI can do with it

  • Audit content pages for AI discoverability
  • Check whether pages can be found and cited by AI assistants
  • Evaluate pages intended for AI-generated answers
  • Assess suitability for search snippets
  • Review pages targeted at knowledge base extraction

Getting started

  1. Have an AI agent set up that can load skills.
  2. Add the llm-parsability skill to the agent's available skills.
  3. Give the agent the URL or content of a page you want audited.
  4. Ask the agent to check the page for AI discoverability and report the findings.

What this skill tells your AI

The instructions your AI receives, as published by thedaviddias/front-end-checklist in skills/llm-parsability/SKILL.md and read by ahel’s review.

AI assistants and answer engines (including Google's AI Overviews) extract and cite content from web pages—pages with clear structure and explicit context are more likely to be accurately cited and surfaced in AI-generated responses.

Quick Reference

  • Use semantic HTML headings, paragraphs, and lists — LLMs prefer structured markup
  • Avoid content locked behind JavaScript rendering or requiring user interaction
  • Write clear, self-contained sections that make sense out of full-page context
  • Structured data (JSON-LD) provides machine-readable context alongside human-readable text

Check

Evaluate whether the page content is parseable by an LLM. Check: (1) Is content in semantic HTML tags (–, , , , )? (2) Is key content accessible without JavaScript? (3) Are section headings descriptive enough to stand alone? (4) Does the page have JSON-LD structured data? (5) Are there FAQ sections or explicit Q&A patterns that match common search queries?

Fix

Restructure content into explicit HTML sections with descriptive headings. Replace JavaScript-rendered content with server-side rendered HTML. Add JSON-LD schema (Article, FAQPage, HowTo) to annotate the content type. Write headings and lead sentences that work as standalone answers—assume the reader only sees one paragraph.

Explain

Large language models and answer engines process web content by extracting text from HTML. Pages that use semantic markup, clear headings, and server-rendered content are parsed more accurately than JavaScript-heavy or visually-structured pages. As AI-generated answers increasingly cite specific web sources, well-structured content is more likely to be accurately quoted and linked.

Code Review

Check the page's rendered HTML for: (1) proper heading hierarchy (h1→h2→h3), (2) content wrapped in semantic elements (, , ), (3) key content visible in initial HTML response (not injected by JS), (4) presence of FAQPage, HowTo, or Article JSON-LD schema, (5) absence of content hidden behind modals, tabs, or accordions that require JS interaction.


For full implementation details, code examples, and framework-specific guidance, see references/rule.md.

Rule page: https://frontendchecklist.io/en/rules/seo/llm-parsability

Signals

GitHub stars
74k
Forks
7k
Last commit
Aug 2026

Questions

When should this skill be used?
When auditing content pages for AI discoverability, any informational page intended to appear in AI-generated answers, search snippets, or knowledge base extraction.
What kinds of pages does it apply to?
Any informational page meant to show up in AI-generated answers, search snippets, or knowledge base extraction.
What does the skill actually do?
It lets your agent check whether web pages are written so AI assistants can find and cite them.
Advanced
Item type
skill
Key
llm-parsability
Source
github.com/thedaviddias/front-end-checklist