ParseLess

ParseLess serves your WordPress content as clean Markdown to AI crawlers (via User-Agent detection) and on manual ?format=md requests. Same URL, same content, none of the theme chrome, navigation, widgets, or page-builder scaffolding that AI bots and CLI tools don’t need.

It also exposes /llms.txt for the emerging AI-indexing standard, so models know where to find your content.

Who is this for?

1. Developers using Claude Code, Cursor, Aider, or any CLI that feeds your own site content into an LLM.

If you’ve ever piped a blog post into Claude or ChatGPT for analysis, rewriting, or summarization, you’ve watched it burn through tokens parsing nav menus, footer markup, and CSS classes that have nothing to do with your content. A typical WordPress page measured live: ~19,800 tokens of HTML for ~975 tokens of actual content — a 20x reduction just by stripping the theme. Heavy page-builder sites (Elementor, Divi) routinely hit 100x or more.

That’s the difference between fitting a handful of pages in a context window and fitting dozens.

Just append ?format=md to any post URL and pipe it straight into your tool of choice:

curl https://yoursite.com/my-post/?format=md | claude "summarize this"

2. Site owners getting “high resource usage” warnings from their host because AI bots are hammering the site.

GPTBot, ClaudeBot, PerplexityBot, Google-Extended, and a dozen others crawl WordPress sites constantly. Each request renders your full theme, runs widget queries, loads page-builder assets, and ships hundreds of KB of HTML per page — most of which the bot discards before extracting the actual text.

ParseLess intercepts these crawls and serves a tiny Markdown payload instead. You keep the AEO/SEO benefit of being indexed by AI search, without paying the server cost of rendering your full theme for every bot hit.

Typical impact on AI bot traffic (measured on real WordPress pages):

• 95%+ less bandwidth per crawled page (typically 15–30x smaller; e.g. a 79 KB page → 4 KB. Heavy page-builder sites see 100x+)
• ~60–80% fewer database queries per request
• ~60% lower peak PHP memory per request
• ~50–80% faster Time To First Byte (measured 54% on a content-heavy page, 67% on a short one)
• On a site with 500 posts crawled monthly by major AI bots, that’s roughly gigabytes → tens of megabytes of monthly bandwidth and a fraction of the cumulative PHP execution time

Numbers vary by theme and content. Heavier setups (Elementor, Divi, Avada) see the biggest savings; lightweight themes see less dramatic but still meaningful gains. The conversion is cached as a transient, so repeated bot hits cost almost nothing.

How it works

• AI crawlers are detected by User-Agent and served Markdown automatically — no configuration required.
• Humans, search engines, and unknown bots receive your normal HTML output. ParseLess never affects what real visitors see.
• The ?format=md query parameter works on any post URL for manual preview or CLI piping.
• /llms.txt is published at your site root with a list of available content for AI indexers.
• Conversion happens once per post and is cached. Subsequent requests serve a single transient read.

Features

• Automatic Markdown for known AI bots (GPTBot, ClaudeBot, PerplexityBot, OAI-SearchBot, CCBot, Google-Extended, Applebot-Extended, Bytespider, Meta-ExternalAgent, cohere-ai, and more)
• Manual preview and CLI access via ?format=md on any post URL
• /llms.txt endpoint for AI-indexing standards
• Respects noindex flags from Yoast SEO, Rank Math, and Genesis
• Skips private, draft, password-protected, and trashed posts
• Works with all public post types (configurable)
• Optional YAML frontmatter (title, URL, author, date, categories, tags, excerpt)
• Transient-based caching with configurable TTL
• Settings page at Tools → ParseLess for detection mode, bot list, cache TTL, post types, and llms.txt control
• Per-post meta box with Markdown preview and copy-to-clipboard
• Extensible via filters: md4ai_bot_list, md4ai_supported_post_types, md4ai_markdown_output, md4ai_cache_ttl, md4ai_should_serve_markdown