onevteam

vslnk

One-V LLM Serve makes every public page on your WordPress site available as clean Markdown at the same URL with a <code>.md</code> extension — zero configuration required.
<pre><code>https://example.com/about/ ← HTML page for humans
https://example.com/about.md ← clean Markdown for AI
</code></pre>
AI systems — ChatGPT, Perplexity, ClaudeBot, Google AI Overviews, and most RAG pipelines — parse Markdown far more efficiently than HTML. When these systems encounter an HTML page, they must strip navigation, headers, footers, sidebars, scripts, and tracking pixels before they can read the actual content. This noise introduces errors, increases token cost, and leads to lower-quality outputs.
The Markdown file contains a configurable YAML frontmatter block followed by the page title, headings in correct hierarchy, and the body text. Nothing else.
<h4>Core features</h4>
<ul>
<li>Zero-config Markdown endpoint for every public post, page, and custom post type</li>
<li>YAML frontmatter with configurable fields (<code>title</code>, <code>date</code>, <code>modified</code>, <code>url</code>, <code>description</code>, <code>image</code>, <code>tags</code>, <code>categories</code>, <code>lang</code>, <code>type</code>)</li>
<li><code>/llms.txt</code> discovery file at the site root following the <a href="https://llmstxt.org" rel="nofollow ugc">llmstxt.org</a> convention</li>
<li>Taxonomy archives as Markdown — <code>/category/news.md</code>, <code>/tag/foo.md</code>, custom taxonomies</li>
<li><code>?format=markdown</code> query parameter as an alternative to the <code>.md</code> URL on any singular page</li>
<li>Per-post exclude via a sidebar checkbox on the post editor</li>
<li>Works with Classic Editor and Gutenberg via the <code>the_content</code> filter</li>
<li>ACF integration — opt-in per-post: pick which text, textarea, WYSIWYG, URL, email, or link fields to append below the body</li>
<li>Filterable AI analytics — per-hit events with full denormalised dimensions (UA bucket, referrer host, language, post type, response code), sticky filter bar that drives every chart and table live, six KPI tiles, a stacked-area time chart, three composition donuts (UA bucket / referrer source / language), four Top tables, a User-Agent classifier transparency table, and a Recent Activity stream. Referrers are tracked by hostname only — paths and query strings are stripped before storage so no PII is retained. Forward-compatible classification: when the bot or referrer catalogue is updated in a future release, historical rows are reclassified automatically — no Reset Analytics required.</li>
<li>Browser-bucket sub-classification — anything that looks like a browser visit gets split into four kinds based on the <code>Sec-Fetch-Site</code>, <code>Sec-Fetch-User</code>, and <code>Sec-CH-UA</code> request headers a real browser sends: verified user (top-level navigation triggered by a click or address-bar Enter in a recognised browser), headed agent (real Chromium driven programmatically — Playwright, Puppeteer, Selenium), script agent (bare HTTP client imitating a browser UA — <code>requests</code>, <code>httpx</code>, LangChain, custom agents), spoofer (UA shape that no real browser would emit, like modern Chrome with a non-reduced UA). Visible as a stacked-bar breakdown on the User-Agents subpage so you can see at a glance how much of your “human” traffic is actually automation, and rendered inline as colour-coded slugs on every browser-bucket row in the Recent Activity table on the Analytics page. Detection is server-side fingerprinting of the request itself — no cookies, no JS, no IP.</li>
</ul>
<h4>Discoverability</h4>
<ul>
<li><code>Link: rel="alternate"; type="text/markdown"</code> HTTP header on every HTML page</li>
<li><code><link rel="alternate"></code> tag in <code><head></code> for HTML-based discovery</li>
<li><code>Allow: /*.md$</code> directive in <code>robots.txt</code></li>
<li>CORS <code>Access-Control-Allow-Origin: *</code> on <code>.md</code> and <code>/llms.txt</code> so browser-based AI clients can fetch them</li>
</ul>
<h4>Operations</h4>
<ul>
<li>Transient caching with automatic invalidation on <code>save_post</code>, on ACF field value saves, on any ACF field group change, and on plugin settings save</li>
<li>“Clear cache” button in the settings page</li>
<li>Admin notice on fallback HTTP fetch failures</li>
<li>“Settings” link next to the plugin row in Plugins screen</li>
<li>“View .md” row action in the Posts and Pages list tables</li>
</ul>
<h4>Developer hooks</h4>
<ul>
<li><code>ovls_markdown</code> filter for the final Markdown output</li>
<li><code>ovls_frontmatter</code> filter for adding, removing, or modifying frontmatter fields</li>
<li><code>ovls_content_queries</code> filter for the HTML extraction XPath cascade</li>
</ul>
<h4>How it works</h4>
Each request to <code>/about.md</code> is captured by a WordPress rewrite rule and routed through the plugin’s content generator. The generator runs the post through <code>apply_filters( 'the_content', ... )</code> — the same pipeline WordPress uses on the front end — so Classic Editor, Gutenberg, and shortcodes all work without separate code paths. The rendered HTML is converted to Markdown via <code>league/html-to-markdown</code>, then cached in a WordPress transient.
The cache is invalidated automatically on <code>save_post</code>, on ACF field/group changes, and whenever plugin settings are saved. A manual Clear cache button is also available on the settings page.
<h4>Access methods</h4>
There are three equivalent ways to request the Markdown version of a page:
<ul>
<li><code>.md</code> extension — <code>https://example.com/about.md</code></li>
<li><code>?format=markdown</code> query — <code>https://example.com/about/?format=markdown</code></li>
<li><code>Link: rel="alternate"</code> header — returned by every HTML page</li>
</ul>
The <code>.md</code> URL is the recommended canonical form.
<h4>ACF integration</h4>
When <a href="https://www.advancedcustomfields.com/" rel="nofollow ugc">Advanced Custom Fields</a> is active, ACF field rendering is opt-in at two levels:
<ol>
<li>Site defaults per post type — at Settings → One-V LLM Serve → ACF Defaults, tick fields that should be appended to every post of a given post type.</li>
<li>Per-post override — the One-V LLM Serve metabox on each post editor lists every supported ACF field applicable to that post. Tick fields to replace the site defaults for that one post.</li>
</ol>
Supported ACF types: <code>text</code>, <code>textarea</code>, <code>wysiwyg</code>, <code>url</code>, <code>email</code>, <code>link</code>. Each selected field is rendered under a <code>## Field Label</code> heading. Empty fields are skipped.
<h3>Disclaimer</h3>
This plugin is provided “as is”, without warranty of any kind, express or implied, in accordance with the GNU General Public License v2 or later. The authors and contributors are not liable for any direct, indirect, incidental, special, or consequential damages — including but not limited to data loss, lost profits, business interruption, search-ranking changes, or third-party claims — arising from the use of, or inability to use, this software, even if advised of the possibility of such damages.
By installing and activating the plugin you acknowledge that:
<ul>
<li>You are responsible for testing the plugin in a staging environment before deploying to production.</li>
<li>You are responsible for the content this plugin exposes as Markdown — <code>.md</code> URLs and <code>/llms.txt</code> serve the same content as their HTML counterparts and are intended to be crawled and consumed by AI systems and third-party LLMs.</li>
<li>The plugin does not transmit data to any external service. All Markdown generation, caching, and file writes happen on your own server.</li>
</ul>
Nothing in this disclaimer is intended to exclude or limit liability for matters that cannot lawfully be excluded under the consumer-protection laws of your jurisdiction. For the full legal terms see the GPLv2 license at <a href="https://www.gnu.org/licenses/gpl-2.0.html" rel="nofollow ugc">https://www.gnu.org/licenses/gpl-2.0.html</a>.

One-V LLM Serve

Serve clean Markdown versions of every public page at the same URL with a .md extension for AI crawlers, LLMs, and GEO optimization.

Fran Barbero

The AI era has a problem: ChatGPT, Claude, and Perplexity are making up facts about your brand.
They crawl your raw HTML — a format built for humans — and hallucinate the gaps. Traditional SEO 
cannot fix this. A static sitemap cannot fix this. LLM Override fixes this.
LLM Override is a Machine-to-Machine (M2M) interception engine for WordPress. It speaks the 
language AI crawlers actually understand: clean, structured Markdown with semantic context — served 
in real time, directly from your site, without modifying a single page.
<h3>How AI systems read your content</h3>
Most AI tools for WordPress generate a list of URLs. That tells an AI crawler where your content 
is. LLM Override tells AI crawlers what your content means — making your brand accurately 
represented across AI-powered search engines.
When a bot visits your page, LLM Override intercepts the request before WordPress renders any HTML, 
and responds with a structured Markdown payload containing:
<ul>
<li>Your content, cleaned of scripts, ads, and UI noise</li>
<li>A YAML frontmatter block with your canonical title, URL, and last-updated timestamp</li>
<li>Your Site Manifest — verifiable organization facts included in your /llms.txt</li>
</ul>
This is Generative Engine Optimization (GEO): making your content accessible and accurately represented to AI systems.
<h3>How it works</h3>
<ol>
<li>LLM Override adds a <code><link rel="alternate" type="text/markdown"></code> tag into your page <code><head></code>.</li>
<li>An AI crawler discovers this link and follows it — that’s the standard Content Negotiation protocol.</li>
<li>It appends <code>?view=raw</code> to your URL and sends the request.</li>
<li>LLM Override intercepts at the WordPress routing layer — no HTML is rendered, no theme loads.</li>
<li>The crawler receives clean, semantic Markdown. Accurate content. No hallucinations.</li>
</ol>
Your human visitors never see any of this. Their experience is unchanged.
<h3>Core Features (Free)</h3>
M2M Interception Engine 
✅ Intercepts AI bot requests via <code>?view=raw</code> — works on any page, any post type 
✅ Converts HTML to clean Markdown using <code>league/html-to-markdown</code> 
✅ Strips <code><script></code>, <code><style></code>, <code><iframe></code>, and empty elements before conversion 
✅ Disables page caching (WP Rocket, LiteSpeed, W3TC, Cloudflare) for M2M requests to guarantee fresh content 
✅ Adds <code>X-Robots-Tag: noindex</code> to Markdown responses to prevent duplicate content flags 
✅ Adds <code>X-Content-Processing</code> transparency header declaring conversion method and source 
✅ Adds YAML frontmatter: title, canonical URL, last modified date, plugin version
Content Rules 
✅ Site Manifest — provide verifiable organization facts in your /llms.txt site manifest
llms.txt Standard Compliance 
✅ Dynamic <code>/llms.txt</code> endpoint — always current, zero static files, works on any hosting 
✅ Extended <code>/llms-full.txt</code> endpoint — includes content snippets for deeper AI context 
✅ Semantic Blockquote — select a global context page via UI to auto-generate the site manifest 
✅ Link Grouping — automatically categorizes links by post type (Pages, Optional, etc.) per llmstxt.org specs 
✅ Both endpoints automatically respect <code>noindex</code> rules from Yoast SEO, Rank Math, SEOPress, and AIOSEO 
✅ Announces <code>/llms.txt</code> in your <code>robots.txt</code> for passive bot discovery 
✅ <code><link rel="alternate" type="text/markdown"></code> auto-injected into every page <code><head></code>
Precision Control 
✅ Native WordPress metabox on every post/page: exclude from AI manifests or override the M2M payload manually 
✅ “View as AI” button in the WordPress Admin Bar: see exactly what any AI bot receives from any page
Shadow Analytics Lite 
✅ Tracks global M2M interception hits with a simple counter in your dashboard 
✅ GDPR-compliant: IP addresses are hashed daily, never stored in plain text 
✅ Detects 58 known AI bots across 4 categories (Training, Query, Discovery, Scraping)
Enterprise Sanitization 
✅ Strips Unicode corruption before delivery: BOM markers, Zero-Width Spaces, Non-Breaking Spaces, Soft Hyphens — the exact characters that cause parser errors in ChatGPT and Claude 
✅ Transient-based caching (12-hour TTL) for endpoint performance — with one-click AJAX flush
Developer API 
✅ 14 documented action/filter hooks for extending behavior without modifying plugin files 
✅ Clean OOP architecture with full Composer autoloading
<h3>Built to WordPress standards</h3>
LLM Override is developed following strict WordPress coding standards. Every function prefixed, 
every output escaped, every database query prepared, every nonce verified. No direct filesystem 
operations. No raw SQL injection. No short PHP tags.
The plugin passes the official WordPress Plugin Check tool with zero errors and zero warnings.
<h3>LLM Override Pro — Industrial-scale GEO</h3>
The free version covers the complete core M2M engine. Large sites and agencies need scale.
Pro unlocks: 
* 🤖 AI Copilot — per-post AI-generated Markdown with custom personas (GPT, Claude, DeepSeek, OpenRouter via BYOK) 
* ⚙️ Batch Accelerator — compile your entire site in the background via Action Scheduler, no timeouts 
* 📊 Full GEO Analytics — granular telemetry: which bots, which pages, which entities were injected 
* 🔬 Autopilot llms.txt — AI-drafted manifesto grounded in your actual content 
* 🏢 Agency MCP Server — expose a full Model Context Protocol endpoint for external agent orchestration
<a href="https://llmoverride.com" rel="nofollow ugc">Explore Pro features →</a>
<h3>GEO Compliance</h3>
LLM Override follows the principle of Content Faithfulness: everything served to 
AI bots is a faithful representation of your visible web content, optimized for 
machine consumption but never altered in substance.
<ul>
<li>Content is converted from HTML to Markdown without semantic changes</li>
<li>No content is added or removed from individual page responses</li>
<li>Structured data (JSON-LD) is extracted directly from visible page content</li>
<li>Full transparency via X-Content-Processing HTTP headers</li>
<li>Content Faithfulness Score tracks parity between HTML and Markdown outputs</li>
</ul>

LLM Override

Make your content accessible and accurate for AI systems. The compliance-first GEO optimization toolkit for WordPress.

One-V LLM Serve vs LLM Override