The Plain Fetch viewer
In short
The viewer requests a URL the way a plain-fetch agent does: no JavaScript, one request for HTML, one for markdown, one for llms.txt and one for a path that should not exist. It shows the initial HTML on the left, the readable text on the right, and seven flags underneath.
Pre-loaded with www.wikipedia.org, read 4 November 2026. Type any public URL to run your own.
The page answers a plain fetch: 4 of 6 checks found.
Initial HTML what a plain fetch receives
<!DOCTYPE html>
<html lang="en">
<head>
<meta charSet="utf-8" data-next-head=""/>
<title data-next-head="">Elastic: The search database for AI | Search, AI agents, Observability, and Security | Elastic
</title>
[... 5 more head elements folded ...]
<meta name="description" content="Powered by Elasticsearch. Ready to deploy your data? Start free." data-next-head=""/>
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<meta name="viewport" content="width=device-width, initial-scale=1" data-next-head=""/>
[... 1 more head element folded ...]
<meta name="robots" content="index,follow" data-next-head=""/>
<link rel="canonical" href="https://www.elastic.co/" data-next-head=""/>
[... 38 more head elements folded ...]
</head>
<body>
<div id="__next">
<div class="progress-container">
<div class="progress-bar" id="myBar">
</div>
</div>
<div class="skip-links"><a href="#main-content" rel="noreferrer" class="euiButton euiSkipLink css-1a3wap1-euiButtonDisplay-s-defaultMinWidth-fill-primary-euiSkipLink-euiScreenReaderOnly-showOnFocus"><span class="css-cf8eum-euiButtonDisplayContent"><span class="eui-textTruncate">Skip to main content</span></span></a>
</div>
<header class="primary header-wrapper" data-nav-version="2026-03">
<div class="Navigation_navigation__vsvF6 Navigation_navigation-fixed__IaYBy" data-theme="light" data-global-nav="true">
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<div class="Masthead_masthead-content__Hnnhh">
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<p class="Marquee_marquee-tag__n7Zjn">
<svg data-component="Icon" class="Icon_icon__W79Na" width="10" height="10" aria-hidden="true" xmlns="http://www.w3.org/2000/svg" fill="none"><path fill="#DD0A73" d="M10 5a5 5 0 0 0-5 5 5 5 0 0 0-5-5 5 5 0 0 0 5-5 5 5 0 0 0 5 5"></path>
</svg>
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<div class="Marquee_marquee-container__Cz9uv">
<p>The Forrester Wave™: XDR Platforms, Q2 2026
</p>
</div><a href="/resources/security/report/forrester-xdr-wave?plcmt=global-alert-banner&cta=eswp-174" data-location="masthead">Access report</a>
</div>
<div class="Masthead_masthead-links__82Txb"><a href="/about" data-location="masthead">About us</a><a href="/partners" data-location="masthead">Partners</a><a href="/support" data-location="masthead">Support</a>|<button type="button" id="radix-:Rmckl6:" aria-haspopup="menu" aria-expanded="false" data-state="closed" class="Language_language__HzQJL" data-location="top-nav">
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</svg>Log in</a>
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<div data-component="Container" class="Container_container__CBaVM Container_container--gutter-sm__KJ8r_ Container_container--width-lg__WQnkF Navigation_navigation-container__3V6Pb"><a class="Logo_logo__8Ik3Q" href="/">
<svg width="117" height="40" viewBox="0 0 117 40" fill="none" xmlns="http://www.w3.org/2000/svg" aria-labelledby="elastic-logo-title">[... 5,981 characters folded ...]
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<nav aria-label="Main" data-orientation="horizontal" dir="ltr" class="NavDropdown_nav-dropdown__bxj1L">
<div class="NavDropdown_nav-dropdown-overlay__WIC7T">
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<div style="position:relative">
<ul data-orientation="horizontal" class="NavDropdown_nav-dropdown-list__aQOGV" dir="ltr">
<li><button id="radix-:R6kkl6:-trigger-Products" data-state="closed" aria-expanded="false" aria-controls="radix-:R6kkl6:-content-Products" class="NavDropdown_nav-dropdown-trigger__VzR18" data-location="top-nav" data-nav-trigger-value="Products" data-radix-collection-item=""><span>Elasticsearch</span>
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 16 16" fill="currentColor" aria-hidden="true" data-slot="icon">[... 190 characters folded ...]
</svg></button>
<div id="radix-:R6kkl6:-content-Products" aria-labelledby="radix-:R6kkl6:-trigger-Products" data-orientation="horizontal" data-state="closed" class="NavDropdown_nav-dropdown-products__z5AD2 nav-dropdown-container" style="pointer-events:none" dir="ltr">
<div class="NavSection_nav-section__xqslV">
<h5 class="NavSection_nav-section-title__sxDjV">Elasticsearch for...
</h5>
<ul class="NavSection_nav-section-cards__c0XRx NavSection_nav-section-cards-twin-column__xh7r9">
<li><a href="/elasticsearch/context-engineering" class="NavSection_nav-section-card__B5R3D" data-location="top-nav">
<h6 class="NavSection_nav-section-subtitle__fMMCy">Context engineering
</h6>
<p class="NavSection_nav-section-description__BJJEx">Get the most relevant context to agents so that they deliver accurate and trusted outcomes
</p></a>
</li>
<li><a href="/elasticsearch/vector-database" class="NavSection_nav-section-card__B5R3D" data-location="top-nav">
<h6 class="NavSection_nav-section-subtitle__fMMCy">Vector database
</h6>
<p class="NavSection_nav-section-description__BJJEx">Efficiently create, store, and search vector embeddings
</p></a>
</li>
<li><a href="/enterprise-search/search-applications" class="NavSection_nav-section-card__B5R3D" data-location="top-nav">
<h6 class="NavSection_nav-section-subtitle__fMMCy">Search powered applications
</h6>
<p class="NavSection_nav-section-description__BJJEx">The speed, scale, and flexibility to power modern application experience
</p></a>
</li>
<li><a href="/observability/log-monitoring" class="NavSection_nav-section-card__B5R3D" data-location="top-nav">
<h6 class="NavSection_nav-section-subtitle__fMMCy">Logs
</h6>
<p class="NavSection_nav-section-description__BJJEx">Collect, search, explore, and act on large volumes
</p></a>
</li>
<li><a href="/security/investigation-response" class="NavSection_nav-section-card__B5R3D" data-location="top-nav">
<h6 class="NavSection_nav-section-subtitle__fMMCy">Threat protection
</h6>
<p class="NavSection_nav-section-description__BJJEx">Detect, investigate, and remediate cyber threats at scale on real-time data
</p></a>
</li>
<li><a href="/elasticsearch/workflows" class="NavSection_nav-section-card__B5R3D" data-location="top-nav">
<h6 class="NavSection_nav-section-subtitle__fMMCy">Workflows
</h6>
<p class="NavSection_nav-section-description__BJJEx">Combine scripted automation with AI reasoning natively in Elasticsearch
</p></a>
</li>
</ul>
</div>
<div class="NavSection_nav-section__xqslV">
<h5 class="NavSection_nav-section-title__sxDjV">Elasticsearch components
</h5>
<ul class="NavSection_nav-section-cards__c0XRx NavSection_nav-section-cards-twin-column__xh7r9">
<li><a href="/elasticsearch" class="NavSection_nav-section-card__B5R3D" data-location="top-nav">
<h6 class="NavSection_nav-section-subtitle__fMMCy">Elasticsearch
</h6>
<p class="NavSection_nav-section-description__BJJEx">A distributed, RESTful search and analytics engine
</p></a>
</li>
<li><a href="/kibana" class="NavSection_nav-section-card__B5R3D" data-location="top-nav">
<h6 class="NavSection_nav-section-subtitle__fMMCy">Kibana (Discover, Dashboards)
</h6>
<p class="NavSection_nav-section-description__BJJEx">Explore, visualize, and build dashboards using data stored in Elasticsearch
</p></a>
</li>
<li><a href="/elasticsearch/agent-builder" class="NavSection_nav-section-card__B5R3D" data-location="top-nav">
<h6 class="NavSection_nav-section-subtitle__fMMCy">Elastic Agent Builder
</h6>
<p class="NavSection_nav-section-description__BJJEx">Build context-aware agents faster that incorporate all your data and deliver best-in-class relevance.
</p></a>
</li>
<li><a href="/platform/autoops" class="NavSection_nav-section-card__B5R3D" data-location="top-nav">
<h6 class="NavSection_nav-section-subtitle__fMMCy">AutoOps
</h6>
<p class="NavSection_nav-section-description__BJJEx">Easy cluster management with performance recommendations, resource utilization, and cost insights
</p></a>
</li>
<li><a href="/elasticsearch/piped-query-language" class="NavSection_nav-section-card__B5R3D" data-location="top-nav">
<h6 class="NavSection_nav-section-subtitle__fMMCy">Piped query language
</h6>
<p class="NavSection_nav-section-description__BJJEx">Simplify workflows and accelerate query response for efficient data processing
</p></a>
</li>
<li><a href="/jina-search-models" class="NavSection_nav-section-card__B5R3D" data-location="top-nav">
<h6 class="NavSection_nav-section-subtitle__fMMCy">Jina AI search models
</h6>
Shown with 41 long blocks (scripts, styles, long tags) folded into a marker that says how many characters they hide; line breaks added before block tags because the source is minified; the pane stops after the first 200 words; the page is 891 KB.
Reading view the text a plain-fetch client can extract
title: Elastic: The search database for AI | Search, AI agents, Observability, and Security | Elastic
Elasticsearch: The search database for AI
Skip to main content The Forrester Wave™: XDR Platforms, Q2 2026 Access report About us Partners Support | Log in Elasticsearch Elasticsearch for... Context engineering Get the most relevant context to agents so that they deliver accurate and trusted outcomes Vector database Efficiently create, store, and search vector embeddings Search powered applications The speed, scale, and flexibility to power modern application experience Logs Collect, search, explore, and act on large volumes Threat protection Detect, investigate, and remediate cyber threats at scale on real-time data Workflows Combine scripted automation with AI reasoning natively in Elasticsearch Elasticsearch components Elasticsearch A distributed, RESTful search and analytics engine Kibana (Discover, Dashboards) Explore, visualize, and build dashboards using data stored in Elasticsearch Elastic Agent Builder Build context-aware agents faster that incorporate all your data and deliver best-in-class relevance. AutoOps Easy cluster management with performance recommendations, resource utilization, and cost insights Piped query language Simplify workflows and accelerate query response for efficient data processing Jina AI search models Jina AI is part of Elastic, bringing best-in-class models for embeddings, rerankers, and URL and doc extraction Deployment options Elastic Cloud Serverless Zero operational load so that you can build faster Start free trial Elastic Cloud Hosted Deploy
2263 more words follow in the initial HTML.
| Check | Result | Detail |
|---|---|---|
| H1 in the initial HTML | Found one H1 | First H1: Elasticsearch: The search database for AI |
| First 200 words in the initial HTML | Found 200 of 200 words | The initial HTML carries 2463 words of visible text; the first 200 are marked in the left pane. |
| llms.txt present and linked | Note present, not linked | 14936 bytes, 195 links. Structure grade A (6 of 6). Nothing on the home page points to it. Ora's lab found 86 percent of llms.txt fetches arrived through a link. |
| Markdown on request | Missing 200 text/html | Accept: text/markdown returned 200 with text/html; charset=utf-8. The server ignores the header. |
| Status of a made-up path | Found 404 | /agent-ready-html-missing-path-check returned 404: a real status code for a missing page. |
| JSON-LD types | Found WebPage | 1 schema.org type in JSON-LD blocks on the home page: WebPage. |
| OpenAPI link | Note none on the home page | No OpenAPI link on the home page. It matters only for a site that ships an API. |
Run the full check
The viewer read one page with four requests. The full check we recommend next is Ora's scan. Its Access layer runs 42 checks worth 30 of its 100 points, among them content without JavaScript, bot detection, llms.txt, markdown on request, JSON-LD and the sitemap (Ora's check catalogue, contract 1.38.0, read 5 November 2026). Open Ora's report for elastic.co.
Limits: Ora reads public URLs only, says two runs of one scan land within a couple of points without publishing repeat-scan data, and keeps the product that fixes what it finds behind a waitlist. Cloudflare's scanner at isitagentready.com is a quick free alternative, and Mintlify's score covers documentation.
What the viewer does
It sends four plain GET requests with the user agent Mozilla/5.0 (compatible; agent-readiness-crawl/1.0): the URL itself, the same URL with Accept: text/markdown, /llms.txt on the same host, and a made-up path at the root. It runs no JavaScript. The left pane is the first bytes of the HTML as text, with long scripts and styles folded into a marker that says how many characters they hide. The H1 and the first 200 words of visible text are marked in both panes. The flags under the panes say what the four responses added up to.
Limits
- Ten seconds for all four requests together, 1.5 MB read from the home page, at most five redirects, each one checked again.
- http and https only, default ports only. Private, local and internal addresses and names are refused.
- Ten runs per address per minute. The counter lives in memory on the edge function, so it is per instance rather than global. Past ten you get a 429 with a Retry-After header.
- Results are cached for 24 hours by the response headers. Nothing is written to a database: the viewer keeps the first 200 words and the extracted fields for the length of the request and keeps no page body beyond that.
What it does not tell you
A plain fetch from this server is not a real agent. Bot protection weighs the source address more than the user agent, so a page that answers 200 here can still refuse an agent, and the reverse. Ora's lab found (2026-10-19) that returning 403 to agent user agents and hiding the answer in JavaScript were the only two of 19 configurations that stopped retrieval; the viewer can see the second, and can only hint at the first. The initial HTML reference covers both. The server logs and the published crawler address ranges settle the first.
The seven flags
- H1 in the initial HTML
- Whether the HTML the server sends already contains an H1. It is the cheapest sign that the page does not depend on scripts to say what it is.
- First 200 words in the initial HTML
- Whether at least 200 words of visible text arrive in the initial HTML. Under 40 words with an app root element is flagged as a JavaScript shell.
- llms.txt present and linked
- Whether /llms.txt answers with a plain-text file, whether the home page links it (an anchor, a link element or a Link header), and the structure grade the index uses.
- Markdown on request
- Whether a request with Accept: text/markdown comes back as text/markdown. Cloudflare Radar found 3.9 percent of scanned top sites passing this at its April 2026 launch.
- Status of a made-up path
- Whether a path that should not exist returns 404 or 410. A 200 is a soft 404 and reads as a live page.
- JSON-LD types
- The schema.org types found in JSON-LD blocks on the page. Ora's lab found JSON-LD made no difference when the answer was already in the HTML.
- OpenAPI link
- Whether the page links an OpenAPI file, by an anchor or a service-desc link relation. It matters only for a site that ships an API.
Sources
- Ora: AgentReady launch post (Ora's lab findings) https://ora.ai/blog/agentready-launch, read 4 November 2026
- Ora check catalogue, contract 1.38.0 (132 checks, 42 in the Access layer) https://ora.ai/api/checks, read 5 November 2026
- Ora home page (the fixing product is behind a waitlist) https://ora.ai/, read 5 November 2026
- Ora: Introducing Deep Scan (repeat scans) https://ora.ai/blog/introducing-deep-scan, read 5 November 2026
- Ora llms.txt (public URLs only) https://ora.ai/llms.txt, read 5 November 2026
- Vercel: Make your site readable by AI agents https://vercel.com/kb/guide/make-your-site-readable-by-ai-agents, read 4 November 2026
- llms.txt proposal (llmstxt.org) https://llmstxt.org/, read 4 November 2026
Last reviewed 5 November 2026