agentspeed.

llamaindex.ai

scanned 7/25/2026, 10:40:31 PM · cached · refresh in 22h · rubric 2026.07.4
robots.txt present: passrobots.txt allows AI agents: passContent-Signal directives: failllms.txt present: warnSitemap present: failLink response headers: failCanonical URL: failMCP server card: failOAuth authorization metadata: failOAuth resource metadata: failAPI catalog / OpenAPI: failWeb Bot Auth: failMarkdown negotiation: failText-to-markup ratio: failContent without JavaScript: skipHeading hierarchy: passCookie wall blocks content: passPage title: passMeta description: passJSON-LD present: failStructured data validates: skipSchema type coverage: passPaywall / login wall: passAgent Skills manifest: failWebMCP actions: failPrimary action reachable: passReachability: passTime to first byte: passFull render time: skipPage weight: pass64/ 100 · D
Needs work

This is how AI agents (not browsers) experience llamaindex.ai. The score weights five categories of machine-readability; the ticks on the arc are the 30 individual checks behind it.

✉ Email me this report + alert me when it changes ↓

Top fixes

failSitemap presentDiscoverability

No reachable sitemap.xml. Publish one and reference it in robots.txt.

Fix: Publish /sitemap.xml and reference it from robots.txt with a Sitemap: line.

failCanonical URLDiscoverability

No <link rel="canonical"> tag in <head>. Agents use canonical URLs to dedupe and cite.

Fix: Add <link rel="canonical" href="…"> pointing at the primary URL of each page.

failJSON-LD presentStructured data

No JSON-LD blocks found. Add a <script type="application/ld+json"> with a schema.org type for this page.

Fix: Add a <script type="application/ld+json"> describing the page (Organization, Article, Product, FAQPage).

warnllms.txt presentDiscoverability

Found /llms.txt but missing H1 header and markdown links.

Fix: Publish /llms.txt at your domain root. Build a spec-compliant one at /tools/llms-txt-generator.

failLink response headersDiscoverability

No HTTP Link: response headers. Emit canonical/alternate/describedby relations so HEAD-only or stream-rendering agents get them without parsing HTML.

Fix: Emit `Link:` headers for canonical, alternate-language, and describedby relations. Agents that fetch HEAD-only or stream-render rely on these.

failText-to-markup ratioReadability

Visible text is 2.7% of HTML weight (8396/308439 bytes). Low. Markup may be crowding out agent-usable text.

Fix: Heavy ad or navigation markup crowds out agent-usable text. Aim for a text-to-DOM ratio above 15%.

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Fix it

Generated, ready-to-ship files for the gaps above — copy them or download and drop them into your repo.

Add an llms.txt
Publish this at https://llamaindex.ai/llms.txt
# LlamaIndex | AI Agents for Document OCR + Workflows

> LlamaParse is the world

## Key pages
- [Home](https://llamaindex.ai/)
- [Document OCR for the agentic stack](https://llamaindex.ai/)
- [Get started with LlamaParse for free](https://llamaindex.ai/)
- [We parse your most complex docs](https://llamaindex.ai/)
- [Unrivaled performance across complex documents](https://llamaindex.ai/)
- [How leading teams use document intelligence](https://llamaindex.ai/)
- [Built for every document-heavy industry](https://llamaindex.ai/)

## About
Describe what llamaindex.ai does, who it's for, and the primary action you want an
agent to be able to complete. Keep it factual and current.

What the agent receives

The agent’s-eye view
LlamaIndex | AI Agents for Document OCR + Workflows Live Webinar ! Decision-ready context for financial services agents → Save your seat Product LlamaParse Industry-leading document processing Parse Extract Index Open Source OSS repos trusted by millions of developers LiteParse Workflows LlamaIndex Solutions Persona Engineering &amp; R&amp;D Accelerate product development Administrative Operations Streamline business processes Financial Analysts Build AI-powered financial models Industry Insurance Automate claims and underwriting Finance Power financial research Manufacturing Optimize system uptime Healthcare &amp; Pharma Accelerate clinical research Use cases Financial Due Diligence Speed up compliance reviews Invoice Processing Automate manual review Technical Document Search Find answers in complex docs Customer Support Instant, accurate responses Docs Resources Resources Customer stories See real-world success stories Jeppesen (a Boeing Company) Saves ~2,000 Engineering Hours with Unified Chat Framework Company About us Our mission and story Careers Join our growing team Brand Logos and brand guidelines View open roles at LlamaIndex Blog Pricing Book a demo Try for free Product LlamaParse Industry-leading document processing Parse Extract Index Open Source OSS repos trusted by millions of developers LiteParse Workflows LlamaIndex Solutions Persona Engineering &amp; R&amp;D Accelerate product development Administrative Operations Streamline business processes Financial Analysts Build AI-powered financial models Industry Insurance Automate claims and underwriting Finance Power financial research Manufacturing Optimize system uptime Healthcare &amp; Pharma Accelerate clinical research Use cases Financial Due Diligence Speed up compliance reviews Invoice Processing Automate manual review Technical Document Search Find answers in complex docs Customer Support Instant, accurate responses Docs Resources Customer stories See real-world success stories How Jeppesen (a Boeing Company) Saves ~2,000 Engineering Hours with Unified Chat Framework Company About us Our mission and story Careers Join our growing team Brand Logos and brand guidelines View open roles at LlamaIndex Blog Pricing Book a demo Try for free Document OCR for the agentic stack LlamaParse turns hours of manual document processing into seconds of automation, with VLM-powered document understanding agents. Get started Book a Demo Get started with LlamaParse for free Our free plan includes: 10,000 free credits per month (~1000 pages) Agentic OCR for layout-aware document parsing Structured extraction of defined schemas Build and deploy end-to-end document agents Try LlamaParse How it works We parse your most complex docs 01 / 02 / 03 Agentic Understanding Complex layouts turned into clean, LLM-ready outputs through semantic understanding. Specialized experts Task-specific agents break down content such as text, charts, tables, and more, routing it to the right expert. Auto-Correction Loops Recursive checks that detect and fix errors automatically, delivering high pass-through rates even on messy scans and multi-modal documents. Handwritten Text Parse messy handwriting, extract structure, and make it usable for AI workflows. Tables Extract rows, columns, and relationships — even from dense or irregular layouts. Charts Turn charts and graphs into structured data your pipelines can use. 1B+ Documents processed 25M+ package downloads a month 300k+ LlamaParse users Unrivaled performance across complex documents Benchmark LlamaParse VLM - Proprietary Commercial - IDP Open Source OCR Overall performance Charts Tables 01 LlamaParse LlamaParse powers enterprise-grade document automation with industry-best parsing, extraction, indexing, and retrieval — optimized for accuracy, configurability, and scalability. Learn more Book a demo Parse Industry-leading document parsing for 50+ unstructured file types — including support for embedded images, complex layouts, multi-page tables, and even handwritten notes. Extract Turn unstructured content into structured insights using schema-based, LLM-powered extraction agents — no training required Split Segment a document into logical sections based on natural-language descriptions. Classify Automatically categorize documents using natural-language rules. Index Enterprise-grade chunking and embedding pipeline. Built to deliver precision and relevance in every retrieval call for best-in-class RAG. npm install @llamaindex/liteparse 02 LiteParse Parse Any Document. Locally. Fast. Open-source document parsing from the team behind LlamaParse. Parsed text from PDFs, Office docs, and images — no cloud, no LLM tokens, no limits. View on GitHub Learn more Fully open-source Fast local processing All major formats Bounding box output Use cases How leading teams use document intelligence Context for AI Agents Enable LLMs to read complex documents with human-level precision. Book a demo Replace legacy IDP Modernize document processing without custom templates. Book a demo Multi-step document agents Build durable agents that automate knowledge work. Book a demo Industries Built for every document-heavy industry Get started Book a demo Finance From financial research and due diligence to automated invoice processing, leading banks, hedge funds, and fintechs are transforming workflows with AI. Explore finance Insurance Risk and protection leaders are turning unstructured data into action—streamlining underwriting, audits, and claim proccessing. Explore insurance Manufacturing Leading manufacturers are using AI to extract insights from specs, manuals, and inspection reports—faster and more accurately. Explore Manufacturing Healthcare From medical records and handwritten doctor notes to insurance claims, healthcare providers are using AI to streamline clinical and administrative workflows. Explore Healthcare 99.9% uptime Infrastructure designed for always-on document processing — stable under real production load. Enterprise-Grade Security Granular access controls, enhanced data encryption, and HIPAA, GDPR, and SOC2 compliant out-of-the-box. Dedicated Support &amp; SLAs Dedicated support, fast response times, and SLAs tailored to mission-critical AI workloads. Flexible Deployment Run in our secure cloud or deploy fully in your VPC, ensuring data residence requirements. Enterprise Ready Built for teams running production-grade AI with reliability, security, and control at scale. Book a demo 99.9% uptime Infrastructure designed for always-on document processing — stable under real production load. Enterprise-Grade Security Granular access controls, enhanced data encryption, and HIPAA, GDPR, and SOC2 compliant out-of-the-box. Dedicated Support &amp; SLAs Dedicated support, fast response times, and SLAs tailored to mission-critical AI workloads. Flexible Deployment Run in our secure cloud or deploy fully in your VPC, ensuring data residence requirements. testimonials Trusted by leading AI teams Manuel De Juan Director, Global AI office at NttData “LlamaParse simplifies parsing complex documents which is crucial for end-to-end AI development.” Alvin Alaphat Founding engineer at Delphi “We benchmarked LlamaParse against everything else we could find. It had the most reliable output and cleanest formatting—especially for our most difficult content.” Dean Barr Applied AI Lead and Data Scientist at Carlyle “LlamaParse stands out as the premier solution for parsing complex documents in enterprise agent pipelines.” Upgrade your document processing today LlamaParse unlocks unrivaled accuracy and scale. Sign up for free Book a Demo Build document agents that understand, reason, and act Contact sales Sign up Explore AI Summary Solutions Engineering & R&D Administrative Operations Financial Analysts Developers Insurance Finance Manufacturing Healthcare &amp; Pharma Finance Due Diligence Invoice Processing Technical Document Search Customer Support Products LlamaParse Parse Extract Index LlamaInde

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AgentSpeed score for llamaindex.ai
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Full breakdown

12 pass1 warn14 fail3 skip
Discoverability
pass
robots.txt present
A robots.txt is reachable at the site root.
100/100
pass
robots.txt allows AI agents
All 8 answer-time access agents allowed.
100/100
fail
Content-Signal directivesemerging
No Content-Signal directives. Add e.g. `Content-Signal: ai-train=no, ai-summarize=yes` to declare granular AI usage policy beyond binary allow/disallow.
0/100
warn
llms.txt present
Found /llms.txt but missing H1 header and markdown links.
60/100
fail
Sitemap present
No reachable sitemap.xml. Publish one and reference it in robots.txt.
0/100
fail
Link response headers
No HTTP Link: response headers. Emit canonical/alternate/describedby relations so HEAD-only or stream-rendering agents get them without parsing HTML.
0/100
fail
Canonical URL
No <link rel="canonical"> tag in <head>. Agents use canonical URLs to dedupe and cite.
0/100
fail
MCP server cardemerging
No valid MCP Server Card at /.well-known/mcp/server-card.json. Publish one so agents can discover your tools without HTML scraping.
0/100
fail
OAuth authorization metadataemerging
No RFC 8414 metadata at /.well-known/oauth-authorization-server. Agents that act on behalf of users need this to discover your authorization endpoints.
0/100
fail
OAuth resource metadataemerging
No RFC 9728 metadata at /.well-known/oauth-protected-resource. Publish it so agents can discover required scopes without hand-coded credentials.
0/100
fail
API catalog / OpenAPIemerging
No /.well-known/api-catalog (RFC 9727) and no /openapi.json|yaml. Publish one so agents that integrate with APIs can discover your endpoints.
0/100
fail
Web Bot Authemerging
No Web Bot Auth JWKS at /.well-known/http-message-signatures-directory.json. Publish one to allow trusted agents while keeping a default-deny posture for the rest.
0/100
Readability
fail
Markdown negotiationemerging
Accept: text/markdown returns HTML, not markdown. Serve a markdown variant of primary content when requested; agents summarize and cite it more reliably.
0/100
fail
Text-to-markup ratio
Visible text is 2.7% of HTML weight (8396/308439 bytes). Low. Markup may be crowding out agent-usable text.
20/100
skip
Content without JavaScript
Browser pass unavailable; cannot measure JS dependency.
pass
Heading hierarchy
Hierarchy is well-formed (1 H1, no skipped levels, 24 headings total).
100/100
pass
Cookie wall blocks content
No common consent-modal markers detected.
100/100
pass
Page title
A concise <title> is present (51 chars).
100/100
pass
Meta description
A well-sized meta description is present (146 chars).
100/100
Structured data
fail
JSON-LD present
No JSON-LD blocks found. Add a <script type="application/ld+json"> with a schema.org type for this page.
0/100
skip
Structured data validates
No JSON-LD blocks present; nothing to validate (covered by structured_data.jsonld_present).
pass
Schema type coverage
Page intent unclear; no specific schema.org type expected.
100/100
Actionability
pass
Paywall / login wall
No paywall or login-wall detected on the landing URL.
100/100
fail
Agent Skills manifestemerging
No Agent Skills manifest at /.well-known/agent-skills.json. Enumerate the tasks agents can perform (search, add-to-cart, contact-support) so they pick the right one without scraping.
0/100
fail
WebMCP actionsemerging
No WebMCP detected. On pages with first-class actions (cart, support, account), embed a WebMCP server so on-page agents invoke tools directly.
0/100
pass
Primary action reachable
Primary offering identified ("Document OCR and parsing platform") with price/CTA ("Try for free").
100/100
pass
Reachability
HTTP 200 after 1 redirect.
100/100
Performance
pass
Time to first byte
TTFB 122ms. Healthy.
100/100
skip
Full render time
Full-render time unavailable (browser pass skipped or failed).
pass
Page weight
Initial document is a lean 301 KB.
100/100
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