agentspeed.

modal.com

scanned 7/25/2026, 10:41:03 PM · cached · refresh in 22h · rubric 2026.07.4
Built with Webflow
robots.txt present: passrobots.txt allows AI agents: passContent-Signal directives: failllms.txt present: passSitemap present: failLink response headers: warnCanonical URL: skipMCP 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: skipCookie wall blocks content: skipPage title: skipMeta description: skipJSON-LD present: passStructured data validates: warnSchema type coverage: failPaywall / login wall: skipAgent Skills manifest: failWebMCP actions: failPrimary action reachable: passReachability: passTime to first byte: passFull render time: skipPage weight: pass54/ 100 · F
At risk

This is how AI agents (not browsers) experience modal.com. 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

Checks tagged “emerging” are 2026 agent-protocol standards most of the web hasn’t adopted yet — adopting early is an edge, not a defect.

failSitemap presentDiscoverability

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

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

failText-to-markup ratioReadability

Visible text is 1.4% of HTML weight (5906/411674 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%.

warnStructured data validatesStructured data

1 recommended-field warning(s). First: WebSite recommends "potentialAction" (improves agent comprehension).

Fix: Validate your JSON-LD with Google Rich Results test. Fix missing required properties.

failSchema type coverageStructured data

Page looks like Article|BlogPosting|NewsArticle; missing JSON-LD type(s): Article|BlogPosting|NewsArticle.

Fix: Align JSON-LD type to page purpose. Product pages without Product markup are skipped by agent shopping flows.

warnLink response headersDiscoverability

A Link: header is present but carries none of canonical/alternate/describedby — the relations agents consume.

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

failContent-Signal directivesemergingDiscoverability

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.

Fix: Add `Content-Signal:` directives to your robots.txt. This is the emerging standard (Cloudflare-driven) for declaring fine-grained AI usage policy beyond a binary allow/disallow.

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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.

Reference a sitemap
Publish /sitemap.xml and add this line to robots.txt.
Sitemap: https://modal.com/sitemap.xml

What the agent receives

The agent’s-eye view
Modal: High-performance AI infrastructure Product Solutions Resources Customers Pricing Docs Log In Sign Up AI infrastructure that developers love Run inference, training, batch processing, and sandboxes with sub-second cold starts, instant autoscaling, and a developer experience that feels local. Get Started Contact Us The production cloud for AI. Modal SDK Your cloud environment, in code. Stay in Python, ship to the cloud. Composable primitives that specify everything from logic to hardware in one place. AI-native runtime Built for speed, at any scale. Engineered from the ground up for heavy AI workloads, with super-fast autoscaling and containers that boot instantly. Elastic cloud capacity Autoscale from 0 to 1000+ GPUs, instantly. Modal routes workloads across clouds and regions in real time. Get the GPUs you need in seconds, with no commitments or capacity planning. Production ready Out-of-the-box observability. Integrated logging and full visibility into every function, sandbox, and container. The observability tools to build robust, production-ready applications. Workloads Build full-scale AI systems. Inference Deploy and scale inference for LLMs, audio, image/video generation. Training Fine-tune open-source models on single or multi-node clusters instantly. Sandboxes Programmatically scale secure, ephemeral environments for running untrusted code. Engineered for inference. From the proxy layer to the GPU scheduler, every part of Modal's stack is optimized for how inference workloads actually behave. Learn More LLM Inference Run any model or inference engine on H100s, A100s, A10Gs and more. Scale to zero between requests, burst to handle demand. Multi-modal Inference Image generation, video, audio, embeddings, or a model your team built from scratch. Any framework, any hardware config. Batch and Async Inference Run evals, embeddings, re-ranking, and dataset generation at scale. Thousands of GPUs, fully parallel, no job orchestration to manage. Online inference Sub-10ms overhead latency from anywhere with our globally distributed compute. Out-of-the-box support for token streaming, WebRTC, WebSocket. Built for the full training loop. From single-GPU fine-tuning to parallel hyperparameter sweeps to multi-node runs, Modal handles all of your coding infrastructure in a single code file. Learn More Fine-tuning SFT, LoRA, full fine-tunes on B200s, H100s, A100s and more. Any framework, any architecture, single or multi-GPU. Reinforcement Learning Thousands of concurrent trajectories, running in parallel. The only platform where sandboxes and training infrastructure are native to the same stack. Multi-node training Access up to 128 B200s with 3200 Gbps Infiniband networking, gang-scheduled with just a single line of code. Parallel hyperparameter sweeps Launch hundreds of experiments simultaneously with a few lines of code. Scale to the hardware you need, back to zero when you're done. Designed to scale agents. From interactive coding agents to long-running RL rollouts, Modal Sandboxes are the execution layer AI systems need: isolated, flexible, and built to scale. Learn More Coding agents Spin up fresh, isolated sandboxes programmatically. Custom images, any dependency — built for the latency and scale consumer AI products demand. Background agents Autonomous agents with the right tools, context, and credentials already in place — running securely in a full, isolated dev environment. RL rollouts Spin up hundreds of thousands of concurrent rollout environments in seconds. Fast enough to keep your GPU inference resources saturated across every episode. GPU-accelerated research H100s, A100s, A10Gs available on demand. Attach to any sandbox, scale to thousands of concurrent runs, pay by the second with no reserved capacity. Global GPU infrastructure Any GPU, any time Globally distributed across clouds Automated fleet health Scales with demand Any GPU, any time Globally distributed across clouds Automated fleet health Scales with demand Security and governance Team controls Battle-tested isolation SOC2 & HIPAA Data residency controls Learn More Team controls Battle-tested isolation SOC2 & HIPAA Data residency controls Learn More Empowering teams of all sizes to ship at scale Learn More 65% Latency reduction Real-time, multi-node inference for Runway Characters Real-time robot control running on Modal with 10–15 ms latency. 4 months faster to launch ML‑driven molecular design Powering AI app generation at scale “We’re actively saving 2 engineers’ worth of ongoing time” 3x latency decrease for document processing “Modal makes it easy to write code that runs on 100s of GPUs in parallel, transcribing podcasts in a fraction of the time.” Built with Modal All examples Audio Transcription LLM Inference Coding Agents Computational Biology Image and Video Inference Transcribe speech in batches with Whisper Turn audio bytes into text at scale Voice chat with LLMs Build an interactive voice chat app Transcribe speech with Kyutai STT Stream transcripts at the speed of speech Make music Turn prompts into music with ACE-Step Fine-tune Whisper on domain vocab Improve Whisper transcription accuracy on specialized vocabularies with fine-tuning Deploy a TTS API with Chatterbox Serve text-to-speech with Chatterbox to generate natural audio from text Ship your first app in minutes. Get Started $30 / month free compute AI infrastructure that developers love © Modal 2026 Products Inference Sandboxes Training Notebooks Batch Core Platform Resources Documentation Pricing Slack Community Articles GPU Glossary LLM Engine Advisor Model Library Company About Blog Careers Events Privacy Policy Security & Privacy Terms Popular Examples Serve your own LLM API Create custom art of your pet Analyze Parquet files from S3 with DuckDB Run hundreds of LoRAs from one app Finetune an LLM to replace your CEO

Show your score

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AgentSpeed score for modal.com
<a href="https://agentspeed.com/scan/modal.com"><img src="https://agentspeed.com/badge/modal.com" alt="AgentSpeed agent-readiness score" height="56"></a>

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Full breakdown

8 pass2 warn12 fail8 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. 1 training-data crawler(s) blocked (Bytespider) — a licensing choice, not scored.
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
pass
llms.txt present
Found /llms.txt (23734 bytes), H1 + at least one link present.
100/100
fail
Sitemap present
No reachable sitemap.xml. Publish one and reference it in robots.txt.
0/100
warn
Link response headers
A Link: header is present but carries none of canonical/alternate/describedby — the relations agents consume.
60/100
skip
Canonical URL
Check could not run.
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 1.4% of HTML weight (5906/411674 bytes). Low. Markup may be crowding out agent-usable text.
11/100
skip
Content without JavaScript
Browser pass unavailable; cannot measure JS dependency.
skip
Heading hierarchy
Check could not run.
skip
Cookie wall blocks content
Check could not run.
skip
Page title
Check could not run.
skip
Meta description
Check could not run.
Structured data
pass
JSON-LD present
Found 1 JSON-LD block.
100/100
warn
Structured data validates
1 recommended-field warning(s). First: WebSite recommends "potentialAction" (improves agent comprehension).
95/100
fail
Schema type coverage
Page looks like Article|BlogPosting|NewsArticle; missing JSON-LD type(s): Article|BlogPosting|NewsArticle.
0/100
Actionability
skip
Paywall / login wall
Check could not run.
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 ("AI infrastructure platform") with price/CTA ("$30 / month free compute").
100/100
pass
Reachability
HTTP 200.
100/100
Performance
pass
Time to first byte
TTFB 163ms. Healthy.
100/100
skip
Full render time
Full-render time unavailable (browser pass skipped or failed).
pass
Page weight
Initial document is a lean 402 KB.
100/100
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