agentspeed.

braintrust.dev

scanned 7/25/2026, 10:40:58 PM · cached · refresh in 22h · rubric 2026.07.4
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robots.txt present: passrobots.txt allows AI agents: passContent-Signal directives: failllms.txt present: passSitemap present: passLink response headers: warnCanonical URL: passMCP 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: warnMeta description: passJSON-LD present: passStructured data validates: passSchema type coverage: passPaywall / login wall: passAgent Skills manifest: failWebMCP actions: failPrimary action reachable: passReachability: passTime to first byte: passFull render time: skipPage weight: pass78/ 100 · C
Good

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

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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.

failText-to-markup ratioReadability

Visible text is 2.2% of HTML weight (6991/316803 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%.

warnPage titleReadability

<title> is 75 characters; keep it under 70 so it isn't truncated.

Fix: Add a concise <title> tag. Agents often cite it verbatim.

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.

failMCP server cardemergingDiscoverability

No valid MCP Server Card at /.well-known/mcp/server-card.json. Publish one so agents can discover your tools without HTML scraping.

Fix: Publish an MCP Server Card describing the tools your site exposes. Agents discover capabilities via `/.well-known/mcp/server-card.json`. See modelcontextprotocol.io for the schema.

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Qualifies for certificationBronze

This score clears the Bronze threshold (70+). Certification turns it into a dated, publicly verifiable attestation — a verification URL, an embeddable badge, and weekly monitoring for a full year. Scores under 70 can’t buy this, which is what makes displaying it mean something.

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What the agent receives

The agent’s-eye view
Braintrust - The AI observability platform for building quality AI products Product Resources Customers Pricing Contact us Sign in Sign up Observe Trace everything Evaluate Test what ships Discover Find patterns Docs Start building Blog Insights and updates Foundations Learn to eval Encyclopedia Eval concepts Product Observe Evaluate Discover Resources Docs Blog Foundations Encyclopedia Customers Pricing Contact us Sign in Sign up Automate pattern discovery with Topics Ship quality agents at scale Surface patterns in production, turn them into evals, and improve quality with every release. Start building Contact sales Build with agents Trusted by the best AI teams Watch video Watch video Watch video Read story Watch video Inspect agent traces in real time Workflow Platform Scale Security Customers Agents fail differently than normal software. You need active observability to monitor and fix them. AI drifts and regresses silently. With patterns surfaced automatically, the best teams can evaluate against expectations and iterate continuously. Trace everything Inspect prompts, responses, and tool calls in real time Measure quality with evals Score outputs with LLMs, code, or humans Catch issues early Block bad releases before they hit production Explore the three pillars of AI observability Take the eval maturity assessment Agent observability and evals for the whole team. From engineering to product, in one platform. Observability See what actually happened in production. Inspect every agent trace and tool call, search across millions of logs, and track latency, cost, and quality in real time. Scalable agent trace ingestion Live performance monitoring Custom views and annotation Log your first trace Evals Define what good looks like before you ship. Run experiments against real datasets, compare prompts and models side-by-side, and score outputs with LLMs, code, or humans. Fast prompt engineering Flexible, versioned datasets Automated and human scoring Run your first eval Discovery Turn production signals into improvements automatically. Topics surfaces patterns in real time across task, issues, and sentiment, online scoring catches regressions, and quality gates block bad releases. Automatic pattern discovery Continuous online scoring Quality gates and alerts Discover patterns with Topics Everything you need to build smarter, faster Loop agent AI that helps you improve agents. Describe what you want to optimize, and Loop generates better prompts, scorers, and datasets automatically. Optimize your evals Custom facets Define the dimensions that matter to your business, like use case, customer segment, compliance, or tone. Topics continuously clusters every trace against them. Design your own facet Task-specific trace views Build annotation interfaces that match your team&#x27;s workflow. Review support conversations differently than code generation, with no frontend work required. Build custom views Trace to dataset Turn production traces into eval datasets with one click. Build regression tests from real failures and edge cases, not synthetic examples. Explore datasets MCP Query logs, run evals, and update prompts directly from your IDE. Braintrust&#x27;s MCP server connects your coding agent to your AI stack. Set up MCP Framework agnostic Works with any stack you&#x27;re already using. No framework lock-in, no rewrites, no vendor dependencies to manage. View all integrations Native SDKs SDKs for Python, TypeScript, Go, Ruby, C#, and more. Start tracing production agents with just a few lines of code. Read SDK docs Brainstore, the database built for AI data at scale. Designed for complex agent traces. Agent traces are large and nested. Traditional databases can&#x27;t handle the complexity. Brainstore is designed specifically for agent observability so you can query millions of traces quickly. Learn more about Brainstore 0.0x Faster full text search Competition 0 ms Brainstore 0 ms 0.00x Faster write latency Competition 0 ms Brainstore 0 ms 0.00x Faster span load time Competition 0 ms Brainstore 0 ms Secure by default. Compliant from day one. SOC 2 Type II certified. GDPR compliant. SSO, RBAC, HIPAA compliant, and hybrid deployment options out of the box. SOC 2 Type II Independently audited security controls verified annually SSO / SAML Integrate with your identity provider for seamless authentication HIPAA compliant Full compliance with HIPAA requirements to secure PII GDPR compliant Full compliance with EU data protection regulations Granular permissions Fine-grained access control at the project and resource level Hybrid deployment Deploy Brainstore data plane on your own infrastructure Learn about hybrid deployments Visit trust center Built for teams running agents in production. From first ship to enterprise scale. Meet all the teams Malte Ubl , CTO “ We didn&#x27;t realize we needed deep observability until Braintrust. ” Sarah Sachs , AI Lead “ There are some problems we wouldn&#x27;t know were problems without Braintrust. ” How Coursera builds next-generation learning tools 45x More feedback with AI grading How Notion evaluates AI at scale across 70 engineers &lt;24hrs To deploy a new frontier model Josh Clemm , VP of Engineering “ We can run hundreds to thousands of experiments with Braintrust. ” Luis Héctor Chávez , CTO “ Braintrust helped us identify several patterns that we wouldn&#x27;t have found. ” How Graphite builds reliable AI code review at scale 5% Reduction in negative rules Sarav Bhatia , Sr. Dir. of Engineering “ Braintrust is the core of our evaluation framework process. ” Play Trace everything Sign up Product Observe See what your agents are doing in production Evaluate Define what good means and measure against it Discover Find patterns you didn&#x27;t know to look for Resources Documentation Complete guide to Braintrust AI evaluation platform Integrations AI provider and SDK framework integration guides Eval foundations Learn how to build evals with Braintrust Encyclopedia A comprehensive encyclopedia of eval terms Cookbook Code examples and practical recipes Changelog Latest updates and feature releases For PMs How product managers can leverage Braintrust For startups Startup program for fast-growing AI teams Articles In-depth articles and insights Company Pricing Flexible pricing plans for teams of all sizes Customers How leading teams build AI with Braintrust Blog Latest insights on AI evaluation and LLM best practices Careers Join our team building the future of AI evaluation Contact us Get in touch with our team Manifesto The principles of Braintrust Privacy Policy How we protect your data Trust center Security and compliance documentation Community GitHub Open source libraries and tools Discord Join our developer community Newsletter Subscribe to our newsletter for updates X Latest news and updates YouTube Video tutorials and demos LinkedIn Follow us for company updates Copyright ©2026 Braintrust Data, Inc.

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

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Full breakdown

16 pass2 warn10 fail2 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
pass
llms.txt present
Found /llms.txt (14450 bytes), H1 + at least one link present.
100/100
pass
Sitemap present
sitemap.xml reachable and referenced from robots.txt.
100/100
warn
Link response headers
A Link: header is present but carries none of canonical/alternate/describedby — the relations agents consume.
60/100
pass
Canonical URL
Canonical points to self: https://www.braintrust.dev/.
100/100
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 2.2% of HTML weight (6991/316803 bytes). Low. Markup may be crowding out agent-usable text.
17/100
skip
Content without JavaScript
Browser pass unavailable; cannot measure JS dependency.
pass
Heading hierarchy
Hierarchy is well-formed (1 H1, no skipped levels, 22 headings total).
100/100
pass
Cookie wall blocks content
No common consent-modal markers detected.
100/100
warn
Page title
<title> is 75 characters; keep it under 70 so it isn't truncated.
60/100
pass
Meta description
A well-sized meta description is present (162 chars).
100/100
Structured data
pass
JSON-LD present
Found 5 JSON-LD blocks.
100/100
pass
Structured data validates
4/4 checkable block(s) validated cleanly against schema.org. 1 block(s) skipped — type outside the set we check.
100/100
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 ("AI observability platform for agents") with price/CTA ("Start building").
100/100
pass
Reachability
HTTP 200 after 1 redirect.
100/100
Performance
pass
Time to first byte
TTFB 112ms. Healthy.
100/100
skip
Full render time
Full-render time unavailable (browser pass skipped or failed).
pass
Page weight
Initial document is a lean 309 KB.
100/100
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