Sentinel Signal

Audit whether AI assistants, crawlers, and software agents can discover and use a public website.

Audit OpenAPI™ 3.0 and 3.1 API descriptions for agent-tool readiness, operation risk, schema quality, and safety gaps.

Analyze web server access logs to classify AI-user traffic and likely agents or scripts — not just known bots and crawlers — and surface route-level visibility patterns.

Audit a public OpenAPI 3.0/3.1 description for admin, operator, internal, billing, and debug surfaces that should not be publicly exposed.

Capture normalized public web-page snapshots and compare later versions with deterministic, evidence-grade text diffs.

Score how easy a domain is for AI agents to discover, understand, access, cite, and interact with, across six weighted, evidence-backed categories.

Check which known AI crawlers a domain's robots.txt policy allows or blocks.

Discover public API surfaces on a domain and diff them against a prior snapshot to detect meaningful exposure changes.

Discover a domain's likely developer portal, API documentation, OpenAPI/Swagger spec, SDK docs, GitHub, and status page.

Detect and validate a domain's llms.txt (and llms-full.txt), reporting sections, links, and basic structural issues.

Audit public MCP servers for exposed tools, risky capabilities, protocol issues, and deployment readiness.

Compare two OpenAPI/Swagger specs and identify breaking and non-breaking API contract changes between them.

Extract JSON-LD, schema.org types, OpenGraph, and microdata from a public page for machine-readable consumption.