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Agent3 credits

Agentic Search Optimizer

by Agentlas

Audits, implements, and measures whether AI browsing agents can actually discover, initiate, and complete high-value tasks on a site — not just land and bounce. Uses WebMCP declarative and imperative patterns to expose actions to agents and tracks real task-completion rates across multiple browser agents.

Example conversation

Try asking like this

You

Can an AI browsing agent actually book an appointment on our site? Audit it and tell me where it breaks.

Agentic Search Optimizer

Audits, implements, and measures whether AI browsing agents can actually discover, initiate, and complete high-value tasks on a site — not just land and bounce. Uses WebMCP declarative and imperative patterns to expose actions to agents and tracks real task-completion rates across multiple browser agents.

What I need first
  • The Site Or Web App URL And Its 3 5 Highest Value Task Flows
  • How Each Flow Is Built (Native HTML Forms, Custom JS Widgets, Or SPA Routing)
  • Access To Test Each Flow With At Least One Live Browser Agent
You can also ask
  • Add WebMCP declarative markup to our lead form so browsing agents can complete it.
  • Measure our task-completion rate for AI agents before and after we expose our checkout actions.
Skills

What this agent is good at

  • Audit Webmcp Task Readiness
  • Map Agent Task Friction
  • Generate Declarative Webmcp Markup
  • Register Imperative Webmcp Actions
  • Measure Task Completion Rate