A structured report identifying trust concerns, competitors, and prioritized improvements to help the page win more AI recommendations, along with specific evidence calls for verification.
The agent first checks available credits using get_credits to ensure sufficient funds. It then calls analyze_url with the target public landing-page URL and a unique requestId. The agent polls get_run with the status section until the run is terminal, checking reportQuality and missing participants. Finally, it reads the summary and actions, following evidenceCalls or verdicts to understand the exact responses and citations, allowing the user to verify the evidence before making revisions.
- Category: Software development
- Effect: Read-only
- MCP servers: Agentzia MCP (https://koskamo.com/explore/agentzia-mcp)
- Source: MCP documentation | Agentzia (https://www.agentzia.dev/docs)
- Source quote: "Ask your agent: “Use Agentzia to analyze this landing page, explain the report, and propose the highest-priority improvements.”"
- Playbook page: https://koskamo.com/explore/use-cases/analyze-landing-page-for-ai-visibility-and-propose-fixes
Prompt: Use Agentzia to analyze this landing page, explain the report, and propose the highest-priority improvements. First check my credits, then run the analysis for https://example.com, poll for completion, and summarize the key actions and evidence.