The agent successfully gathered enough information to explain Harbor's core offering, target audience, and pricing structure from the site itself, then supplemented with external platform comparisons to contextualize differentiation. The site was moderately navigable—core pages were reachable and clearly structured, but pricing remained vague and use-case examples were sparse, requiring the agent to flag gaps rather than fill them.

• ›Steps [1], [5] (about page) provided the clearest positioning: 'all-in-one agent execution layer' with workspace-scoped isolation, auditability, and agent-native design. These were fetched directly and formed the backbone of the 'What They Do' section.
• ›Pricing page [2] confirmed three tiers but revealed deliberate opacity: 'custom pricing' for Workspace and Enterprise, with a call-to-action to 'contact sales.' The agent faithfully reported what was published rather than guessing dollar amounts.
• ›The agent discovered alternatives (LangGraph, Composio, n8n, CrewAI) via web search [7], not from Harbor's site. Harbor's own pages contain no competitive comparisons, so the 'How It's Different' section relied on external context to position Harbor relative to known alternatives.
• ›Navigation was straightforward for core pages (homepage, /pricing, /about), but /features returned 404, and /docs redirected to a subdomain (docs.tryharbor.ai). No broken links were followed to completion; the agent adapted by working with what was accessible.
• ›The agent identified and called out genuine information gaps (unclear 'last next-tool problem' tagline, no real-world use-case examples, vague beta status) rather than inventing details—a sign of appropriate confidence boundaries.