The agent assembled a comprehensive overview of PeakTech's business, products, pricing, and positioning by combining web search results, product category pages, and company/service pages—but worked around a poorly agent-readable website where the HTML body was heavily JavaScript-rendered and inaccessible. The site's structure and URLs were navigable, but meaningful content required external search results and prior knowledge to fill gaps left by truncated fetches.

• ›Content-bearing steps were almost entirely web search results (steps 11, 16, 19, 20) and their target pages (steps 13, 14, 17, 18, 21). Direct homepage fetches (steps 1, 3, 12) returned only HTML metadata/head tags with no readable body content—the site is heavily client-side rendered.
• ›The agent successfully inferred the B2B business model, product range (multimeters, oscilloscopes, thermal cameras, power supplies), manufacturer status, and OEM customization services from search snippets and company/service page titles and URLs, not from the fetched page bodies.
• ›Pricing was partially recovered from search result snippets and product category URLs, but the agent explicitly flagged inability to access full pricing tiers, bulk discounts, or clear B2B pricing structures due to inaccessible page content.
• ›The agent relied heavily on prior knowledge (ZoomInfo, company founding date 1957, ISO certification 2019) and competitor positioning inferred from web search context, not from peaktech.de's own statements.
• ›Site structure is URL-friendly (logical hierarchies like /uk/Products/Electrical-engineering/Multimeters/Basic-multimeters/) but the site is not fetch-friendly—all substantive answers required routing through search or guessing URLs, then extracting from search snippets rather than page bodies.