The agent satisfied the task by assembling a comprehensive explanation of Skaneria from the site's homepage and guide (which contained the core value proposition and marker types) combined with the underlying open-source GitHub project documentation, which provided critical detail about what Skaneria actually does. The site itself is minimal and French-only, forcing the agent to rely heavily on prior knowledge and external sources (GitHub) to construct a complete answer; pricing and competitive positioning were not documented on the site and had to be inferred or sourced externally.

• ›Step [1] (homepage) returned metadata clearly stating 'scanner of invisible characters and AI metadata' and 'free, no account required,' which directly answered the what and pricing questions.
• ›Step [4] (guide page) enumerated the four marker families (invisible characters, homoglyphs, statistical watermark, metadata) but the full content was truncated in the response; the agent had to rely on the meta description and schema context rather than the rendered body.
• ›Steps [23] and [25] (GitHub README) were the only source that explained *how* Skaneria differs from alternatives — by detecting physical markers rather than scoring AI probability — a core differentiator not stated on the Skaneria site itself.
• ›The site navigation failed for `/tarification` (pricing page), `/analyser` (tool), and `/a-propos` (about) — all 404s — meaning the agent could not discover pricing tiers, company info, or API details through site exploration alone.
• ›The site is entirely in French with no language selector, creating a barrier for non-French speakers; the agent noted this explicitly as a discovery friction point.
• ›The agent had to perform 7 web searches to gather context (alternatives, creator identity, GitHub project link) because the Skaneria site itself does not document competitors, team, or technical details.