The agent successfully assembled a comprehensive explanation of HeadCode CMS by combining direct site fetches (homepage, docs, start guide) with GitHub repository content. The site itself is minimally documented for discovery purposes—the agent had to rely heavily on the GitHub README and installation docs to answer the task, since headcodecms.com/ appears to be a landing page with limited detail. The agent filled gaps using prior knowledge about the CMS landscape and web searches, ultimately delivering a coherent answer despite sparse on-site documentation.

• ›Step [1] (homepage) returned HTML but no readable content summary—the agent could not extract positioning or feature details from the main landing page alone.
• ›Step [4] and [6] (GitHub repository and raw README) were the primary content sources, providing the core definition ('open-source CMS for Next.js'), feature list (MCP server, draft/live publishing, Convex backend, llms.txt), and target audience. The README explicitly states the project's philosophy and early-stage status.
• ›Step [10] (start.md installation guide) provided operational context about setup and dependencies but not positioning or pricing.
• ›The site does not publish pricing or competitor comparison information directly—the agent inferred 'completely free' from open-source status and mentioned external service dependencies (Convex, Resend) based on README references, not a dedicated pricing page.
• ›Steps [3], [5], [7], [8], [9] were routing/search steps that pointed to GitHub and comparative articles but did not themselves contain directly usable content; excluded from success_step_ids.
• ›The agent had to assemble 'how it's different' by combining GitHub README philosophy with prior knowledge of CMS alternatives (Sanity, Contentful, Strapi, Payload), since no direct comparison exists on-site.
• ›The site is low in agent-readiness for this discovery task: no dedicated FAQ, pricing page, or structured metadata (schema.org); the agent succeeded by falling back to GitHub (a proxy for authoritative source) and inferring from code-first positioning.