The agent successfully assembled a comprehensive overview of candycode's business model, target customers, and competitive positioning by combining markdown content pages with web search context. However, the site made pricing discovery difficult—candycode does not publish pricing information on any fetched page, forcing the agent to rely on inferred service patterns and search results. The final answer honestly flags this gap, making the response partial rather than fully satisfied.

• ›Steps [21], [23], [27], [28] returned markdown content that clearly articulated what candycode does (React migrations, Sanity CMS migrations, Next.js app router migrations, evergreen subscriptions), who they serve, and their methodology (deterministic reversible migrations, zero downtime, weekly rebases). These pages are machine-readable and directly cited.
• ›The site does not publish a pricing page—steps [3] and [4] both returned 404s for /pricing and /features. The agent had to infer pricing strategy ('custom quotes only') from repeated mentions of 'evergreen subscriptions' and 'maintenance retainers' without actual price points, rates, or service tiers visible anywhere.
• ›Web search (steps [7], [11], [15], [16], [20], [22], [29], [31]) provided discovery context (Y Combinator backing, Sanity/Netlify/Payload partnerships, San Diego location) but did not surface candycode-specific pricing—most search results returned competing products (Candy AI) or generic agency pricing guides. The agent correctly noted this absence rather than fabricating prices.
• ›The site is well-structured for describing services (multiple dedicated migration pages with consistent template structure) but deliberately opaque about commercial terms. The agent had to bridge gaps by inferring 'calm methodology,' 'boutique agency positioning,' and 'bespoke service model' from narrative language rather than explicit service definitions.
• ›The agent correctly identified what it could not find: granular breakdown of evergreen subscription contents, specific case studies with measurable outcomes, and any public price range. This honest labeling of missing information demonstrates good awareness of the site's agent-readiness limits.