Four tools with minimal descriptions (10-30 chars each) and incomplete schemas. Tool names follow verb_noun convention (search_site, get_page_content, list_content, get_sitemap), which is good. However, descriptions are far below the 50-200 char baseline for LLM-optimized tools. Input schemas are present but sparse: search_site has 'query' and 'limit' with basic type info; get_page_content has only 'uri'; list_content has 'type'; get_sitemap has empty input. No output schemas documented. No error handling guidance. No parameter constraints (enums, ranges, formats). All tools are read-only (low risk), but lack the depth needed for confident agent selection and execution.

• Expand tool descriptions to 80-150 chars. Example: 'search_site: Search the site index by keyword. Returns up to [limit] matching URLs with titles and snippets. Use this first to discover relevant pages before calling get_page_content.'
• Document output schemas for each tool. Specify fields returned (e.g., search_site returns [{url, title, snippet, relevance_score}]).
• Add parameter constraints: search_site.limit should have min/max (e.g., 1-50); list_content.type should be an enum (e.g., 'page'|'post'|'guide').
• Add error handling guidance: 'If no results found, try broader keywords or call get_sitemap to explore available content.'
• Document pagination for list_content and search_site (offset/limit or cursor-based) and return total_count so agents know if more results exist.