20 tools across 3 domain servers (Fedlex, I14Y, LINDAS). All tools are READ_ONLY with basic verb-noun naming (read_, get_, list_, search_, query_). Descriptions are present but minimal (15-80 chars), below the 194-char baseline for A+ tools. No input schemas visible in provided source code, cannot verify parameter types, constraints, or descriptions. Output schemas not documented. Error handling not evident. Tools appear well-composed (single responsibility) but lack the rigor expected for production agent integration.

• Add explicit JSON Schema input definitions to all tools. Include parameter types (string, integer, array), constraints (enum, minLength, pattern), and descriptions (50 - 100 chars each). Example: search_text should document 'query' (string, required), 'document_id' (string, optional), 'limit' (integer, 1 - 100, default 20).
• Expand tool descriptions to 100 - 200 chars. Follow the pattern: '[WHAT] [WHEN] [RETURNS]'. Example: 'Search text within a Fedlex document by keyword. Use this to find specific articles or sections. Returns matching text snippets with line numbers and context.'
• Document output schemas for all tools. Specify field names, types, and whether results are paginated. Example: list_datasets returns {datasets: [{id, name, description}], total_count, next_cursor}.
• Add error handling guidance. For each tool, document common failure modes and recovery steps. Example: 'If document_id not found, call search_text() first to discover valid IDs. If SPARQL endpoint times out, retry after 5 seconds.'
• Rename tools lacking action verbs: article_history → get_article_history, subdivisions → list_subdivisions, vocabulary → get_vocabulary, related_topics → list_related_topics.