All 4 tools have minimal descriptions (10-50 chars) and incomplete input schemas. Tool names lack action verbs (search, query, entities, graph_query are weak). No output schemas documented. Parameters have type info but lack descriptions explaining constraints, formats, or when to use each tool. No error handling guidance. No pagination support despite tools returning lists. Schemas are present but sparse, missing required field documentation, constraints, and response structures. This server falls well below production baseline (194 chars avg description, 100% param descriptions in A+ tools).

• Expand each tool description to 100-200 characters. Example: 'search' → 'Search the knowledge base using full-text search. Returns matching guides with titles, IDs, and relevance scores. Use this to find guides by topic or keyword. For relationship exploration, use graph_query instead.'
• Add descriptions to all parameters. Example: 'query' param → 'Search query string. Supports natural language keywords (e.g., "authentication patterns") or exact phrases in quotes. Minimum 2 characters.'
• Document output schemas for each tool. Example: search() returns {results: [{id: string, title: string, score: number}], total: number}. This enables LLMs to extract the right fields for downstream calls.
• Rename tools with clearer verbs: 'search' → 'search_guides', 'query' → 'get_guide_by_id', 'entities' → 'list_entities', 'graph_query' → 'search_knowledge_graph'. Verb_noun naming helps LLMs parse intent.
• Add pagination to entities: accept offset/limit, return total_count and next_offset. Cap results at 50 items per call to prevent context window exhaustion.