Server has 4 tools with basic schemas and descriptions, but significant gaps in parameter documentation, output schema clarity, and error guidance. All tools have descriptions (10-50 chars, below the 50-200 char baseline for LLM optimization). Input schemas present but parameters lack detailed constraints and format guidance. No output schemas documented. Error handling returns generic McpError without recovery guidance. Tool names follow verb_noun convention (list_, get_, update_, run_) but descriptions are minimal. No tool annotations (readOnlyHint, destructiveHint, idempotentHint) despite clear risk profiles (2 WRITE tools, 2 READ_ONLY).

• Add range constraints to numeric parameters: 'page (number, ≥1, default 1)' and 'pageSize (number, 1 - 100, default 20)'. Include in description: 'Page number (1-indexed, default 1). Pair with pageSize to paginate results.'
• Document output schemas for all tools. E.g., list_notebooks returns [{ref: string, title: string, status: string, ...}]. get_notebook returns {content: string, metadata: {ref, owner, created_at}}. This enables LLMs to plan chaining.
• Enhance error messages with recovery guidance. E.g., 'Invalid notebookRef format. Expected username/slug (e.g., john-doe/my-analysis) or full URL. Call list_notebooks() to discover valid references.' instead of generic 'Failed to get notebook'.
• Add tool annotations: mark list_notebooks and get_notebook with readOnlyHint=true; mark update_notebook and run_notebook with destructiveHint=true and idempotentHint=false. This signals to agents which tools are safe to retry.
• Expand tool descriptions to 100 - 150 chars with context. E.g., 'List all Kaggle notebooks you own. Returns paginated results (default 20 per page). Call this first to discover notebook references before downloading or running them.' This guides LLM selection and planning.