This server defines 6 tools with explicit schemas and descriptions visible in notebooklm_mcp/server.py. However, critical issues prevent a higher score: (1) Tool naming uses 'notebooklm_' prefix rather than action verbs as primary convention, while names are descriptive, they don't lead with verbs like 'list_', 'get_', 'set_' which help LLMs parse intent immediately. (2) Descriptions are minimal (10-50 chars for most tools) and lack WHEN/WHY guidance, parameter relationships, or error recovery hints. For example, 'Check NotebookLM auth status and active notebook' (48 chars) doesn't explain when to call it vs notebooklm_auth_check, or what happens on failure. (3) Most parameters lack per-parameter descriptions, only notebooklm_ask and notebooklm_use_notebook have parameter descriptions; the no-arg tools (login, status, auth_check, list_notebooks) have no parameter descriptions to evaluate, but this is acceptable since they take no parameters. (4) Output schemas are NOT documented, the code shows handlers return a result object with .output and .success attributes, but the response structure is never specified in tool definitions, forcing LLMs to guess what fields to extract from replies. (5) Error handling is minimal, no guidance on retryability, no actionable recovery instructions. (6) No pagination or limit parameters visible, though list_notebooks might return large lists. The rubric baseline is 194 chars avg for tool descriptions; these average ~40 chars. Following pattern:tool and pattern:tool-description, this is a significant gap.

• Add formal output schema definitions to all tools. Example for notebooklm_ask: {'type': 'object', 'properties': {'response_text': {'type': 'string'}, 'query': {'type': 'string'}, 'notebook_id': {'type': 'string'}, 'confidence': {'type': 'number'}}, 'required': ['response_text', 'query']}. Document this in the tool definition, not just in code comments.
• Expand all tool descriptions to 100 - 200 characters minimum. Include WHEN to use (vs. similar tools), WHAT side effects occur, and WHEN to retry. Example for notebooklm_status: 'Check current authentication state and active notebook. Call before any operation to verify login status. Returns auth token validity and active notebook ID. Use notebooklm_login() if auth is invalid.'
• Rename tools to lead with action verbs: notebooklm_status → get_notebook_status, notebooklm_auth_check → check_auth_status, notebooklm_use_notebook → set_active_notebook. This enables LLMs to parse intent from the name alone.
• Add limit and offset parameters to notebooklm_list_notebooks. Example: {'limit': {'type': 'integer', 'minimum': 1, 'maximum': 100, 'default': 20, 'description': 'Max notebooks to return (1 - 100, default 20).'}, 'offset': {'type': 'integer', 'minimum': 0, 'default': 0, 'description': 'Pagination offset (0-indexed).'}}. Document in tool description: 'Returns up to 20 notebooks per page.'
• Consolidate notebooklm_status and notebooklm_auth_check into a single tool (e.g., get_auth_status) or clarify their distinct purposes in descriptions. Currently, LLMs cannot determine which to call and will waste tokens trying both.